8 papers
Continual Quadruped Robots Coordination via Semantic Skill Discovery
Daoqing Wang, Yuchen Xiao, Weixuan Huang +5
Multi-quadruped coordination has attracted increasing attention due to its enhanced payload capacity, broader contact coverage, and improved adaptability to challenging tasks. Exis…
Autonomous Aerial Manipulation via Contextual Contrastive Meta Reinforcement Learning
Lixuan Jin, Bingxuan Lan, Xinyi Bao +9
Unmanned aerial vehicles (UAVs) are increasingly being deployed in logistics, service robotics, and other real-world applications, creating a growing demand for autonomous payload…
Cooperative Long Rope Skipping via Multi-Agent Reinforcement Learning
Zihao Wang, Shijie Peng, Kerui Wu +6
Humans exhibit remarkable motor agility, enabling a wide range of dynamic skills such as running and jumping, which highlights the great potential of humanoid robots for athletic l…
Anticipation-VLA: Solving Long-Horizon Embodied Tasks via Anticipation-based Subgoal Generation
Zhilong Zhang, Wenyu Luo, Haonan Wang +9
Vision-Language-Action (VLA) models have emerged as a powerful paradigm for embodied intelligence, enabling robots to perform tasks based on natural language instructions and curre…
Model-Based Proactive Cost Generation for Learning Safe Policies Offline with Limited Violation Data
Ruiqi Xue, Lei Yuan, Kainuo Cheng +2
Learning constraint-satisfying policies from offline data without risky online interaction is crucial for safety-critical decision making. Conventional methods typically learn cost…
Multi-agent In-context Coordination via Decentralized Memory Retrieval
Tao Jiang, Zichuan Lin, Lihe Li +6
Large transformer models, trained on diverse datasets, have demonstrated impressive few-shot performance on previously unseen tasks without requiring parameter updates. This capabi…