Quick Overview: In this work we present a general, two-stage reinforcement learning approach for going from a single demonstration Abstract: Linear Model Predictive Control (MPC) has been successfully used for generating feasible walking motions for ... Isabelle Maroger, Olivier Stasse, Bruno Watier (IROS 2020) Abstract : In order to fluidly perform complex tasks in collaboration ...

Robust Humanoid Locomotion Using Trajectory - Detailed Overview & Context

In this work we present a general, two-stage reinforcement learning approach for going from a single demonstration Abstract: Linear Model Predictive Control (MPC) has been successfully used for generating feasible walking motions for ... Isabelle Maroger, Olivier Stasse, Bruno Watier (IROS 2020) Abstract : In order to fluidly perform complex tasks in collaboration ... Stepping strategy, including step time and step location modulation, and hip strategy, i.e., upper-bod movement, play crucial roles ... This work presents a comprehensive study on Conference: IROS 2022 Paper link: arXiv preprint: ...

This video shows dynamic walking simulations supporting our newly accepted paper: Y. Zhao, B. Fernandez and L. Sentis. In this video, we propose a modular framework to generate Final Project for MIT 6.832 - Underactuated Robotics. Dynamic Complementarity Conditions and Whole-Body The video highlights that models trained by ES (left frame) are more

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Robust Humanoid Locomotion Using Trajectory Optimization and Sample-Efficient Learning
Robust Humanoid Locomotion Using Trajectory Optimization and Sample-Efficient Learning
Model-free RL for Robust Locomotion Using Trajectory Optimization for Exploration
Stochastic and Robust MPC for Bipedal Locomotion: A Comparative Study on Robustness and Performance
Robust Humanoid Locomotion via Sequential Stepping and Angular Momentum Optimization
Masked Whole-Body Controller for Humanoid Robots
Control Guided RL for Humanoid Locomotion -- Zachary Olkin
Walking Human Trajectory Models and Their Application to Humanoid Robot Locomotion
Real-World Humanoid Locomotion with Reinforcement Learning
Robust Humanoid Locomotion via Sequential Stepping and Angular Momentum Optimization
Reinforcement Learning for Versatile, Dynamic, and Robust Bipedal Locomotion Control
Robot Trajectory Adaptation to Optimise the Trade-off between Human Cognitive Ergonomics
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