5 papers
Knowledge Reutilization in Meta-Reinforcement Learning
Yuan Meng, Bo Wang, Juan de los Rios Ruiz +4
Meta-reinforcement learning enables fast adaptation by extracting shared structure from related tasks, but existing end-to-end methods often couple task inference with embodiment-s…
EAGG: Embodiment-Aligned Grasp Generation via Geometry-Aware Graph Conditioning
Wanhao Niu, Qiyan Ke, Yuan Sun +5
Cross-end-effector grasp generation seeks a unified model that generalizes across objects and across embodiments ranging from parallel grippers to dexterous end effectors. Existing…
DualGazeNet: A Biologically Inspired Dual-Gaze Query Network for Salient Object Detection
Yu Zhang, Haoan Ping, Yuchen Li +3
Recent salient object detection (SOD) methods aim to improve performance in four key directions: semantic enhancement, boundary refinement, auxiliary task supervision, and multi-mo…
Inference-stage Adaptation-projection Strategy Adapts Diffusion Policy to Cross-manipulators Scenarios
Xiangtong Yao, Yirui Zhou, Yuan Meng +7
Diffusion policies are powerful visuomotor models for robotic manipulation, yet they often fail to generalize to manipulators or end-effectors unseen during training and struggle t…
Pick-and-place Manipulation Across Grippers Without Retraining: A Learning-optimization Diffusion Policy Approach
Xiangtong Yao, Yirui Zhou, Yuan Meng +7
Current robotic pick-and-place policies typically require consistent gripper configurations across training and inference. This constraint imposes high retraining or fine-tuning co…