Polytopic Planar Region Characterization of Rough Terrains for Legged Locomotion
Zhi Xu, Hongbo Zhu, Hua Chen, Wei Dong Zhang · 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) · 2022
This paper studies the problem of constructing polytopic representations for planar regions from depth camera readings. This problem is of great importance for terrain mapping in complicated environment and has great potentials in legged locomotion applications. To address the polytopic planar region characterization problem, we propose a two-stage solution scheme. At the first stage, the planar regions embedded within a sequence of depth images are extracted individually and then merged to establish a terrain map containing only planar regions in a selected frame. To simplify the representations of the planar regions that are applicable to foothold planning for legged robots, we further approximate the extracted planar regions via convex polytopes at the second stage. With the polytopic representation, the proposed approach achieves a great balance between accuracy and simplicity. Experimental validations with RGB-D cameras are conducted to demonstrate the performance of the proposed scheme. The proposed scheme successfully characterizes the planar regions via polytopes with acceptable accuracy. More importantly, the run time of the overall scheme is less than 10ms (i.e., > 100Hz) throughout the tests, which strongly illustrates the advantages of our approach developed in this paper.