A Safe and Efficient Timed-Elastic-Band Planner for Unstructured Environments

In unstructured environments with complex obstacles and obscure road boundaries, the local planner faces more severe challenges in terms of safety and real-time performance. In order to fulfill these emerging requirements, we propose a novel Timed-Elastic-Band approach for unstructured environments, abbreviated as TEB-U. This approach incorporates a free space extraction optimization module for 2D occupancy grid maps, which efficiently transforms irregular free space boundaries into polygons and restrains robots within the boundaries. Moreover, a dynamic global point adjustment module is designed to adaptively correct the trajectory points obtained from the global planner, thereby enabling robots to travel along the centerline of free space and providing a better initial trajectory for subsequent modules. To reduce the computational cost, we replace the obstacle constraint of TEB with the boundary constraint in hyper-graph optimization. We evaluate our planner in three distinct scenarios, and the results show that TEB-U improves the average success rate by 21% and reduces the planning time by 23% compared to TEB in unstructured road, which demonstrates its safety and efficiency.