9 papers
GAMMS: Graph based Adversarial Multiagent Modeling Simulator
Rohan Patil, Jai Malegaonkar, Xiao Jiang +3
As intelligent systems and multi-agent coordination become increasingly central to real-world applications, there is a growing need for simulation tools that are both scalable and…
LEARN: Learning End-to-End Aerial Resource-Constrained Multi-Robot Navigation
Darren Chiu, Zhehui Huang, Ruohai Ge +1
Nano-UAV teams offer great agility yet face severe navigation challenges due to constrained onboard sensing, communication, and computation. Existing approaches rely on high-resolu…
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…
Refinery: Active Fine-tuning and Deployment-time Optimization for Contact-Rich Policies
Bingjie Tang, Iretiayo Akinola, Jie Xu +6
Simulation-based learning has enabled policies for precise, contact-rich tasks (e.g., robotic assembly) to reach high success rates (~80%) under high levels of observation noise an…
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…