This video is part of the supplementary material of the publication "LSTP: Long Short-Term Motion Planning for Legged and Legged-Wheeled Systems", accepted to IEEE Transaction on Robotics, 2023.

This article presents a hybrid motion planning and control approach applicable to various ground robot types and morphologies. Our two-step approach uses a sampling-based planner to compute an approximate motion which is then fed to numerical optimization for refinement.

We present tasks of traversing challenging terrain that requires discovering a contact schedule,
navigating non-convex obstacles, and coordinating many degrees of freedom. Our hybrid planner has been applied to three different robots: a quadruped, a wheeled quadruped, and a legged excavator. We validate our hybrid locomotion planner in the real world and simulation, generating behaviors we could not achieve with previous methods.

Authors: Edo Jelavic*, Kaixian Qu*, Farbod Farshidian and Marco Hutter

* - equal contribution

You can find the paper on ETH research collection:
https://www.research-collection.ethz....