Anytime Hybrid Driving-Stepping Locomotion Planning

TL;DR

This paper presents a hybrid locomotion planning method for quadruped robots that combines driving and stepping, enabling efficient navigation over diverse terrains by planning abstract maneuvers and detailed motions while ensuring stability.

Contribution

It introduces a novel hybrid planning algorithm that integrates driving and stepping, considering robot footprint and stability, with a two-stage planning process for efficiency.

Findings

Planner generates feasible paths in challenging terrains.

Hybrid approach improves navigation flexibility and efficiency.

Planning time remains practical for real-world applications.

Abstract

Hybrid driving-stepping locomotion is an effective approach for navigating in a variety of environments. Long, sufficiently even distances can be quickly covered by driving while obstacles can be overcome by stepping. Our quadruped robot Momaro, with steerable pairs of wheels located at the end of each of its compliant legs, allows such locomotion. Planning respective paths attracted only little attention so far. We propose a navigation planning method which generates hybrid locomotion paths. The planner chooses driving mode whenever possible and takes into account the detailed robot footprint. If steps are required, the planner includes those. To accelerate planning, steps are planned first as abstract manoeuvres and are expanded afterwards into detailed motion sequences. Our method ensures at all times that the robot stays stable. Experiments show that the proposed planner is capable of providing paths in feasible time, even for challenging terrain.