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Crocoddyl: An Efficient and Versatile Framework for Multi-Contact Optimal Control

Authors: Carlos Mastalli, Rohan Budhiraja, Wolfgang Merkt, Guilhem Saurel, Bilal Hammoud, Maximilien Naveau, Justin Carpentier, Ludovic Righetti, Sethu Vijayakumar, Nicolas Mansard

Published: 2019 (Conference Paper)

Source: IEEE International Conference on Robotics and Automation

Algorithm: Crocoddyl

arXiv: 1909.04947

DOI: 10.1109/ICRA40945.2020.9196673

Summary

Introduces Crocoddyl, an open-source multi-contact trajectory optimization library built on Feasibility-driven DDP (FDDP). FDDP accepts infeasible initial trajectories and keeps shooting gaps open during early iterations, achieving faster convergence and higher reliability than standard DDP for legged robot tasks.

Abstract

We introduce Crocoddyl (Contact RObot COntrol by Differential DYnamic Library), an open-source framework tailored for efficient multi-contact optimal control. Crocoddyl efficiently computes the state trajectory and the control policy for a given predefined sequence of contacts. Its efficiency is due to the use of sparse analytical derivatives, exploitation of the problem structure, and data sharing. It employs differential geometry to properly describe the state of any geometrical system, e.g. floating-base systems. Additionally, we propose a novel optimal control algorithm called Feasibility-driven Differential Dynamic Programming (FDDP). Our method does not add extra decision variables which often increases the computation time per iteration due to factorization. FDDP shows a greater globalization strategy compared to classical Differential Dynamic Programming (DDP) algorithms. Concretely, we propose two modifications to the classical DDP algorithm. First, the backward pass accepts infeasible state-control trajectories. Second, the rollout keeps the gaps open during the early "exploratory" iterations (as expected in multiple-shooting methods with only equality constraints). We showcase the performance of our framework using different tasks. With our method, we can compute highly-dynamic maneuvers (e.g. jumping, front-flip) within few milliseconds.

Primary

Paper arxiv.org

Standard

arXiv Abstract 1909.04947 arXiv PDF 1909.04947 arXiv HTML 1909.04947 DOI 10.1109/ICRA40945.2020.9196673

Alternate

ieeexplore.ieee.org ieeexplore.ieee.org GitHub: loco-3d/crocoddyl github.com gepettoweb.laas.fr gepettoweb.laas.fr

Tags

  • Trajectory optimization

  • Differential dynamic programming

  • Multi-contact

  • Legged robots

  • Optimal control

  • FDDP

  • Open source