An adaptive hierarchical control framework for quadrupedal robots in planetary exploration

TL;DR

This paper introduces an adaptive hierarchical control framework for quadrupedal robots, enabling robust navigation in unknown, challenging terrains typical of planetary exploration, validated through extensive field testing.

Contribution

It presents a modular control system combining model-based control, online adaptation, and footstep planning, tailored for uncertain environments and supporting runtime reconfiguration.

Findings

Successfully navigated over 700 meters in volcanic terrain

Validated on multiple hardware platforms

Supports environment and robot parameter uncertainties

Abstract

Planetary exploration missions require robots capable of navigating extreme and unknown environments. While wheeled rovers have dominated past missions, their mobility is limited to traversable surfaces. Legged robots, especially quadrupeds, can overcome these limitations by handling uneven, obstacle-rich, and deformable terrains. However, deploying such robots in unknown conditions is challenging due to the need for environment-specific control, which is infeasible when terrain and robot parameters are uncertain. This work presents a modular control framework that combines model-based dynamic control with online model adaptation and adaptive footstep planning to address uncertainties in both robot and terrain properties. The framework includes state estimation for quadrupeds with and without contact sensing, supports runtime reconfiguration, and is integrated into ROS 2 with open-source availability. Its performance was validated on two quadruped platforms, multiple hardware architectures, and in a volcano field test, where the robot walked over 700 m.