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Bibliographic Details
Main Authors: Bartlett, Tara, Manchester, Ian R.
Format: Preprint
Published: 2024
Subjects:
Online Access:https://arxiv.org/abs/2409.09939
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author Bartlett, Tara
Manchester, Ian R.
author_facet Bartlett, Tara
Manchester, Ian R.
contents This paper presents an algorithm that finds a centroidal motion and footstep plan for a Spring-Loaded Inverted Pendulum (SLIP)-like bipedal robot model substantially faster than real-time. This is achieved with a novel representation of the dynamic footstep planning problem, where each point in the environment is considered a potential foothold that can apply a force to the center of mass to keep it on a desired trajectory. For a biped, up to two such footholds per time step must be selected, and we approximate this cardinality constraint with an iteratively reweighted $l_1$-norm minimization. Along with a linearizing approximation of an angular momentum constraint, this results in a quadratic program can be solved for a contact schedule and center of mass trajectory with automatic gait discovery. A 2 s planning horizon with 13 time steps and 20 surfaces available at each time is solved in 142 ms, roughly ten times faster than comparable existing methods in the literature. We demonstrate the versatility of this program in a variety of simulated environments.
format Preprint
id arxiv_https___arxiv_org_abs_2409_09939
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Real-time Coupled Centroidal Motion and Footstep Planning for Biped Robots
Bartlett, Tara
Manchester, Ian R.
Robotics
This paper presents an algorithm that finds a centroidal motion and footstep plan for a Spring-Loaded Inverted Pendulum (SLIP)-like bipedal robot model substantially faster than real-time. This is achieved with a novel representation of the dynamic footstep planning problem, where each point in the environment is considered a potential foothold that can apply a force to the center of mass to keep it on a desired trajectory. For a biped, up to two such footholds per time step must be selected, and we approximate this cardinality constraint with an iteratively reweighted $l_1$-norm minimization. Along with a linearizing approximation of an angular momentum constraint, this results in a quadratic program can be solved for a contact schedule and center of mass trajectory with automatic gait discovery. A 2 s planning horizon with 13 time steps and 20 surfaces available at each time is solved in 142 ms, roughly ten times faster than comparable existing methods in the literature. We demonstrate the versatility of this program in a variety of simulated environments.
title Real-time Coupled Centroidal Motion and Footstep Planning for Biped Robots
topic Robotics
url https://arxiv.org/abs/2409.09939