Zobrazeno 1 - 10
of 10
pro vyhledávání: '"Guillaume Bellegarda"'
Publikováno v:
Nature Communications, Vol 15, Iss 1, Pp 1-16 (2024)
Abstract Quadruped animals are capable of seamless transitions between different gaits. While energy efficiency appears to be one of the reasons for changing gaits, other determinant factors likely play a role too, including terrain properties. In th
Externí odkaz:
https://doaj.org/article/681d691c189d4fbfa72337c06b0d43da
Autor:
Guillaume Bellegarda, Quan Nguyen
Publikováno v:
IEEE Control Systems Letters. 6:1958-1963
In this letter we present a versatile trajectory optimization framework that leverages a fused kinematic-dynamic bicycle model for highly dynamic vehicle drifting maneuvers. Our framework can be used online to generate drifting maneuvers, offline to
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::cca2cd8c6cfa1c3736620e0b2cb39e13
https://doi.org/10.1109/lcsys.2021.3136142
https://doi.org/10.1109/lcsys.2021.3136142
Autor:
Guillaume Bellegarda, Auke Ijspeert
In this letter, we present a method for integrating central pattern generators (CPGs), i.e. systems of coupled oscillators, into the deep reinforcement learning (DRL) framework to produce robust and omnidirectional quadruped locomotion. The agent lea
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::bbac14217fe3a1dfe40e576e205a71be
http://arxiv.org/abs/2211.00458
http://arxiv.org/abs/2211.00458
Deep reinforcement learning has emerged as a popular and powerful way to develop locomotion controllers for quadruped robots. Common approaches have largely focused on learning actions directly in joint space, or learning to modify and offset foot po
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b70507852775e6bced2a0fe4649a4583
Autor:
Katie Byl, Guillaume Bellegarda
Publikováno v:
IROS
Recent breakthroughs both in reinforcement learning and trajectory optimization have made significant advances towards real world robotic system deployment. Reinforcement learning (RL) can be applied to many problems without needing any modeling or i
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::651891abfaec2f9f242f8d02a2b48773
https://doi.org/10.1109/iros45743.2020.9341021
https://doi.org/10.1109/iros45743.2020.9341021
Autor:
Katie Byl, Guillaume Bellegarda
Publikováno v:
ICRA
Car models have been extensively studied at varying levels of abstraction, and planning and executing motions under ideal conditions is well researched and understood. For more aggressive maneuvers, for example when drifting or skidding, empirical an
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f3e8ad0440323e81be1de54194609b5c
https://doi.org/10.1109/icra40945.2020.9197541
https://doi.org/10.1109/icra40945.2020.9197541
Erratum to 'Dynamic Vehicle Drifting With Nonlinear MPC and a Fused Kinematic-Dynamic Bicycle Model'
Autor:
Guillaume Bellegarda, Quan Nguyen
Publikováno v:
IEEE Control Systems Letters. 6:2779-2779
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0c416413a752758fc7c0fa5dc6e6297e
https://doi.org/10.1109/lcsys.2022.3175230
https://doi.org/10.1109/lcsys.2022.3175230
Autor:
Katie Byl, Guillaume Bellegarda
Publikováno v:
IROS
Recent breakthroughs in the reinforcement learning (RL) community have made significant advances towards learning and deploying policies on real world robotic systems. However, even with the current state-of-the-art algorithms and computational resou
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a5d73294e61f3ddde584f9e901c0bf0f
http://arxiv.org/abs/1903.02219
http://arxiv.org/abs/1903.02219
Publikováno v:
ICRA
This paper explores locally-optimal, efficient locomotion of a two-link planar robot balancing on a single, unactuated wheel. Because this model is essentially an acrobot mounted on a passive wheel, we name this model the acrollbot. By actuating an i
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3b2eb2d25783052864171a2572713075
https://doi.org/10.1109/icra.2018.8461221
https://doi.org/10.1109/icra.2018.8461221
Publikováno v:
ICRA
This paper describes skating locomotion for a quadruped robot with dexterous limbs. The emphasis is on design of omnidirectional motion primitives and quantification of resulting speed and accuracy when traversing different types of smooth but potent
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3e55fc8dfc4a619938807cddb97531d0
https://doi.org/10.1109/icra.2018.8460600
https://doi.org/10.1109/icra.2018.8460600