Self-Reflective Terrain-Aware Robot Adaptation for Consistent Off-Road Ground Navigation

TL;DR

This paper introduces a self-reflective, terrain-aware adaptation method that enables ground robots to navigate consistently over unstructured off-road terrains by self-assessing and adjusting to terrain and robot changes.

Contribution

The paper presents a novel self-reflective adaptation approach that improves off-road navigation consistency by enabling robots to self-assess and adapt to terrain and robot variations.

Findings

Enhanced navigation consistency in unstructured terrains

Outperforms baseline and previous methods in experiments

Effective self-reflection improves robot maneuverability

Abstract

Ground robots require the crucial capability of traversing unstructured and unprepared terrains and avoiding obstacles to complete tasks in real-world robotics applications such as disaster response. When a robot operates in off-road field environments such as forests, the robot's actual behaviors often do not match its expected or planned behaviors, due to changes in the characteristics of terrains and the robot itself. Therefore, the capability of robot adaptation for consistent behavior generation is essential for maneuverability on unstructured off-road terrains. In order to address the challenge, we propose a novel method of self-reflective terrain-aware adaptation for ground robots to generate consistent controls to navigate over unstructured off-road terrains, which enables robots to more accurately execute the expected behaviors through robot self-reflection while adapting to varying unstructured terrains. To evaluate our method's performance, we conduct extensive experiments using real ground robots with various functionality changes over diverse unstructured off-road terrains. The comprehensive experimental results have shown that our self-reflective terrain-aware adaptation method enables ground robots to generate consistent navigational behaviors and outperforms the compared previous and baseline techniques.