Learning to Guide Online Multi-Contact Receding Horizon Planning

Jiayi Wang, Teguh Santoso Lembono, Sanghyun Kim, Sylvain Calinon, Sethu Vijayakumar, Steve Tonneau

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In Receding Horizon Planning (RHP), it is critical that the motion being executed facilitates the completion of the task, e.g. building momentum to overcome large obstacles. This requires a value function to inform the desirability of robot states. However, given the complex dynamics, value functions are often approximated by expensive computation of trajectories in an extended planning horizon. In this work, to achieve online multi-contact Receding Horizon Planning (RHP), we propose to learn an oracle that can predict local objectives (intermediate goals) for a given task based on the current robot state and the environment. Then, we use these local objectives to construct local value functions to guide a short-horizon RHP. To obtain the oracle, we take a supervised learning approach, and we present an incremental training scheme that can improve the prediction accuracy by adding demonstrations on how to recover from failures. We compare our approach against the baseline (long-horizon RHP) for planning centroidal trajectories of humanoid walking on moderate slopes as well as large slopes where static stability cannot be achieved. We validate these trajectories by tracking them via a whole-body inverse dynamics controller in simulation. We show that our approach can achieve online RHP for 95%-98.6% cycles, outperforming the baseline (8%-51.2%).
Original languageEnglish
Title of host publicationProceedings of the 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
Number of pages8
Publication statusAccepted/In press - 30 Jun 2022
EventThe 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems - Kyoto, Japan
Duration: 23 Oct 202227 Oct 2022
https://iros2022.org/

Conference

ConferenceThe 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems
Abbreviated titleIROS 2022
Country/TerritoryJapan
CityKyoto
Period23/10/2227/10/22
Internet address

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