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cs.RO2025
ClutterDexGrasp: A Sim-to-Real System for General Dexterous Grasping in Cluttered Scenes
Zeyuan Chen, Qiyang Yan, Yuanpei Chen +6
Dexterous grasping in cluttered scenes presents significant challenges due to diverse object geometries, occlusions, and potential collisions. Existing methods primarily focus on s…
cs.RO2025
Adaptive Visuo-Tactile Fusion with Predictive Force Attention for Dexterous Manipulation
Jinzhou Li, Tianhao Wu, Jiyao Zhang +6
Effectively utilizing multi-sensory data is important for robots to generalize across diverse tasks. However, the heterogeneous nature of these modalities makes fusion challenging.…
cs.AI2025
Boosting Universal LLM Reward Design through Heuristic Reward Observation Space Evolution
Zen Kit Heng, Zimeng Zhao, Tianhao Wu +4
Large Language Models (LLMs) are emerging as promising tools for automated reinforcement learning (RL) reward design, owing to their robust capabilities in commonsense reasoning an…