12 papers
DORA: Object Affordance-Guided Reinforcement Learning for Dexterous Robotic Manipulation
Lei Zhang, Soumya Mondal, Zhenshan Bing +5
Dexterous robotic manipulation remains a longstanding challenge in robotics due to the high dimensionality of control spaces and the semantic complexity of object interaction. In t…
Pretrained Bayesian Non-parametric Knowledge Prior in Robotic Long-Horizon Reinforcement Learning
Yuan Meng, Xiangtong Yao, Kejia Chen +4
Reinforcement learning (RL) methods typically learn new tasks from scratch, often disregarding prior knowledge that could accelerate the learning process. While some methods incorp…
Gassidy: Gaussian Splatting SLAM in Dynamic Environments
Long Wen, Shixin Li, Yu Zhang +5
3D Gaussian Splatting (3DGS) allows flexible adjustments to scene representation, enabling continuous optimization of scene quality during dense visual simultaneous localization an…
Locomotion Generation for a Rat Robot based on Environmental Changes via Reinforcement Learning
Xinhui Shan, Yuhong Huang, Zhenshan Bing +4
This research focuses on developing reinforcement learning approaches for the locomotion generation of small-size quadruped robots. The rat robot NeRmo is employed as the experimen…
Real-Time Adaptive Safety-Critical Control with Gaussian Processes in High-Order Uncertain Models
Yu Zhang, Long Wen, Xiangtong Yao +4
This paper presents an adaptive online learning framework for systems with uncertain parameters to ensure safety-critical control in non-stationary environments. Our approach consi…
Optimizing Dynamic Balance in a Rat Robot via the Lateral Flexion of a Soft Actuated Spine
Yuhong Huang, Zhenshan Bing, Zitao Zhang +3
Balancing oneself using the spine is a physiological alignment of the body posture in the most efficient manner by the muscular forces for mammals. For this reason, we can see many…