Motion coordination for a mobile robot in dynamic environments
Generating coordinated motion for a mobile robot operating in natural, continuously changing environments among moving obstacles such as humans is a complex task which requires the solution of various sub problems. In this thesis, we will cover the topics of perception and navigation in dynamic environments, as well as reasoning about the motion of the obstacles and of the robot itself. Perception is mainly considered for a laser range finder, and an according method for obstacle detection and tracking is proposed. Network optimization algorithms are used for data association in the tracking step, resulting in considerable robustness with respect to clutter by small objects. Navigation in general is accomplished using an adaptation of the velocity obstacle approach to the given vehicle kinematics, and cooperative motion coordination between the robot and a human guide is achieved using an appropriate selection rule for collision-free velocities. Next, the robot is enabled to compare its path to the path of a human guide using one of a collection of presented distance measures, which permits the detection of exceptional conditions. Furthermore, a taxonomy for the assessment of situations concerning the robot is presented, and following a summary of existing approaches to more intelligent and comprehensive perception, we propose a method for obstruction detection. Finally, a new approach to reflective navigation behaviors is described where the robot reasons about intelligent moving obstacles in its environment, which allows to adjust the character of the robot motion from regardful and defensive to more self-confident and aggressive behaviors.
Roboter, Bewegungsplanung, dynamische Umgebungen, Robot, Motion Planning, Dynamic Environments
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