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Who to Trust in Multi-Robot Systems: Joint Robot and Object Hypothesis Trust Inference via Neural-Symbolic Cross-Validation
Ruiyang Wang, Hao-Lun Hsu, Haocheng Meng +2
Multi-robot systems (MRS) offer significant advantages over single-robot platforms by enabling information sharing and coordination for different tasks in complex environments. How…
GAVEL: Graph World Models for Verified and Efficient Long-Horizon LLM Task Planning
Ruiyang Wang, Hao-Lun Hsu, Swarajh Mehta +3
Large language models (LLMs) provide a flexible interface for long-horizon robot planning, but generated plans often fail to respect embodiment constraints, recover from planning e…
Semantic Area Graph Reasoning for Multi-Robot Language-Guided Search
Ruiyang Wang, Hao-Lun Hsu, Jiwoo Kim +1
Coordinating multi-robot systems (MRS) to search in unknown environments is particularly challenging for tasks that require semantic reasoning beyond geometric exploration. Classic…
COMRES-VLM: Coordinated Multi-Robot Exploration and Search using Vision Language Models
Ruiyang Wang, Hao-Lun Hsu, David Hunt +3
Autonomous exploration and object search in unknown indoor environments remain challenging for multi-robot systems (MRS). Traditional approaches often rely on greedy frontier assig…