18 citations · 57 across the 32 of their papers we have counts for
9 papers · 1 filter
Subdimensional Expansion Using Attention-Based Learning For Multi-Agent Path Finding
Lakshay Virmani, Zhongqiang Ren, Sivakumar Rathinam +1
Multi-Agent Path Finding (MAPF) finds conflict-free paths for multiple agents from their respective start to goal locations. MAPF is challenging as the joint configuration space gr…
Multi-objective Conflict-based Search Using Safe-interval Path Planning
Zhongqiang Ren, Sivakumar Rathinam, Maxim Likhachev +1
This paper addresses a generalization of the well known multi-agent path finding (MAPF) problem that optimizes multiple conflicting objectives simultaneously such as travel time an…
Multi-Objective Path-Based D* Lite
Zhongqiang Ren, Sivakumar Rathinam, Maxim Likhachev +1
Incremental graph search algorithms such as D* Lite reuse previous, and perhaps partial, searches to expedite subsequent path planning tasks. In this article, we are interested in…
Bounds on Optimal Revisit Times in Persistent Monitoring Missions with a Distinct \& Remote Service Station
Sai Krishna Kanth Hari, Sivakumar Rathinam, Swaroop Darbha +3
Persistent monitoring missions require an up-to-date knowledge of the changing state of the underlying environment. UAVs can be gainfully employed to continually visit a set of tar…
MS*: A New Exact Algorithm for Multi-agent Simultaneous Multi-goal Sequencing and Path Finding
Zhongqiang Ren, Sivakumar Rathinam, Howie Choset
In multi-agent applications such as surveillance and logistics, fleets of mobile agents are often expected to coordinate and safely visit a large number of goal locations as effici…
S: A Heuristic Information-Based Approximation Framework for Multi-Goal Path Finding
Kenny Chour, Sivakumar Rathinam, Ramamoorthi Ravi
We combine ideas from uni-directional and bi-directional heuristic search, and approximation algorithms for the Traveling Salesman Problem, to develop a novel framework for a Multi…