\r\n\tSome nematodes are directly transmitted through the environment while some are indirectly transmitted as they require vectors usually arthropods for them to be transmitted from one host to another. Some nematodes are food and waterborne. Domestic and wild Animals are also affected by a barrage of nematode infections and some of these infections are transmissible to man. The book also provides insights into these zoonoses and what we should be doing to prevent and control the nematode infections of which proper and adequate diagnosis is indeed essential. This book intends to provide the reader with a comprehensive overview of nematode infections in all the aforementioned critically important and ineludible subject areas.
",isbn:"978-1-78985-336-0",printIsbn:"978-1-78985-335-3",doi:null,price:0,slug:null,numberOfPages:0,isOpenForSubmission:!0,hash:"4310c447926737005796ba986c60c3e5",bookSignature:"Associate Prof. Omolade Olayinka Okwa",publishedDate:null,coverURL:"https://cdn.intechopen.com/books/images_new/8727.jpg",keywords:"Parasitic worms, Microfilariae, Insect vectors, Life cycles, Filarial nematodes, Arthropods, Geohelminthes, Soil, Transmission, Animals, Sanitation, Antihelminthic drugs",numberOfDownloads:null,numberOfWosCitations:0,numberOfCrossrefCitations:0,numberOfDimensionsCitations:null,numberOfTotalCitations:null,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"January 21st 2019",dateEndSecondStepPublish:"February 11th 2019",dateEndThirdStepPublish:"April 12th 2019",dateEndFourthStepPublish:"July 1st 2019",dateEndFifthStepPublish:"August 30th 2019",remainingDaysToSecondStep:"5 days",secondStepPassed:!0,currentStepOfPublishingProcess:3,editedByType:null,editors:[{id:"99780",title:"Associate Prof.",name:"Omolade",middleName:"Olayinka",surname:"Okwa",slug:"omolade-okwa",fullName:"Omolade Okwa",profilePictureURL:"https://mts.intechopen.com/storage/users/99780/images/system/99780.jpg",biography:"Omolade O. Okwa has Ph.D. Parasitology (1997), M. Sc Cellular Parasitology (1992) and B. Sc (Hons) Zoology (1990) all from the University of Ibadan, Nigeria. She completed and obtained her West African School Certificate (WAEC) from Ikeja High School, G.R.A Ikeja, Lagos, Nigeria She was a recipient of Commonwealth fellowship supported by British Council tenable at Center for Entomology and Parasitology (CAEP), School of Life Sciences, Keele University, Staffordshire, United Kingdom. She was a visiting Honorary Visiting Research Fellow at Keele University from 2005-2007. She is a member of Malaria Society of Nigeria (MSN), Nigerian Society of Experimental Biology (NISEB), Nigerian Society for Parasitology (NSP), Science Association of Nigeria (SAN, Zoological Society of Nigeria (ZSN) and the Vice- Chairperson, Organization of Women in Science, (OWSG), Lagos State University (LASU) chapter. She is presently a Professor of Zoology at the Faculty of Science, Lagos State University, Nigeria. She teaches and supervises research at the undergraduate and graduate levels. She headed the Department of Zoology and Environmental Biology, 2003-2004, 2007-2010 and 2014-2016 at LASU. She has 51 publications consisting of 42 scientific research publications in local and international journals, 5 scientific reviews and 4 books. 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From chapter submission and review, to approval and revision, copyediting and design, until final publication, I work closely with authors and editors to ensure a simple and easy publishing process. I maintain constant and effective communication with authors, editors and reviewers, which allows for a level of personal support that enables contributors to fully commit and concentrate on the chapters they are writing, editing, or reviewing. I assist authors in the preparation of their full chapter submissions and track important deadlines and ensure they are met. I help to coordinate internal processes such as linguistic review, and monitor the technical aspects of the process. As an ASM I am also involved in the acquisition of editors. 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The autonomous robot and vehicle industry has had an immense impact on our economy and society and this trend will continue with biologically inspired neural network techniques. Biologically inspired intelligence, such as biologically inspired neural networks (BNNs), is about learning from nature, which can be applied to the real world robot and vehicle systems. Recently, the research and development of bio-inspired systems for robotic applications is increasingly expanding worldwide. Biologically inspired algorithms contain emerging subtopics such as bio-inspired neural network algorithms, brain-inspired neural networks, swam intelligence with BNN, ant colony optimization algorithms (ACO) with BNN, bee colony optimization algorithms (BCO), particle swarm optimization with BNN, immune systems with BNN, and biologically inspired evolutionary optimization and algorithms. Additionally, it is decomposed of computational aspects of bio-inspired systems such as machine vision, pattern recognition for robot and vehicle systems, motion control, motion planning, movement control, sensor-motor coordination, and learning in biological systems for robot and vehicle systems.
One of the applications of biologically inspired intelligence techniques on the robot navigation is complete area coverage navigation of autonomous mobile robots. Complete area coverage (CAC) is an essential issue in mobile robots, which requires the robot path to pass through every area in the workspace. Many robotic applications require CAC, e.g., cleaning robots [1, 2, 3, 4, 5, 6], vacuum robots [7], painter robots, autonomous underwater covering vehicles, de-mining robots [8], land mine detectors [9], lawn mowers, automated harvesters [10], agricultural crop harvesting equipment [11], and window cleaners [12]. CAC can be completed by a single robot or multiple robots.
Nowadays, cooperative coverage by a multiple robot system is becoming increasingly important. The cooperative area coverage by multiple robots can improve the efficiency and complete the work more quickly than a single robot. These robots may share the coverage tasks and thus reduce the time to complete the coverage task. Additionally, if one of the robots fails, the rest will fulfill the missions, therefore, the coverage by robots is able to improve reliability and robustness. For instance, in de-mining applications, coverage reliability, an important factor, is enhanced by using cooperative multirobots. In some cleaning applications, the workspace (e.g., a stadium) needs to be cleaned in a limited amount of time. Thus, it requires multiple robots to work in a cooperative manner.
Multi-robot coverage has been extensively studied using various models. Depending on whether a map is required for the multirobots, the coverage models may be categorized as off-line and on-line algorithms [13]. Off-line algorithms require a map of workspace for robots (e.g. [14, 15, 16]), while on-line algorithms do not need an environmental map (e.g. [17, 18, 19, 20, 21]). Previous research on area coverage may be classified into cell-decomposition-based model (e.g. [15, 16, 21, 22, 23, 24]), spanning-tree-based approach (e.g. [14, 18, 23, 24, 25]), behaviour-based model (e.g. [26, 27, 28, 29, 30]), graph-based model (e.g. [20, 31, 32]), depth first search approach (e.g. [18, 19]), Frontier-based model (e.g. [33, 34, 35, 36, 37]), and others (e.g. [38, 39, 40, 41]).
Many multi-robot coverage algorithms are based on cell decomposition. Cell decomposition methods break continuous space into a finite set of cells. After this decomposition, a connectivity graph is constructed according to the adjacency relationships between the cells. From this connectivity graph, a continuous path can be determined by simply following adjacent free cells from the initial point to the goal point. Oh et al. [6] developed a triangular cell decomposition method for unknown environments for CAC. This method combines triangular cell decomposition, a template-based approach, and a wall following navigation algorithm for CAC. It can only deal with a single robot CAC. Wagner et al. [21] proposed multi-robot coverage algorithms to explore and cover an unknown environment by approximate cell decomposition approach. The group of multiple robots has limited sensors and no explicit communication. Kurabayashi et al. [15, 16] proposed an exact cell decomposition off-line coverage algorithm for multiple cleaning robots using a Voronoi diagram and boustrophedon approach, where a cost function is defined to obtain a near-optimal solution of the collective coverage task. The approach can avoid overlaps of sweeping areas. The algorithm needs to consider in advance the knowledge of the workspace with known obstacles.
Gabriely and Rimon [42] suggested a spanning tree coverage approach with single robot. It divides up the workspace into discrete cells and generates spanning tree of graph induced by the cells. The robot is able to cover every point precisely once and travel an optimal path in a grid-like representation in the workspace that achieves complete area coverage. Hazon and Kaminka [14] developed a complete and robust multi-robot spanning-tree coverage (MSTC) algorithm based on approximate cell decomposition. Afterwards, the coverage efficiency was improved by a multi-robot forest coverage (MFC) algorithm of approximate cell decomposition proposed by Zheng et al. [23]. Hazon et al. [18] successfully extended the spanning tree work with single robot of Gabriely and Rimon [42] and their off-line work [14] into on-line multi-robot coverage and improved the coverage efficiency.
Behaviour-based strategy for a multi-robot system employs relatively little internal variable states to model the environment and makes fewer assumptions about their environment, thus it is more robust. The cooperative coverage by multirobots with the feature of reactive planning model is implemented by designing individual and team behaviours. Jung et al. [29] combined the advantages of spatial and topological map representations of the environment in a behaviour-based framework for cooperative cleaning of multiple robots. The cooperative multi-robot coverage missions can be accomplished by unifying paths in navigation, cooperation, communication and reactive behaviours [43]. The more detailed explanation of the implementation of the architecture for behaviour-based agents for cooperative multiple cleaning robots are given in [30]. Balch and Arkin [26] proposed a behaviour-based multi-robot approach for coverage, in which the robots are developed with various goal-oriented behaviours for navigation. Recently, Fang et al. [27] used a behaviour-based coverage approach for multirobots to efficiently define the region in which an optimal solution can be found in unknown environments. Most recently, an idea of a leader robot and other follower robots for planning path and controlling robots was proposed using the behaviour-based model [44].
The idea of building up a graph of environment is used for multi-robot coverage. One workspace is decomposed into subregions called cells and therefore a graph may be constructed. The underlying idea of graph-based approach is that multiple robots traverse every edge of the graph to achieve the cooperative coverage. Wagner et al. [20, 31] proposed an approximate cellular decomposition approach for multi-robot coverage to decompose the environment. They employ a dirt grid on the floor for communication among robots. The robots communicate with each other by leaving traces. A graph is built up for representation of the workspace to be covered. Each edge is assigned to two “smell labels”. If an edge is traversed, it is marked by a fresh trace of odour. Recently, to benefit from the graph-based approach, Williams and Burdick [32] constructed a graph for multi-robot navigation. An improved graph representation of the task is applied for boundary coverage problem and a graph algorithm is developed for the boundary coverage problem.
A robot can obtain updated knowledge for its environmental map if it moves to a frontier since frontiers are this type of areas that are on the boundary between open space and uncovered space. With the movement of single robot or multiple robots to successive frontiers, the robots can obtain sufficient information to build up and update the maps for coverage mission. Yamauchi [36, 37] adopted a Frontier-based coverage approach, which leads each robot to the closest unknown region, represented by frontier between the free and unknown workspace to produce a robust autonomous cooperative coverage strategy. The technique builds a global map of the environment, which is analysed to locate the frontiers around the robot and environments. Recently, Burgard et al. [33] and Ko et al. [35] developed algorithms to compute utilities of frontier cells to cover different areas of the unknown environments.
Some previous work combines several approaches to take an advantage of different benefits. For instance, Rekleitis et al. [19] split a terrain by an exact cell decomposition method and a tree was built with each subregion as a node. A centralized depth first search (DFS) algorithm is employed for robots to traverse the unknown region and thus the entire areas are explored and covered. Hazon et al. [18] recently extended the spanning tree work with single robot [42] and their own off-line work [14] into on-line multi-robot coverage. Their spanning trees are constructed by a DFS-like procedure. The effective, robust, and complete multi-robot coverage is implemented. Gossage et al. [34] combined the advantages, in order to obtain robust cooperation, of local Frontier-based approach and global graph-based representation of unknown environments for the cooperation of multirobot. Most recently, Zavlanos and Pappas [45] combined a distributed multi-destination potential field approach and a dynamic assignment algorithm for coverage motion planning of multiple robots.
In some other methods, multirobots collect the incoming sensor information of every single robot in a team to cooperatively perform coverage in unknown environments. In most cases, cell decomposition method is used to split terrain and ensures complete coverage [46]. Butler [38, 39] proposed a distributed cooperative coverage algorithm for multirobot, which performs independently on each robot in a team with a rectilinear environment. The algorithm employs only intrinsic contact sensing knowledge to determine the boundaries of the environment. Recently, Boonpinon and Sudsang [47] developed a multi-robot mapping and area coverage approach using a centroidal Voronoi diagram where a team of robots exchange limited sensory information by explicit communication. Latimer et al. [40] and Rekleitis et al. [41] proposed a coordinated multi-robot approach for a coverage mission while the workspace is typically broken down into distinct regions by Boustrophedon decomposition and different region is covered by robots with back-and-forth motions. Most recently, Schwager et al. [48] suggested a near optimal sensing configuration for coverage by a group of robots by learning the distribution of the sensory information in environments.
Although there have been many studies on multi-robot coverage and most attempt to improve completeness, very few existing coverage algorithms focus on robustness. The MSTC algorithm proposed by Hazon and Kaminka [14] is robust and complete. The robots with this algorithm would cover cells more than once. Neural network methods have been broadly applied to robot motion planning, control and coverage (e.g. [2], [49, 50]). However, most of them deal with single robot for coverage (e.g. [2, 5, 6]). Some neural network models require learning procedures (e.g. [51, 52], which are computationally expensive and difficult to achieve CAC in real time.
In this chapter, a neural dynamics approach is proposed for multi-robot area coverage applications. Mobile robots have no collisions among themselves and can avoid obstacles and cooperatively work together to improve cleaning productivity effectively. The proposed approach is capable of performing CAC for multirobots, autonomously without any human intervention. Each robot treats the other robots as moving obstacles. The neural activity landscape of each robot is able to guide the robot to follow a reasonable path and to cooperate with other robots. In this paper, the real-time path is generated by employing a neural network algorithm, without either any prior knowledge of the environment or any pre-defined template. No learning procedures are required in the proposed algorithm. The advantage of such CAC strategy using the proposed neural networks is that the robots do not repeat the previous covered locations. The simulation studies demonstrate that the robustness and fault-tolerant can be ensured if one of the robots fails. It is computationally simple and flexible to implement the proposed algorithm on autonomous CAC as no learning procedures and no templates are required. The dynamics of each neuron is characterized by a shunting equation or an additive equation derived from the membrane model for a biological neural system [53]. There are only local lateral connections among neurons. Thus, the computational complexity depends on the neural network size. The varying environment is represented by the dynamic activity landscape of the neural network. Multiple robots share the environmental information, which is collected from the sensors mounted in the workspace, and all the sensors on individual robots.
The effective, complete, and robust cooperate area coverage is achieved by the proposed neural dynamics model. The term “cooperate” is in the sense that multiple robots can work together to achieve a common coverage mission more efficiently and more quickly. “Robust” is in the sense that the multi-robot system does not fatally failed or is not wholly affected by a single robot failure. In this chapter, cleaning robot is used as an example, but the method is applicable for any CAC applications.
The rest of the chapter is organized as follows. In Section 2, the biological inspiration, model algorithm, and stability analysis of this neural dynamics-based approach to real-time collision-free CAC by multirobot are addressed. Several simulation studies aimed to demonstrate the completeness, robustness, and effectiveness of the proposed model for CAC are performed and described in Section 3. Finally, several important properties of the proposed model with CAC are concluded in Section 4.
In this section, the originality of the proposed neural network approach to real-time CAC for multiple mobile robots will be briefly introduced. Then, the fundamental concept and model algorithm of the proposed approach will be presented.
In 1952, Hodgkin and Huxley [53] proposed a computational model for a patch of membrane in a biological neural system using electrical circuit elements. In this model, the dynamics of voltage across the membrane,
where
By setting
where
The fundamental concept of the proposed model is to develop a neural network architecture, whose dynamic neural activity landscape represents the dynamically varying environment. By properly defining the external inputs from the varying environment and internal neural connections, the uncovered areas and obstacles are guaranteed to stay at the peak and the valley of the activity landscape of the neural network, respectively. The uncovered areas globally attract the robot in the whole state space through neural activity propagation, while the obstacles have only local effect in a small region to avoid collisions. The real-time collision-free robot area coverage is accomplished based on the dynamic activity landscape of the neural network, the previous robot position and the other robot positions, to guarantee all locations to be covered and the robots to travel along smooth, continuous paths with less turning.
The proposed topologically organized model is expressed in a 2D Cartesian workspace
where
where
The architecture of a 2D neural network with three-layer (r = 1, 2, and 3) neighbouring neurons with regard to the central neuron C(m,n). The i th neuron has only eight lateral connections to its neighbouring neurons that are within its receptive field.
The proposed network characterized by Eq. (3) ensures that the positive neural activity can propagate to all the state space, but the negative activity only stays locally. Therefore, the uncovered areas globally attract the robot, while the obstacles only locally prevent the robot from collisions. The positions of the uncovered areas and obstacles may vary over time, e.g., there are moving obstacles (other robots); the covered areas become uncovered again. The activity landscape of the neural network dynamically changes due to the varying external inputs from the uncovered areas and obstacles and the internal activity propagation among neurons. For energy and time efficiency, the robot should travel a shortest path (with least re-visited locations) and make least turning of moving directions. The robot path is generated from the dynamic activity landscape and the previous robot position to avoid least navigation direction changes. For a given current robot position in
where
where
In a multi-robot system, if there exist two robots that work together to sweep in a workspace, it may be viewed as a multiple neural network system [58]. Each robot needs one neural network and all robots share the same workspace information. Each robot treats the other robots as moving obstacles recognized by the sensor information so that they can avoid collisions and cooperatively work together. Each robot has its own neural network which is updated dynamically on the positions of the robot. The environmental knowledge is also dynamically updated, which is sensed by robots via the sensor information. Every position is flagged by a number in Eq. (4). Once one of the multiple robots moves to Position
The proposed neural network is a stable system. The neural activity
which is Grossberg’s general form [54]. It can be proved that Eqs. (2) or (3) satisfies all the three stability conditions required by the Grossberg’s general form [54]. The rigorous proof of the stability and convergence of Eq. (7) can be found in [59]. The dynamics of the neural network is guaranteed to converge to an equilibrium state of the system. Eq. (3) combined with the previous robot position ensures to generate complete coverage path. At the beginning, when
It is inevitable that multiple cleaning robots have to deal with a deadlock situation in real-world applications. When a cleaning robot arrives in a deadlock situation, i.e., all the neighboring positions are either obstacle or covered locations, all the neural activities of its neighboring locations are not larger than the activity at the current location, because its neighboring locations receive either negative external input (obstacles) or no external input (covered locations), and all the covered neighboring locations passed a longer decay time as they were covered earlier than the current location [see Eq. (3)]. In the proposed model, the neural activity at the deadlock location will quickly decay to zero due to the passive decay term
The complexity is squarely proportional to the degree of discretization. There are only local connections among neurons. If the workspace is an
There have been many studies on the CAC implementation of mobile robots using various approaches [46, 61, 62, 63]. The selection of on-board sensors is equally important as the development of CAC navigation algorithm itself. The performance of multirobots will depend on both CAC navigation algorithm and the placement of on-board sensors. Appropriate amount of sensors is key for the multi-robot system. Use of excessive amount of sensors will cause the increase of cost of robots [62, 64]. Each robot in this multi-robot system has the same configuration. The basic configuration of the robot consists of CPU, memory, sensors, DC motors, wheels, brush or dustpan, and an on-board power supply (e.g., rechargeable battery) [61].
Sensors equipped on the robots are assumed to be imaging sensors (e.g., camera and position sensor) and rang sensors (e.g., infrared sensors, sonar, ultrasonic sensors or small radar). With on-board sensors, mobile robots can construct current environmental map around the robots [2, 65]. Ultrasonic sensors are employed for range measures due to their simplicity, flexibility, adaptability, low cost, and robustness. The interpretation of the sonar readings is helpful to build an environmental map. The small angular resolution of infrared sensors makes it suitable for CAC with back-and-forth motion. Infrared sensors are capable of reducing angular uncertainty caused by accumulated error of dead reckoning [63]. In addition, several cameras are suspended from the ceiling of workspace that provides global environmental information to robots [66].
Wheels, DC motors, and discretized environments: each robot is driven by two DC geared motors with two wheels installed to the gear axis. The 2D Cartesian workspace is discretized into squares as most other CAC models. The diagonal length of each discrete grid is equal to a robot sweeping radius, which is the size of the robot effector or footprint (Figure 2). The robot in this paper is assumed to be round in shape and a square is embedded in this round as robot’s body. A robot sweeping range, which is the size of the robot effector, is proportional to the size of each square. The size of a robot is slightly larger than that of each square. Two wheels driven by DC motors are mounted on shafts with brush or dustpan. The wheels are axle mounted and supported using two sealed ball bearings [see Figure 3(a)]. Note that ball bearings do not appear in Figure 3. New design is assumed that the wheels have capability to rotate at any directions on the floor make the robots flexibly turn in the workspace. For example, Figure 3(b) shows that the robot turns clockwise and counterclockwise 45
Discretized square enclosed by sweeping area.
Two wheels driven by DC motors are mounted to the robot. (a) The robot; (b) the robot rotates clockwise and counter-clockwise 45°.
The proposed model for CAC is performed by simulation experiments in C++ in this section. The approach is capable of performing CAC for multiple cleaning robots, autonomously without human operation. Two or more mobile robots can cooperatively sweep in indoor environments so as to improve the work productivity. Each robot is required to not only clean its own floor but also cooperate with others to perform the cleaning tasks. In this section, the proposed approach is first applied to multiple robots for cooperative coverage in a corridor-like environment. Then, cooperative coverage in an indoor room environment is studied. Next, it is applied to cooperative coverage in a warehouse environment. Finally, four cleaning robots working together to sweep a sport field is simulated.
To illustrate the cooperative coverage by a multi-robot system, the proposed model is applied to a cooperative coverage with obstacle avoidance in a corridor-like environment. In the simulation for the multi-robot system, there are two neural network systems for these two robots that share mutual external input signals from the sensor information representing environmental knowledge. Each neural network has
Cooperative coverage in a corridor-like environment. (a) When Robot 1 reaches Position B188 and Robot 2 Position B22419; (b) when two robots fulfill the coverage task.
The neural activity landscape of the neural networks for the corridor-like environment case when Robots 1 and 2 reach (a) Positions A1517, A22710; (b) B11213, B22014; (c) C11515, C21712; (d) D1124, D22023; (e) E1176, E21521; and (f) F1256, F2721.
These two robots meet at the middle section of the corridor at Positions
To investigate the flexibility and adaptability of cooperative coverage by multiple robots, the proposed model is applied to a warehouse environment with wall-like obstacles placed in different positions (Figure 6). For each robot, the neural network has
Cooperative coverage in the warehouse environment. (a) Robots 1 and 2 reach Positions F1(28,29) and F2(27,30); (b) two robots work cooperatively.
Robots 1 and 2, respectively, work in the lower half and upper half sections of the workspace. However, they can also assist each other, in other words, one robot can aid to cover the other areas if it has already covered its own column. In this simulation, they start from the same side in the workspace. Robot 1 represented by a solid dot starts from the lower left corner
The wall-like obstacles have influence over the cleaning assignments of two robots. The robot paths that these two robots meet at the middle of the workspace are shown in Figure 6(a) when they reach Positions
The neural activity landscape of the neural networks for the warehouse environment when Robots 1 and 2 reach (a) Positions A1115 and A2116; (b) B175 and B2423; (c) C11215 and C21022; (d) D11425 and D21426; (e) E1164 and E2165; and (f) F12829 and F22730.
These two robots are responsible for the different areas in the warehouse and sweep their own regions. Due to the placement of obstacles, these two robots get through different amounts of sweeping assignments. For instance, when Robot 1 arrives at Position
The proposed model is further applied to cooperative coverage in a sports field environment by four cleaning robots, where there exist four neural network systems and the four cleaning robots share mutual external input signals from sensory data representing the environmental information. Each neural network has
CAC of four mobile robots in a sport field environment. (a) The robot paths when four meet at the centre; (b) the entire robot paths after each robot returns its home position.
After they meet at the central area, where there is a deadlock situation [2], i.e., Robot 1 is at
To verify the robustness and effectiveness of the proposed model, it is applied to a complicated case of cooperative coverage in an indoor environment, where there exist seven sets of obstacles with different sizes and shapes in the workspace as shown in Figure 9. Each neural network has
Complete cooperative coverage in an indoor environment with (a) both robots function properly; (b) a robot failure at Position F22626.
Robot 1 symbolized by a solid circle starts to move from the lower left corner
The neural activity landscape of the neural networks for the unstructured environment case when Robot 1 reaches (a) Position P188; (b) Position Q11613.
Now a simulation is performed to demonstrate the robustness of the proposed model. It is assumed that Robot 2 fails to work at Position
The neural activity landscape of the neural networks for the indoor environment case when Robot 2 fails at F22626 and Robot 1 reaches (a) Position A11119; (b) B1244; (c) C12513.
Multiple robots have the capacity for covering the areas more efficiently than a single robot. In this chapter, a biologically motivated neural network approach to cooperative area coverage by a multi-robot system is proposed, which is capable of autonomously accomplishing collision-free cooperative coverage in CAC environments. The effectiveness of the presented paradigm has been discussed and demonstrated through case studies. Multiple robots can work together to achieve a common coverage goal efficiently and robustly.
It is practical to implement the proposed approach in autonomous area coverage as no learning and no templates are required. The robustness and fault-tolerant can be ensured if some robots fail. The model algorithm is computationally simple. The robot path is generated without explicitly searching over the global free workspace or the collision paths, without explicitly optimizing any global cost functions, without any prior knowledge of the dynamic environment, without any templates, and without any learning procedures.
In the future, some research work will be carried out. First, energy-driven multirobot algorithms associated with deep reinforcement learning will be further studied to explore the minimum-energy cleaning robots. Second, the task allocation and impact of number of robots for the cleaning mission will be addressed. Third, the algorithm will be considered to be implemented on an FPGA-based platform. Finally, SLAM and robot vision will be carried out to make the cleaning algorithms more accurate.
Educational psychology has a long history that has been lost in the dawn of time, hand in hand with the first concerns of Greek philosophers in relation to human thought and their ability to know. However, as a discipline it does not have a transient nature of more than 100 years, a scarce time compared to other fields of knowledge.
It is possible to establish that its birth and development is mainly generated in the twentieth century, spite the identification of a varied range of European precursors such as North Americans [1] in the previous centuries. The birth and consolidation of this discipline, found between the years 1900 and 1920, is sustained and guided by ideologies and conceptual frameworks linked to the behavioral and functionalist perspective of psychology [1, 2], that will print an unmistakable seal of scientificity, evaluation and intervention of the medium to guide such behavior. This seal will be maintained throughout the twentieth century as part of the professional role.
These perspectives of psychology and their cognitivist derivation (cognitive behavioral psychology) were developed on the basis of the conception of the world and the human being of the paradigm of simplicity, which aims to value objectivity, control and reduction of variables [3, 4]. Even though other psychological views populated the twentieth century (psychoanalysis, humanistic psychology, transpersonal or systemic psychology, etc.), they have not had the same impact on educational psychology, as well as on education as a socio-cultural phenomenon, perhaps due to the fact that they search exactly the opposite, that is, the integrity, the subjectivity, the emotional; in other words, the complexity.
With a discipline inspired by the eighteenth and nineteenth centuries, and materialized in the twentieth century, I think it is fair, at the dawn of the twenty-first century, to establish a reflexive, innovative and transformative review of the educational psychology. This is necessary because even with the great amount of knowledge and expertise that has accumulated, educational psychology has not significantly impacted the educational process or contributed to the sociocultural change that is required in these times to learn and teach [5].
What kind of educational psychology does the twenty-first century need? This is a great question to answer. However, little has been done about it [6].
In this chapter we propose a resignification of the work of the educational psychologist in order to establish a complex and non-simplistic discipline that allows facing the essential tensions and dilemmas that have never been clarified [6] such as: what is the identity of educational psychology, and what is the purpose in the generation of knowledge. This desirable horizon, educational psychology from the complexity, requires a crucial tool: the availability of critical thinking. The nature of a professional is to use criticality to generate change, both of themselves as a professional and as a person, as well as of the educational community in which they are located.
The critical concept has different acceptations, on the one hand, it is seen as something decisive or of priority, which must be resolved in a timely manner, and on the other hand, as the constant evaluation of an idea or situation (definition from the Royal Spanish Academy or RAE in Spanish) [7]. In this way, and from a superficial synthesis of these acceptations, critical thinking is a tool that would allow facing relevant situations of the person or the community through questioning and reflection, in order to achieve a change in said situation, and therefore, should be the strategy that allows the work of educational psychologists to promote change as a part of the sociocultural interaction in the educational community, a focus that César Coll was already pointing out in 2001.
Munné [8] has pointed out that the discussion of simplicity and complexity is linked to the search for knowledge, which relates this discussion with an ontological and epistemological analysis with which human beings have explained reality. The preceding is due to the fact that it is a search for knowledge that has guided the development of scientific and professional disciplines. The way in which this search has been based has been to a great extent, although not in a single dimension, on the rationality and reductionism that are characteristics of the traditional and positivist scientific outlook. This has allowed the capturing and understanding of reality in a sequential and orderly manner, and with basic processes of cognition that promote the processing of information in an expeditious and efficient manner, in order to achieve clear, measurable and unambiguous knowledge.
This perspective is oriented by the human need of seeing this reality as something ordered, perfect and harmonious [4, 8], where even the knowledge of the people and the educational theory should also be equally ordered, structured, and specified in stereotyped actions, with a hierarchical, clear and objective management, that leaves out the problems and noises that arise in the educational level (such as learning difficulties, school demotivation, violence and power) as they cannot be explained nor adequately controlled [4, 9].
According to the perspective of the simplistic paradigm, psychology as a scientific discipline (as well as the traditional educational psychology) would fit greatly in that model, as it would present characteristics that are focused on individual attention (preferably), on the assessment of technical knowledge, in the functionality of a pathology, in the standardization of behaviors to behavioral standards (norms), and in the hierarchical relation between the fields of knowledge [6].
Even the history of educational psychology has been influenced by the characteristics of simplicity, as its birth and consolidation seemed to have responded more to pragmatic-conceptual determinations, such as the adherence to the behavioral theory of the 1920s and 1930s, rather than an academic reflection [6]. This adoption of the scientific position (uncritical and amoral), has established a reductionist approach that is focused on the teaching and learning process as a central object of educational psychology [1].
It is necessary to properly recognize the contribution of a scientific view of simplicity that has allowed the conceptual and empirical field of psychology to develop as a serious and respectable discipline, thus, producing the same result in educational psychology. However, nowadays this view has been imposed as the only acceptable paradigm for the development of knowledge and professional performance, generating difficulties in the theoretical, paradigmatic and even technical evolution that this discipline presents in its link with the educational process, which results in an inability to provide adequate answers for the challenges that arise [10].
Therefore, it is necessary to direct our practices toward the development of a perspective centered on complexity, as it is part of our everyday reality, and can give an account of our most human characteristics, the solidary interconnection of the phenomena, and the uncertainty and the contradiction [3]. Its nature is holistic and evolutionary, in constant transformation, and includes the subject as an integral part of the construction of change. It sees knowledge as a multidimensional aspect, integrated by diverse approaches, which allow the integration of diversity, error, interculturality, emotionality and uncertainty [11].
This paradigm is characterized by a transdisciplinary conception of knowledge and praxis, which is achieved through an intricate conformation that must modify itself and, at the same time, modify the subjects that integrate its action, in a constant and participatory manner. In particular, it would allow the generation of a complex, dynamic and non-linear methodology that centrally deals with variability. This paradigm should be endowed with characteristics that are simultaneously so general as to explain phenomena in a vast variety of human situations, which is what science requires, and, at the same time, be able to accept specificities that rescue individuality and subjective contextualization [12].
Thus, in educational psychology, a view that comes from this paradigm is needed to a great extent, due to the fact that education is, precisely, one of the eminently complex areas of human interaction that requires balancing community needs such as discipline, coexistence and the curriculum, with individual needs, motivation and learning demand.
It would imply constructing from psychoeducational knowledge, with awareness, participation and meaning, aiming for a change and allowing it to change us, that is, with a tension between the technical and the critical versus knowledge and practice. In other words, generating knowledge, tools and techniques from theoretical and empirical bases as it has traditionally been done, but reflecting and modifying said elements from experience and interdisciplinary collaboration [6].
The preceding would also imply understanding and valuing the teaching-learning process as a tension between stability and change, given the need to transmit knowledge (what we call recurrence), in order to maintain the culture and, at the same time, to generate new knowledge, to produce what should lead us to change and transformation. In addition, it implies the establishment of a tension between the expertise, with all the knowledge and power that it can grant a person, and the inexperience, with all its ingenuity and dependence, while also valuing the social interaction and feedback that we generate with the other members of the educational community [13]. Finally, it would involve promoting the tension between the construction of knowledge, the techniques and professional identity, and the construction of knowledge based on the expert and inexperienced collaboration of the views, professional and non-professional, of those who share the educational framework.
To achieve this perspective from the complexity, it is of great importance to discuss the tensions of the discipline, as it is through reflection and dialog that we define the limits of knowledge and its adaptation to everyday reality. This does not involve leaving out research and disciplinary conceptualization, but establishing a balance between the latter and the social and cultural reality.
Through this, it would be possible to channel one of the greatest challenges promoted by the perspective of complexity, that is, transdisciplinarity [3]. This concept has been recently developed, due to the evolution that disciplinary groups have experienced in research, as a result of cultural valuation, being an ideal that combines the main values of social constructionism, in clear opposition to the reductionism and disciplinary focus that has been generated in some fields of knowledge that are born from the simplistic view.
The critical perspective is a position in the search for knowledge that allows us to reveal other different perspectives, which opens our understanding toward interpretations different from those given to us by tradition. Critical psychology has its roots in the critical theory of the Frankfurt School, with thinkers such as Horkheimer, Adorno, Marcuse, or Habermas [14].
In this view the acceptance of the world as it is was rejected, with its inequalities and injustices, and with the domination of classes, indicating that reality is not determined by natural reasons, but by historical and particular reasons that lead to a certain order [15]. Some of the most significant, worldwide known, authors of this perspective are Michel Foucault and Paulo Freire. Foucault is mainly known for the redefinition of concepts such as power, knowledge and discourse, as power is not exercised only with sovereignty or laws, nor with weapons or force, but with knowledge. In this sense, knowledge refers to all our opinions and knowledge about reality, to our convictions about basic facts of daily life, as well as to the value parameters we give to such events, good and evil, what is normal, and right or wrong, whether that is to an individual or social organization level.
Freire rescues the human sphere in a more social sense, politically committed with education, and argues that the traditional powers as well as authority impose an inequitable system in which the poor are deprived of their opportunity to participate and change the schemes that maintain said inequity. In addition, he advocates an education that breaks the culture of silence and generates awareness in the oppressed of the cultural and economic causes of their situation, that is, to free the human being through the awareness of their reality and their potential. For this purpose, education must be changed, because this is one of the great mechanisms that reproduce the established order and domesticates individuals in those realities that do not allow them to evolve as human beings [15].
Critical psychology does not act only on dominant theories, it also deals with methods, and its central task is to face the values and practices of psychology that do not review or question the forms of oppression that could be being transmitted or reproduced by them. The questioning, through critical judgment, of the different ways of exercising power, as well as its explicit and implicit manifestations in psychological practice and in daily life, are subject of critical studies, due to the fact that they can be presented as natural ways of being of some situations not discussed or, in some cases, argued as the only appropriate form of social existence.
Criticism as a reflective activity, in a kind of thinking that allows us to analyze the level of foundation of an information or idea, based both on reflection itself and on the reflection of others [16, 17]. In this way, psychology has been developed into two flows, on one hand, from social critical psychology, that is, a more theoretical approach that questions the processes and sociocultural phenomena [18]. And on the other hand, from cognitive psychology, which has developed the concept of critical thinking, which has historically been defined as a type of elaborate thinking, that is, a cognitive process that involves evaluation and reflection [16, 19].
This type of thinking allows the construction of new knowledge, and the strategic use of it in the solution of problems present in everyday life [19, 20, 21]. Critical thinking is also defined as a type of process that is both complex and cognitive, and is composed of interrelated subprocesses that allow a person to evaluate analytically and reflectively process, judge and accept, or reject information produced in social contexts or in scientific studies [22].
However, it should not be considered only as a process oriented toward information but also to action, in a context of problem solving and interaction with other people [23, 24]. Likewise, Saiz [25] states that critical thinking is aimed at the effective resolution of situations that allow achieving wellness.
Taking account of these considerations, it is possible to consider critical thinking as a fundamental tool for the twenty-first century professionals, due to the fact that, currently, society requires professionals with high-quality work and research skills for the development of disciplines. Professionals that will not be influenced by ideological pressures or power groups, but rather, be able to move toward an autonomy of thought [26, 27]. Critical thinking is a fundamental tool in order to achieve the above, as it allows the development of high-level cognitive skills needed to achieve these tasks. This kind of thinking is considered + a tool that allows people to confront situations with less ingenuity while transcending toward the implicit objectives of processes, thus, it is essential for today’s professionals, who must face increasingly complex and diverse social situations [27].
There are some situations that nowadays would benefit educational psychology by using critical thinking as a tool of their performance, as they would allow educational psychology to contribute not only to knowledge but also to social change. One of these situations is related to the relevance and effectiveness of cognitive assessment models and instruments, which are very needed in education; another example is the overcoming of the gap between theory and practice that has characterized various conceptualizations and proposals of educational psychology [6].
It is necessary to understand that the use of critical thinking as part of professional development must consider the purpose of community change in order to achieve greater welfare situations, both individual and collective [25]. This implies serious ethical considerations regarding the way in which we face both the professional exercise and the generation of disciplinary knowledge.
The ethical component in professional construction has been considered as a secondary element in the conceptualization of educational psychology in different cultures [28], due to the fact that usually, as a scientific discipline, it should be axiologically neutral (trait inherited from the paradigm of simplicity). However, this alleged neutrality is unthinkable of achieving in the educational context as its essence is eminently cultural [29].
A proposal with critical thinking in educational psychology needs to consider, among others, the previously seen topics, and complement their conceptual and practical evolution with them. This path is fundamental for the present time, based on the multiplicity of challenges that society, history and politics have brought to the education of the twenty-first century, which affect, I believe directly, this discipline.
Not considering these aspects (a path taken by traditional educational psychology) involves constructing fragmented and reductionist proposals of the human being, the educational process and the sociohistorical and political context [13], this fragmented view has allowed our discipline to be co-responsible and complicit in situations that are seen as negative. For example, the labeling and maintenance of conditions that enabled, and still enable today, discriminatory education of children and young people who present situations of intellectual disability, endorsing an unfair and segregating system.
We must have a reflection in regard to the way in which educational systems are confronted with current social requirements [5], asking, what education does the twenty-first century need? This question can be accompanied by our question stated in the introduction to this chapter. What educational psychology does the twenty-first century education need? The answer is, in my opinion, a critical and complex educational psychology.
A critical educational psychology should be understood as a field of action, training and critical research in the face of situations that negatively affect the educational process, including discrimination in policies and the educational system, which prevent the achievement of an education for all, as well as the recognition of human diversity as a universal right of the human being. In order to achieve this, such education should use critical thinking in massive standardization processes that fail to generate good levels of meaningful or contextualized learning for the vast majority of students [6].
In addition, a critical educational psychology could provide new insights into teaching-learning techniques and processes, so that they are able to generate both a result that is appropriate for students (and that meets quality criteria for teachers), and a process that enables the experimentation of a satisfactory pedagogical relation. And, in this context, this kind of education could support the generation, promotion and prioritization of democratic, liberating and significant relationships among the members of the educational community, in order to promote actions, spaces and policies of school and social coexistence that promote happiness, participation and meaning.
As Redondo points out [30], we should not only expect from educational psychology a proposal based on scientific knowledge that enables a psychological explanation to individual and social problems, and on more than one occasion, that makes a tradition of the psychologization of social problems, but we should also expect a proposal of empowerment that allows educational communities (at any level) to collaborate in the co-construct of their own meaningful educational establishments. The foregoing is relevant due to the fact that that is precisely the purpose of inclusive education [31], which is directly linked to the search for common welfare, through meaningful and dialogued consensus, an idea that can also be achieved through critical perspective.
The school organization is a complex reality as the notion of education itself is complex, thus, its study and action should be approached from the same perspective. It is possible to find the conditions of complexity that pointed out for organizations in general (related to the productive field) [32], and characteristics of socio-affectivity, individual and group evolution, socio-cultural guidelines, political and ethical-regulatory impositions, etc., that are clearly evident in the school organization.
Complexity must be comprehended from the complex [33], which would imply abandoning certain beliefs and paradigms that have strongly marked the field of educational psychology (such as the focus of the teaching and learning process, individualization, and the pathologisation of behaviors). Therefore, the adoption of critical analysis should also be counted, so that a questioning of the concepts, actions, and meanings of those actions is developed [34].
Educational psychology, from a critical and complex perspective, provides an epistemological framework more in line with the great concerns of today’s society, through the development of a disciplinary and professional field that would enable us to collaborate in participative and satisfactory social processes and institutions for professionals of the same area as well as for the community in general, and this certainly would allow us to achieve greater social and political relevance for educational professionals, both for teachers and non-teachers.
This would be achieved through well-known strategies, dialog, reflection, participation, the willingness of agreements; social tools that can be articulated with other logical (scientific and administrative) and technological (digital means of information and communication) tools. In the complex perspective all these elements have a place and are complementary, as they are all products of culture, history and society.
The social-(methodo)logical-technological articulation is carried out through the ethical and social understanding and valuation, which we must give to the educational phenomenon, instead of letting ourselves be caught in traps set by the simplistic view such as the excessive concern for the measurement and evaluation by the quality indicators that have been imposed in the majority of the educational systems in the world [35].
Looking for the meaning of education and the actions that generate learning is one of the central features of the socioconstructivist perspective of learning, and this is exactly what a complex and critical educational psychology should promote, as it is precisely in its core that such constructivist perspective is developed. However, it is necessary to recognize, that given the fact that there is a variety of interests and understandings in a society, we could have different meanings when it comes to education; but there is something that should not be forgotten in this twenty-first century, the fact that the imperative of human rights and the preservation of the environment has been established. For this reason, one of the aspects that can mainstream this disparity of interests and senses is the notion of quality of life, which leads to promote healthy and sustainable environments, respectful and reciprocal human relations, and self-care behaviors [36, 37].
Critical and complex educational psychology must value as an educational purpose the achievement of conditions that ensure a positive and nutritious quality of life for the members of the educational community. In addition, it should promote dialog and democratic consensus among the members of said community, as well as support respect and participation in political and administrative systems. Finally, it should encourage reflection, innovation and adaptation of people, groups and organizations to the incidences of the environment, promoting change at individual, group and organizational levels.
These purposes of critical and complex educational psychology can be achieved through the support of two tools that emerge from the reflection on new perspectives for education and psychology, posed by educators and psychologists interested in the evolution of this field. One of these tools is institutional metacognition, defined as a process of participatory reflection in the educational institution, which allows analyzing information, actions, assumptions and regulations (among others), with the participation of members of the community, in order to make people aware of the ideas, routines and actions that underlie educational decisions, enabling organizational learning and the development of learning communities [38, 39, 40].
A second element of support for the tasks outlined above is the notion of a critical friend as central role of the educational professional; this idea of a critical friend establishes the figure of an agent that questions and promotes the change of educational actors through communication and reflection, guiding these agents to impose significant changes in their decisions and actions [41, 42, 43]. The role of the critical friend is characterized by its empowering nature, to the extent that its action is oriented to promote collaborative work, potentially contributing to generate a global vision of the school [44], and above all, to favor reflective processes on the practices, make explicit assumptions and beliefs that can facilitate the transformation of educational discourses and practices [45].
These tools, among others that can be integrated or constructed, are necessary for educational psychology to maintain the basic elements that define it as a complex and critical proposal, by prioritizing, as previously indicated, reflective, communicational and participation processes in the educational community.
In light of the above, it can be noted that educational psychology presents a history of respectable tradition, contributing to the development of educational processes for just over 100 years. However, nowadays, a great problem related to the relevance and effectiveness achieved by educational psychologists when trying to contribute to educational improvement has begun to be considered [46].
The foregoing does not imply that this discipline is no longer relevant or obsolete, or that it does not share common topics with education and the school system, but rather that it is restricted by a simplistic and technical view of the person, the community and education in general. This simplistic view specifically emphasizes what is less relevant to society and education: The human being.
For this reason, a way to modify that is to redirect the focus and essence of educational psychology, equipping it with tools such as critical thinking, which will provide spaces for reflection and systematic evaluation in the face of its knowledge and the actions that it undertakes with the purpose of establishing effective and significant changes.
The traditional educational psychology cannot offer the answers that the educational challenges of the twenty-first century demand. Therefore, these answers should be obtained through the construction and evaluation of a critical and complex educational psychology, as the latter values the search of senses, collaboration, participatory reflection, innovation and creativity, etc.
The innovative approach proposed, would offer to the educational system, professionals who understand the mixed nature of the teaching and learning process, which are both individual and collective; value the great imperatives of the twentieth century, such as social participation, the valuation of human and civil rights, the democratization of management spaces, the sustainability of the environment and the impact of the human being in their environment, etc. Concerns that are, in turn, related to the topic of quality of life, which should be one of the central purposes of today’s education, as it combines elements of personal well-being, socio-cultural, environmental, etc. [37].
This critical and complex educational psychology can support this response relevant to the current educational situation through at least two tools: the first being the institutional metacognition, a tool for school management that, based on reflection and participatory dialog, can contribute to the search of intentional and significant actions in the learning and coexistence of the educational community and school organization [40]; while the second is the role of a critical friend, a performance that educational psychologists can achieve, through advisory instances that seek to promote resignification for change, both on a personal and institutional level [41, 42].
The benefits of this position of critical and complex educational psychology are that, on one hand, there would be conscious and intentional discipline in the achievement of a quality education, while taking care of the development and respect of human values. On the other hand, there would be an innovative educational psychology that promotes an organizational change, so that it would seek to generate instances in order for the community and the educational organization to be able to adapt, in an appropriate way, to the always dynamic sociopolitical and historical environment.
Likewise, elements that have a greater relationship with the social than with the cultural will be reinforced, which would give a space of importance to people rather than, mainly, to knowledge. The promotion of participation, democratization of decisions and critical reflection will enable people to take more informed and respectful decisions regarding the rights of the community.
On the other side, considering the obstacles and disadvantages that may arise, we cannot fail to mention the impact of the paradigm of simplicity that often restricts the development and the potential of the disciplines. Besides, it should be noted that complexity encourages and respects uncertainty and chaos as fundamental parts of the construction of knowledge, and that is exactly what is often not allowed in educational environments.
In relation to the above, it can be projected as a difficulty, the valuation of change in the educational organization, a central element in a critical psychology, as that change is precisely what should give us new answers and development conditions. However, change is an annoying and unpleasant process for many people, and it is a phenomenon that disrupts the continuum of educational institutions, which suggests that educational agents are reluctant to promote and value change as part of the process of human formation.
Finally, we must consider the same construction of educational psychology as a discipline, and the difficulty of modifying the idea that education responds to individual processes, centered on the cognitive and based on logical and orderly sequentialities, issues that have dominated the definition of this field from the traditional perspective.
The possibility of generating a critical and complex educational psychology, should be a necessary horizon for this discipline, so that we can move forward with the current challenges and face them with relevant and constructive responses from the society and the human being, which would allow us to lay the foundations for a society that reaches, in the near future, these great ideals that we have today.
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