21 citations · 26 across the 9 of their papers we have counts for
10 papers
Scalable Algorithms with Provable Optimality Bounds for the Multiple Watchman Route Problem
Srikar Gouru, Ariel Felner, Jiaoyang Li
In this paper, we tackle the Multiple Watchman Route Problem (MWRP), which aims to find a set of paths that M watchmen can follow such that every location on the map can be seen by…
Lifelong Scalable Multi-Agent Realistic Testbed and A Comprehensive Study on Design Choices in Lifelong AGV Fleet Management Systems
Jingtian Yan, Yulun Zhang, Zhenting Liu +5
We present Lifelong Scalable Multi-Agent Realistic Testbed (LSMART), an open-source simulator to evaluate any Multi-Agent Path Finding (MAPF) algorithm in a Fleet Management System…
From Discrete Plans to Real-World Execution: A World-Model-Driven Framework for Execution-Aware Multi-Agent Path Finding
Jingtian Yan, Shuai Zhou, He Jiang +2
Multi-Agent Path Finding (MAPF) studies how to coordinate multiple agents to reach their goals without collisions and underpins a range of large-scale robotic systems, including au…
WinkTPG: An Execution Framework for Multi-Agent Path Finding Using Temporal Reasoning
Jingtian Yan, Stephen F. Smith, Jiaoyang Li
Planning collision-free paths for a large group of agents is a challenging problem in many real-world applications. While recent advances in Multi-Agent Path Finding (MAPF) have sh…
Advancing MAPF Toward the Real World: A Scalable Multi-Agent Realistic Testbed (SMART)
Jingtian Yan, Zhifei Li, William Kang +7
We present Scalable Multi-Agent Realistic Testbed (SMART), a realistic and efficient software tool for evaluating Multi-Agent Path Finding (MAPF) algorithms. MAPF focuses on planni…
Multi-Agent Motion Planning For Differential Drive Robots Through Stationary State Search
Jingtian Yan, Jiaoyang Li
Multi-Agent Motion Planning (MAMP) finds various applications in fields such as traffic management, airport operations, and warehouse automation. In many of these environments, dif…
Optimal Task Assignment and Path Planning using Conflict-Based Search with Precedence and Temporal Constraints
Yu Quan Chong, Jiaoyang Li, Katia Sycara
The Multi-Agent Path Finding (MAPF) problem entails finding collision-free paths for a set of agents, guiding them from their start to goal locations. However, MAPF does not accoun…
Bidirectional Temporal Plan Graph: Enabling Switchable Passing Orders for More Efficient Multi-Agent Path Finding Plan Execution
Yifan Su, Rishi Veerapaneni, Jiaoyang Li
The Multi-Agent Path Finding (MAPF) problem involves planning collision-free paths for multiple agents in a shared environment. The majority of MAPF solvers rely on the assumption…
Multi-Agent Motion Planning with Bézier Curve Optimization under Kinodynamic Constraints
Jingtian Yan, Jiaoyang Li
Multi-Agent Motion Planning (MAMP) is a problem that seeks collision-free dynamically-feasible trajectories for multiple moving agents in a known environment while minimizing their…
Enhancing Multi-Drone Coordination for Filming Group Behaviours in Dynamic Environments
Aditya Rauniyar, Jiaoyang Li, Sebastian Scherer
Multi-Agent Path Finding (MAPF) is a fundamental problem in robotics and AI, with numerous applications in real-world scenarios. One such scenario is filming scenes with multiple a…