Reactive Neural Path Planning with Dynamic Obstacle Avoidance in a Condensed Configuration Space
Channel: FZIchannel
Date: 2022-07-04

A biologically inspired approach for path planning with dynamic obstacle avoidance is presented. The highly reactive collision-free path planner was implemented on a 6 DOF robot and is capable to operate in real-time. Path planning is performed in a condensed configuration space of the robot,
generated by self-organizing neural networks (SONN). The condensed space represents a cognitive map of the environment, which is inspired by place cells and the concept of cognitive maps in mammalian brains. The system is able to operate in dynamically changing environments and re-plan its trajectories within impressing 0.02 seconds, proofing the concept's real-time capability.As the evaluation a comparative study regarding sample-based planners was carried out. 

A paper of this approach is accepted to IROS2022 (https://iros2022.org/).
https://arxiv.org/pdf/2207.03959.pdf

This research project has been supported by the European Union’s Horizon 2020 Framework Programme for Research and Innovation under the Specific Grant Agreement No. 945539 (Human Brain Project SGA3).