1 citations · 2 across the 8 of their papers we have counts for
8 papers
StratMamba: Strategic and Reactive Stream Partitioning for Path-Efficient LiDAR-Based Obstacle Avoidance
Hung-Chieh Wu, Xiaopan Zhang, Kasra Sinaei +6
This paper proposes StratMamba, a dual-stream Mamba-based temporal modeling architecture, to more efficiently capture long-horizon temporal dependencies required for robot navigati…
CommCP: Efficient Multi-Agent Coordination via LLM-Based Communication with Conformal Prediction
Xiaopan Zhang, Zejin Wang, Zhixu Li +2
To complete assignments provided by humans in natural language, robots must interpret commands, generate and answer relevant questions for scene understanding, and manipulate targe…
GUIDES: Guidance Using Instructor-Distilled Embeddings for Pre-trained Robot Policy Enhancement
Minquan Gao, Xinyi Li, Qing Yan +4
Pre-trained robot policies serve as the foundation of many validated robotic systems, which encapsulate extensive embodied knowledge. However, they often lack the semantic awarenes…
Towards Generalizable Safety in Crowd Navigation via Conformal Uncertainty Handling
Jianpeng Yao, Xiaopan Zhang, Yu Xia +3
Mobile robots navigating in crowds trained using reinforcement learning are known to suffer performance degradation when faced with out-of-distribution scenarios. We propose that b…
From 2D to 3D Cognition: A Brief Survey of General World Models
Ningwei Xie, Zizi Tian, Lei Yang +3
World models have garnered increasing attention in the development of artificial general intelligence (AGI), serving as computational frameworks for learning representations of the…
HEAL: An Empirical Study on Hallucinations in Embodied Agents Driven by Large Language Models
Trishna Chakraborty, Udita Ghosh, Xiaopan Zhang +5
Large language models (LLMs) are increasingly being adopted as the cognitive core of embodied agents. However, inherited hallucinations, which stem from failures to ground user ins…
LaMMA-P: Generalizable Multi-Agent Long-Horizon Task Allocation and Planning with LM-Driven PDDL Planner
Xiaopan Zhang, Hao Qin, Fuquan Wang +2
Language models (LMs) possess a strong capability to comprehend natural language, making them effective in translating human instructions into detailed plans for simple robot tasks…
SoNIC: Safe Social Navigation with Adaptive Conformal Inference and Constrained Reinforcement Learning
Jianpeng Yao, Xiaopan Zhang, Yu Xia +3
Reinforcement learning (RL) enables social robots to generate trajectories without relying on human-designed rules or interventions, making it generally more effective than rule-ba…