3 citations · 3 across the 8 of their papers we have counts for
10 papers
Failure-Resilient Multi-Robot Coordination with -Connectivity Constrained Submodular Maximization
Yoonjae Hwang, Hojune Kim, Ellen Novoseller +2
Multi-robot coordination is essential in applications such as coverage, target tracking, and information gathering, where robots must jointly select actions to maximize team perfor…
MA-LIPP: Cooperative Multi-Agent Load-Aware Informative Path Planning for Heterogeneous Robot Teams
Hojune Kim, Guangyao Shi, Gaurav S. Sukhatme
Field robotics missions often require physical samples to be returned to laboratories for analysis, making path planning inherently load-aware and order-dependent as accumulated sa…
EFLUX: Elastic Multi-Robot Formation Navigation and Adaptation with Agentic LLMs
Jinyuan Zhang, Yuwei Wu, Guangyao Shi +3
Multi-robot teams operating in confined or cluttered environments must adapt both their formation geometry and group topology to navigate through complex obstacles. This adaptation…
PIP-LLM: Integrating PDDL-Integer Programming with LLMs for Coordinating Multi-Robot Teams Using Natural Language
Guangyao Shi, Yuwei Wu, Vijay Kumar +1
Enabling robot teams to execute natural language commands requires translating high-level instructions into feasible, efficient multi-robot plans. While Large Language Models (LLMs…
SPAR: Scalable LLM-based PDDL Domain Generation for Aerial Robotics
Songhao Huang, Yuwei Wu, Guangyao Shi +2
We investigate the problem of automatic domain generation for the Planning Domain Definition Language (PDDL) using Large Language Models (LLMs), with a particular focus on unmanned…
Compositional Coordination for Multi-Robot Teams with Large Language Models
Zhehui Huang, Guangyao Shi, Yuwei Wu +2
Multi-robot coordination has traditionally relied on a mission-specific and expert-driven pipeline, where natural language mission descriptions are manually translated by domain ex…
Hierarchical LLMs In-the-Loop Optimization for Real-Time Multi-Robot Target Tracking under Unknown Hazards
Yuwei Wu, Yuezhan Tao, Peihan Li +4
Real-time multi-robot coordination in hazardous and adversarial environments requires fast, reliable adaptation to dynamic threats. While Large Language Models (LLMs) offer strong…
Inverse Risk-sensitive Multi-Robot Task Allocation
Guangyao Shi, Gaurav S. Sukhatme
We consider a new variant of the multi-robot task allocation problem - Inverse Risk-sensitive Multi-Robot Task Allocation (IR-MRTA). "Forward" MRTA - the process of deciding which…
Human-in-the-Loop Multi-Robot Information Gathering with Inverse Submodular Maximization
Guangyao Shi, Shipeng Liu, Ellen Novoseller +2
We consider a new type of inverse combinatorial optimization, Inverse Submodular Maximization (ISM), for its application in human-in-the-loop multi-robot information gathering. For…
Can Large Language Models Solve Robot Routing?
Zhehui Huang, Guangyao Shi, Gaurav S. Sukhatme
Routing problems are common in mobile robotics, encompassing tasks such as inspection, surveillance, and coverage. Depending on the objective and constraints, these problems often…