1 citations · 1 across the 12 of their papers we have counts for
12 papers
WOLF: World Model Guided LiDAR Exploration with Predictive Frontiers
Yuyang Tian, Penghui Yang, Pengyuan Wu +7
LiDAR-based unmanned aerial vehicle (UAV) exploration builds maps by continually selecting where to observe next. However, decisions based on the measured map provide limited fores…
RPG: Robust Policy Gating for Smooth Multi-Skill Transitions in Humanoid Fighting
Yucheng Xin, Jiacheng Bao, Yubo Dong +5
Humanoid robots have demonstrated impressive motor skills in a wide range of tasks, yet whole-body control for humanlike long-time, dynamic fighting remains particularly challengin…
Learn Weightlessness: Imitate Non-Self-Stabilizing Motions on Humanoid Robot
Yucheng Xin, Jiacheng Bao, Haoran Yang +6
The integration of imitation and reinforcement learning has enabled remarkable advances in humanoid whole-body control, facilitating diverse human-like behaviors. However, research…
Beyond Short-Horizon: VQ-Memory for Robust Long-Horizon Manipulation in Non-Markovian Simulation Benchmarks
Honghui Wang, Zhi Jing, Jicong Ao +4
The high cost of collecting real-robot data has made robotic simulation a scalable platform for both evaluation and data generation. Yet most existing benchmarks concentrate on sim…
ZeroWBC: Learning Natural Whole-Body Humanoid Interaction from Human Egocentric Data
Haoran Yang, Jiacheng Bao, Yucheng Xin +5
Achieving versatile and natural whole-body humanoid interaction control remains challenging due to the high cost of whole-body teleoperation data. We present ZeroWBC, a teleoperati…
SAGE-LLM: Towards Safe and Generalizable LLM Controller with Fuzzy-CBF Verification and Graph-Structured Knowledge Retrieval for UAV Decision
Wenzhe Zhao, Yang Zhao, Ganchao Liu +4
In UAV dynamic decision, complex and variable hazardous factors pose severe challenges to the generalization capability of algorithms. Despite offering semantic understanding and s…
Depth Helps: Improving Pre-trained RGB-based Policy with Depth Information Injection
Xincheng Pang, Wenke Xia, Zhigang Wang +4
3D perception ability is crucial for generalizable robotic manipulation. While recent foundation models have made significant strides in perception and decision-making with RGB-bas…
KOI: Accelerating Online Imitation Learning via Hybrid Key-state Guidance
Jingxian Lu, Wenke Xia, Dong Wang +4
Online Imitation Learning struggles with the gap between extensive online exploration space and limited expert trajectories, hindering efficient exploration due to inaccurate rewar…
Play to the Score: Stage-Guided Dynamic Multi-Sensory Fusion for Robotic Manipulation
Ruoxuan Feng, Di Hu, Wenke Ma +1
Humans possess a remarkable talent for flexibly alternating to different senses when interacting with the environment. Picture a chef skillfully gauging the timing of ingredient ad…
Decentralized Transformers with Centralized Aggregation are Sample-Efficient Multi-Agent World Models
Yang Zhang, Chenjia Bai, Bin Zhao +3
Learning a world model for model-free Reinforcement Learning (RL) agents can significantly improve the sample efficiency by learning policies in imagination. However, building a wo…
SAM-E: Leveraging Visual Foundation Model with Sequence Imitation for Embodied Manipulation
Junjie Zhang, Chenjia Bai, Haoran He +5
Acquiring a multi-task imitation policy in 3D manipulation poses challenges in terms of scene understanding and action prediction. Current methods employ both 3D representation and…
Kinematic-aware Prompting for Generalizable Articulated Object Manipulation with LLMs
Wenke Xia, Dong Wang, Xincheng Pang +4
Generalizable articulated object manipulation is essential for home-assistant robots. Recent efforts focus on imitation learning from demonstrations or reinforcement learning in si…