Neural Network Based Reactive Navigation for Mobile Robot in Dynamic Environment

0421678 - ÚT 2014 RIV CH eng J - Journal Article
Krejsa, Jiří - Věchet, S. - Ripel, T.
Neural Network Based Reactive Navigation for Mobile Robot in Dynamic Environment.
Solid State Phenomena. Roč. 198, č. 2013 (2013), s. 108-113. ISSN 1012-0394
Institutional research plan: CEZ:AV0Z20760514
Institutional support: RVO:61388998
Keywords : mobile robot * reactive navigation * artificial neural networks
Subject RIV: JD - Computer Applications, Robotics

When mobile robots are used among people, the best accepted motion related behavior is a human-like motion of the robot. Such behavior is difficult to obtain with commonly used finite state machine based planners, but can easily be evoked when human controls the robot. The paper presents the way of transforming such knowledge from human controller to reactive planner in the robot navigation module. Reactive planner is based on machine learning, neural networks in particular. The planner consists of two separate neural networks, one serving as predictor of dynamic obstacles behavior, second one serving as the reactive planner itself, producing desirable actions of the robot both in terms of velocity and direction. Planner was verified on real robot producing human-like behavior when used in real environment.
Permanent Link: http://hdl.handle.net/11104/0229601