Publications by Guillaume Denis Antoine Bellegarda

Related publications (14)

Learning-based Hierarchical Control: Emulating the Central Nervous System for Bio-Inspired Legged Robot Locomotion

Auke Ijspeert, Guillaume Denis Antoine Bellegarda, Milad Shafiee Ashtiani

Animals possess a remarkable ability to navigate challenging terrains, achieved through the interplay of various pathways between the brain, central pattern generators (CPGs) in the spinal cord, and musculoskeletal system. Traditional bioinspired control f ...

Institute of Electrical and Electronics Engineers Inc.2024

Identifying important sensory feedback for learning locomotion skills

Auke Ijspeert, Guillaume Denis Antoine Bellegarda, Milad Shafiee Ashtiani

Robot motor skills can be acquired by deep reinforcement learning as neural networks to reflect state-action mapping. The selection of states has been demonstrated to be crucial for successful robot motor learning. However, because of the complexity of neu ...

NATURE PORTFOLIO2023

Learning Human-Robot Handshaking Preferences for Quadruped Robots

Alessandra Chappuis, Auke Ijspeert, Guillaume Denis Antoine Bellegarda

Quadruped robots are showing impressive abilities to navigate the real world. If they are to become more integrated into society, social trust in interactions with humans will become increasingly important. Additionally, robots will need to be adaptable to ...

IEEE Computer Society2024

Puppeteer and Marionette: Learning Anticipatory Quadrupedal Locomotion Based on Interactions of a Central Pattern Generator and Supraspinal Drive

Auke Ijspeert, Guillaume Denis Antoine Bellegarda, Milad Shafiee Ashtiani

Quadruped animal locomotion emerges from the interactions between the spinal central pattern generator (CPG), sensory feedback, and supraspinal drive signals from the brain. Computational models of CPGs have been widely used for investigating the spinal co ...

IEEE2023

Dynamic Object Catching with Quadruped Robot Front Legs

Auke Ijspeert, Guillaume Denis Antoine Bellegarda

This paper presents a framework for dynamic object catching using a quadruped robot's front legs while it stands on its rear legs. The system integrates computer vision, trajectory prediction, and leg control to enable the quadruped to visually detect, tra ...

Institute of Electrical and Electronics Engineers Inc.2024

Viability leads to the emergence of gait transitions in learning agile quadrupedal locomotion on challenging terrains

Auke Ijspeert, Guillaume Denis Antoine Bellegarda, Milad Shafiee Ashtiani

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 this article, we ...

Nature Portfolio2024

Visual CPG-RL: Learning Central Pattern Generators for Visually-Guided Quadruped Locomotion

Auke Ijspeert, Guillaume Denis Antoine Bellegarda, Milad Shafiee Ashtiani

We present a framework for learning visually-guided quadruped locomotion by integrating exteroceptive sensing and central pattern generators (CPGs), i.e. systems of coupled oscillators, into the deep reinforcement learning (DRL) framework. Through both ext ...

Institute of Electrical and Electronics Engineers Inc.2024

Dynamic Vehicle Drifting With Nonlinear MPC and a Fused Kinematic-Dynamic Bicycle Model

Guillaume Denis Antoine Bellegarda

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 plan d ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2022

Online Optimization of Central Pattern Generators for Quadruped Locomotion

Zewei Zhang, Auke Ijspeert, Guillaume Denis Antoine Bellegarda, Milad Shafiee Ashtiani

Typical legged locomotion controllers are designed or trained offline. This is in contrast to many animals, which are able to locomote at birth, and rapidly improve their locomotion skills with few real-world interactions. Such motor control is possible th ...

Institute of Electrical and Electronics Engineers Inc.2024

ManyQuadrupeds: Learning a Single Locomotion Policy for Diverse Quadruped Robots

Auke Ijspeert, Guillaume Denis Antoine Bellegarda, Milad Shafiee Ashtiani

Learning a locomotion policy for quadruped robots has traditionally been constrained to a specific robot morphology, mass, and size. The learning process must usually be repeated for every new robot, where hyperparameters and reward function weights must b ...

Institute of Electrical and Electronics Engineers Inc.2024

Quadruped-Frog: Rapid Online Optimization of Continuous Quadruped Jumping

Auke Ijspeert, Guillaume Denis Antoine Bellegarda, Milad Shafiee Ashtiani

Legged robots are becoming increasingly agile in exhibiting dynamic behaviors such as running and jumping. Usually, such behaviors are either optimized and engineered offline (i.e. the behavior is designed for before it is needed), either through model-bas ...

Institute of Electrical and Electronics Engineers Inc.2024

Robust quadruped jumping via deep reinforcement learning

Guillaume Denis Antoine Bellegarda

In this paper, we consider a general task of jumping varying distances and heights for a quadrupedal robot in noisy environments, such as off of uneven terrain and with variable robot dynamics parameters. To accurately jump in such conditions, we propose a ...

Elsevier2024

Dynamic Vehicle Drifting With Nonlinear MPC and a Fused Kinematic-Dynamic Bicycle Model (vol 6, pg 1958, 2022)

Guillaume Denis Antoine Bellegarda

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2022

CPG-RL: Learning Central Pattern Generators for Quadruped Locomotion

Auke Ijspeert, Guillaume Denis Antoine Bellegarda

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 learns to ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2022