Agile Maneuvers in Legged Robots: a Predictive Control Approach
- URL: http://arxiv.org/abs/2203.07554v1
- Date: Mon, 14 Mar 2022 23:32:17 GMT
- Title: Agile Maneuvers in Legged Robots: a Predictive Control Approach
- Authors: Carlos Mastalli, Wolfgang Merkt, Guiyang Xin, Jaehyun Shim, Michael
Mistry, Ioannis Havoutis, Sethu Vijayakumar
- Abstract summary: We present a contact-phase predictive and state-feedback controllers that enables legged robots to plan and perform agile locomotion skills.
Our work is the first to show that predictive control can handle actuation limits, generate agile locomotion maneuvers and execute locally optimal feedback policies on hardware without the use of a separate whole-body controller.
- Score: 20.55884151818753
- License: http://creativecommons.org/licenses/by-nc-nd/4.0/
- Abstract: Achieving agile maneuvers through multiple contact phases has been a
longstanding challenge in legged robotics. It requires to derive motion plans
and local control feedback policies in real-time to handle the nonholonomy of
the kinetic momenta. While a few recent predictive control approaches based on
centroidal momentum have been able to generate dynamic motions, they assume
unlimited actuation capabilities. This assumption is quite restrictive and does
not hold for agile maneuvers on most robots. In this work, we present a
contact-phase predictive and state-feedback controllers that enables legged
robots to plan and perform agile locomotion skills. Our predictive controller
models the contact phases using a hybrid paradigm that considers the robot's
actuation limits and full dynamics. We demonstrate the benefits of our approach
on agile maneuvers on ANYmal robots in realistic scenarios. To the best of our
knowledge, our work is the first to show that predictive control can handle
actuation limits, generate agile locomotion maneuvers and execute locally
optimal feedback policies on hardware without the use of a separate whole-body
controller.
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