Polytopic Planar Region Characterization of Rough Terrains for Legged Locomotion

TL;DR

This paper presents a fast, accurate method for representing planar regions in rough terrains using polytopes from depth camera data, aiding legged robot navigation.

Contribution

It introduces a two-stage approach for extracting and approximating planar terrain regions with low-dimensional polytopes, enabling real-time terrain mapping for legged locomotion.

Findings

Achieves terrain characterization with acceptable accuracy.

Runs at over 100Hz, enabling real-time applications.

Demonstrates effectiveness with RGB-D camera data.

Abstract

This paper studies the problem of constructing polytopic representations of 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 first 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 low-dimensional 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 perception scheme is less than 10ms (i.e., > 100Hz) throughout the tests, which strongly illustrates the advantages of our approach developed in this paper.