REFERENCE GUIDED LEGGED WHEEL LOCOMOTION ON STAIRS WITH PROXIMAL POLICY OPTIMIZATION

Pareto frontier-guided differentiated skill reinforcement learning for quadrupedal wheeled-legged robots

Wheeled-legged robots possess both extreme maneuverability and strong terrain adaptability, but there is an inherent physical contradiction between high-speed locomotion and disturbance-rejection robustness. Traditional end-to-end reinforcement learning (RL) methods typically rely on black-box trial and error, lacking...

Robust Quadruped Jumping on Sloped Terrains using Reinforcement-Learning-Augmented Model Predictive Control

Legged robots can navigate in much more complex environments than wheeled counterparts due to the added mobility of the limbs. Although much research has been done on walking and running control, real-time dynamic jumping of these robots on 3D sloped terrains remains underexplored. In this work, we aim to control a qua...

ReCo: Response-Consistent Locomotion with Policy-Aware MPC for Legged Manipulation

Continuous legged manipulation requires accurate end-effector tracking while the base keeps walking. Combining reinforcement learning (RL) with model predictive control (MPC) suits this task: the learned policy provides robust locomotion, while MPC coordinates the base and arm to compensate for tracking errors. However...

LLA-MPPI: Rapidly Adaptive Whole-body Control of Legged Robots with GPU-Accelerated Parallel Simulations

Real-time whole-body controllers for legged robots typically plan through a fixed nominal model and degrade when the deployed dynamics change. Adaptive methods typically require a model structure that contact dynamics do not provide, or they need offline training for each anticipated condition. We present Look-back and...

Development of Bipedal Robot STOB-v3 and Reinforcement Learning–Based Locomotion Control Considering a Single Rigid Body Model

Research on Jumping Gait Motion Control of Quadrupedal Robots Based on Reinforcement Learning

High-dynamic quadruped jumping over steps and gap-like support interruptions remains difficult when external terrain perception is unavailable or unreliable. This paper studies a proprioception-only reinforcement-learning policy for bound jumping. The actor is initialized by a flat-ground bound strategy to obtain a sta...