1 citations · 1 across the 5 of their papers we have counts for
5 papers
Targeted Parallelization of Conflict-Based Search for Multi-Robot Path Planning
Teng Guo, Jingjin Yu
Multi-Robot Path Planning (MRPP) on graphs, equivalently known as Multi-Agent Path Finding (MAPF), is a well-established NP-hard problem with critically important applications. As…
Well-Connected Set and Its Application to Multi-Robot Path Planning
Teng Guo, Jingjin Yu
Parking lots and autonomous warehouses for accommodating many vehicles/robots adopt designs in which the underlying graphs are \emph{well-connected} to simplify planning and reduce…
Toward Efficient Physical and Algorithmic Design of Automated Garages
Teng Guo, Jingjin Yu
Parking in large metropolitan areas is often a time-consuming task with further implications toward traffic patterns that affect urban landscaping. Reducing the premium space neede…
Polynomial Time Near-Time-Optimal Multi-Robot Path Planning in Three Dimensions with Applications to Large-Scale UAV Coordination
Teng Guo, Siwei Feng, Jingjin Yu
For enabling efficient, large-scale coordination of unmanned aerial vehicles (UAVs) under the labeled setting, in this work, we develop the first polynomial time algorithm for the…
Sub-1.5 Time-Optimal Multi-Robot Path Planning on Grids in Polynomial Time
Teng Guo, Jingjin Yu
Graph-based multi-robot path planning (MRPP) is NP-hard to optimally solve. In this work, we propose the first low polynomial-time algorithm for MRPP achieving 1--1.5 asymptotic op…