Reactive Neural Path Planning with Dynamic Obstacle Avoidance in a Condensed Configuration Space
Lea Steffen,Tobias Weyer,Stefan Ulbrich,Arne Roennau,Rüdiger Dillmann,Lea Steffen,Tobias Weyer,Stefan Ulbrich,Arne Roennau,Rüdiger Dillmann
We present a biologically inspired approach for path planning with dynamic obstacle avoidance. Path plan-ning is performed in a condensed configuration space of a robot generated by self-organizing neural networks (SONN). The robot itself and static as well as dynamic obstacles are mapped from the Cartesian task to the configuration space by precomputed kinematics. The condensed space represents a...
