Robot mobile navigation is a hard task that requires, essentially, avoiding static and dynamic objects. This chapter presents a strategy for constructing an occupancy map by proposing a probabilistic model of an ultrasonic sensor, during robot indoor navigation. A local map is initially constructed using the ultrasonic sensor mounted in the front of the robot. This map provides the position of the nearest obstacles in the scene useful for achieving the reactive navigation. The encoders allow computing the robot location in the initial local map. A first path for robot navigation based on the initial local map is estimated using the potential field strategy. As soon as the robot starts its trajectory in real indoor environments with obstacles, the sensor continuously detects and updates the occupancy map by the logsig strategy. A Gaussian function is used for modelling the ultrasonic sensor with the aim of reaching higher precision of the distance measured for each obstacle in the scene. Experiments on detecting, mapping and avoiding obstacles are performed using the mobile robotic platform DaNI 2.0 and the VxWorks system. The resulted occupancy grid is analysed and discussed at the end of this document.
Part of the book: Robot Control
Nowadays, many kinds of robots are used in industries to help in manufacturing or placing objects. However, teaching young people and children about robot design and work can be difficult, turning this into a complicated area for them. This chapter provides a detailed description of the design and implementation of a robotic arm mounted on a mobile robot using the LEGO Mindstorms NXT kit® and the starter kit DaNI 2.0, designed by National Instruments®. The mobile palletizer robot takes a box from place A and navigates in the indoor environment until it reaches a predefined place B. The characterization of the robotic arm is based on a parallel structure considering that the end-effector has only two points to hold the object; the gripper is also built using LEGO®. The robot performs the path computed using an A-star algorithm; moreover, actions like moving up and down, opening and closing the gripper and picking up the box and putting it down are executed by the robotic arm using the central unit of the NXT kit. Each stage of the robot design and implementation is explained in detail using diagrams and 3D graphical views with the aim of illustrating the implementation step by step for educational purposes (mainly for young people or children).
Part of the book: Advanced Path Planning for Mobile Entities