| Title: |
Constrained Articulated Body Algorithms for Closed-Loop Mechanisms |
| Authors: |
Sathya, Ajay, Suresha; Carpentier, Justin |
| Contributors: |
Models of visual object recognition and scene understanding (WILLOW); Département d'informatique - ENS-PSL (DI-ENS); École normale supérieure - Paris (ENS-PSL); Université Paris Sciences et Lettres (PSL)-Université Paris Sciences et Lettres (PSL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure - Paris (ENS-PSL); Université Paris Sciences et Lettres (PSL)-Université Paris Sciences et Lettres (PSL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Centre Inria de Paris; Institut National de Recherche en Informatique et en Automatique (Inria); Université Paris Sciences et Lettres (PSL)-Université Paris Sciences et Lettres (PSL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS); This work was supported by the French government under the management of Agence Nationale de la Recherche through the project INEXACT (ANR-22-CE33-0007-01) and as part of the ”Investissements d’avenir” program, reference ANR-19-P3IA-0001 (PRAIRIE 3IA Institute), by the European Union through the AGIMUS project (GA no.101070165) and the Louis Vuitton ENS Chair on Artificial Intelligence.; ANR-19-P3IA-0001,PRAIRIE,PaRis Artificial Intelligence Research InstitutE(2019); ANR-22-CE33-0007,INEXACT,Optimisation inexacte pour le contrôle de robots(2022); European Project: 101070165,HORIZON-CL4-2021-DIGITAL-EMERGING-01,HORIZON-CL4-2021-DIGITAL-EMERGING-01,AGIMUS(2022); European Project: 101211945,HORIZON-MSCA-2024-PF-01,HORIZON-MSCA-2024-PF-01,ExTRAORDiNary(2025) |
| Source: |
https://hal.science/hal-04895583 ; 2025. |
| Publisher Information: |
CCSD |
| Publication Year: |
2025 |
| Subject Terms: |
[INFO.INFO-RB]Computer Science [cs]/Robotics [cs.RO] |
| Description: |
Efficient rigid-body dynamics algorithms are instrumental in enabling high-frequency dynamics evaluation for resource-intensive applications (e.g., model predictive control, large-scale simulation, reinforcement learning), potentially on resource-constrained hardware. Existing recursive algorithms with low computational complexity are mostly restricted to kinematic trees with external contact constraints or are sensitive to singular cases (e.g., linearly dependent constraints and kinematic singularities), severely impacting their practical usage in existing simulators. This article introduces two original lowcomplexity recursive algorithms, loop-constrained articulated body algorithm (LCABA) and proxBBO, based on proximal dynamics formulation for forward simulation of mechanisms with loops. These algorithms are derived from first principles using non-serial dynamic programming, depict linear complexity in practical scenarios, and are numerically robust to singular cases. They extend the existing constrained articulated body algorithm (constrainedABA) to handle internal loops and the pioneering BBO algorithm from the 1980s to singular cases. Both algorithms have been implemented by leveraging the open-source Pinocchio library, benchmarked in detail, and depict state-ofthe-art performance for various robot topologies, including over 6x speed-ups compared to existing non-recursive algorithms for high degree-of-freedom systems with internal loops such as recent humanoid robots. |
| Document Type: |
report |
| Language: |
English |
| Relation: |
info:eu-repo/grantAgreement//101070165/EU/Next generation of AI-powered robotics for agile production/AGIMUS; info:eu-repo/grantAgreement//101211945/EU/Accelerating Differentiable Robot Dynamics Simulation for Advanced Control/ExTRAORDiNary |
| Availability: |
https://hal.science/hal-04895583; https://hal.science/hal-04895583v2/document; https://hal.science/hal-04895583v2/file/main.pdf |
| Rights: |
https://about.hal.science/hal-authorisation-v1/ ; info:eu-repo/semantics/OpenAccess |
| Accession Number: |
edsbas.E49DA747 |
| Database: |
BASE |