Reactive Robot Navigation Utilizing Nonlinear Control
Author(s) -
Ting Lei,
C.J.B. Macnab,
Sebastian Magierowski
Publication year - 2014
Publication title -
international journal of advanced robotic systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.394
H-Index - 46
eISSN - 1729-8814
pISSN - 1729-8806
DOI - 10.5772/58705
Subject(s) - computer science , robot , heuristic , collision avoidance , mobile robot , nonlinear system , position (finance) , fuzzy logic , control theory (sociology) , encoding (memory) , path (computing) , motion planning , stability (learning theory) , collision , artificial intelligence , real time computing , computer vision , control (management) , physics , computer security , finance , quantum mechanics , machine learning , economics , programming language
In this paper, we propose a computationally efficient heuristic solution to choosing a path around obstacles in the face of limited sensor information. Specifically, we propose a navigation algorithm for a mobile robot that reaches a measured target position while avoiding obstacles, making decisions in real-time (without stopping) and relying strictly on information obtained from limited and noisy robot-mounted sensors to determine the location and severity of obstacles. The solution utilizes fuzzy processing to encode the environment – the fuzzy encoding is used both in deciding on an intermediate target direction and in a collision-avoidance strategy. A closed-loop nonlinear feedback control provides a smooth motion with stability guarantees. Simulation results in a corridor environment demonstrate expected collision-free trajectories
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