Janusz Bȩdkowski

Institute of Fundamental Technological Research Polish Academy of Sciences

Janusz Bedkowski, Ph.D., D.Sc. in Automation and Robotics, is an adjunct professor at the Institute of Fundamental Technological Research Polish Academy of Sciences. From 2006 to 2018, he collaborated with Industrial Research Institute for Automation and Measurements, Warsaw, Poland, concerning multi robotic inspection-intervention systems development and integration. He was granted a postdoctoral scholarship in the Royal Military Academy (RMA), Brussels, Belgium, funded by Center for Advanced Studies, Warsaw University of Technology. His research interests are: inspection intervention robot systems, semantic mapping including 3D cloud of points and video processing, 6D SLAM, mobile robot operator training with AR techniques and GPGPU computing. From 2017 he is involved in development of the continent scale Simultaneous Localization and Mapping Technologies for autonomous cars in TomTom. He commercialized robotic 3D mapping technologies within the MANDALA company (www.mandalarobotics.com). He is actively working on multi domain robotic search and rescue R&D projects.

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Latest work with IntechOpen by Janusz Bȩdkowski

The objective of this book is to cover advances of mobile robotics and related technologies applied for multi robot systems' design and development. Design of control system is a complex issue, requiring the application of information technologies to link the robots into a single network. Human robot interface becomes a demanding task, especially when we try to use sophisticated methods for brain signal processing. Generated electrophysiological signals can be used to command different devices, such as cars, wheelchair or even video games. A number of developments in navigation and path planning, including parallel programming, can be observed. Cooperative path planning, formation control of multi robotic agents, communication and distance measurement between agents are shown. Training of the mobile robot operators is very difficult task also because of several factors related to different task execution. The presented improvement is related to environment model generation based on autonomous mobile robot observations.

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