Multi-Contact Inertial Parameters Estimation and Localization in Legged Robots

Fuente: arXiv
Gespeichert in:
Bibliographische Detailangaben
Hauptverfasser: Martinez, Sergi, Griffin, Robert J., Mastalli, Carlos
Format: Preprint
Veröffentlicht: 2024
Schlagworte:
Online-Zugang:
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
_version_ 1866917930016440320
author Martinez, Sergi
Griffin, Robert J.
Mastalli, Carlos
author_facet Martinez, Sergi
Griffin, Robert J.
Mastalli, Carlos
contents Optimal estimation is a promising tool for estimation of payloads' inertial parameters and localization of robots in the presence of multiple contacts. To harness its advantages in robotics, it is crucial to solve these large and challenging optimization problems efficiently. To tackle this, we (i) develop a multiple shooting solver that exploits both temporal and parametric structures through a parametrized Riccati recursion. Additionally, we (ii) propose an inertial manifold that ensures the full physical consistency of inertial parameters and enhances convergence. To handle its manifold singularities, we (iii) introduce a nullspace approach in our optimal estimation solver. Finally, we (iv) develop the analytical derivatives of contact dynamics for both inertial parametrizations. Our framework can successfully solve estimation problems for complex maneuvers such as brachiation in humanoids, achieving higher accuracy than conventional least squares approaches. We demonstrate its numerical capabilities across various robotics tasks and its benefits in experimental trials with the Go1 robot.
format Preprint
id arxiv_https___arxiv_org_abs_2403_17161
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Multi-Contact Inertial Parameters Estimation and Localization in Legged Robots
Martinez, Sergi
Griffin, Robert J.
Mastalli, Carlos
Robotics
Optimal estimation is a promising tool for estimation of payloads' inertial parameters and localization of robots in the presence of multiple contacts. To harness its advantages in robotics, it is crucial to solve these large and challenging optimization problems efficiently. To tackle this, we (i) develop a multiple shooting solver that exploits both temporal and parametric structures through a parametrized Riccati recursion. Additionally, we (ii) propose an inertial manifold that ensures the full physical consistency of inertial parameters and enhances convergence. To handle its manifold singularities, we (iii) introduce a nullspace approach in our optimal estimation solver. Finally, we (iv) develop the analytical derivatives of contact dynamics for both inertial parametrizations. Our framework can successfully solve estimation problems for complex maneuvers such as brachiation in humanoids, achieving higher accuracy than conventional least squares approaches. We demonstrate its numerical capabilities across various robotics tasks and its benefits in experimental trials with the Go1 robot.
title Multi-Contact Inertial Parameters Estimation and Localization in Legged Robots
topic Robotics
url https://arxiv.org/abs/2403.17161