The whole-body control of mobile manipulators for the 6-DOF trajectory following task is the basis of many continuous tasks. However, traditional control strategies rely on accurate models and expert ...

Model Predictive Control (MPC) and Reinforcement Learning (RL) are two prominent strategies for controlling legged robots. RL learns control policies through system interaction, adapting to various ...

Flow-based Polciy for Online Reinforcement Learning We are delighted to introduce FlowRL. It is a new approach for online reinforcement learning that integrates flow-based policy representation with ...

This repository contains the code for a new Safe Multi-Agent Reinforcement Learning (MARL) algorithm. It integrates deep policy gradients with a Lagrangian multiplier framework to enable autonomous ...