activity
20242026
collaborators

8 papers

cs.RO2026

Parallel, Asymptotically Optimal Algorithms for Moving Target Traveling Salesman Problems

Anoop Bhat, Geordan Gutow, Bhaskar Vundurthy +3

The Moving Target Traveling Salesman Problem (MT-TSP) seeks a trajectory that intercepts several moving targets, within a particular time window for each target. When generic nonli…

cs.RO2026

RPT*: Global Planning with Probabilistic Terminals for Target Search in Complex Environments

Yunpeng Lyu, Chao Cao, Ji Zhang +2

Routing problems such as Hamiltonian Path Problem (HPP), seeks a path to visit all the vertices in a graph while minimizing the path cost. This paper studies a variant, HPP with Pr…

cs.RO2025

A Complete and Bounded-Suboptimal Algorithm for a Moving Target Traveling Salesman Problem with Obstacles in 3D

Anoop Bhat, Geordan Gutow, Bhaskar Vundurthy +3

The moving target traveling salesman problem with obstacles (MT-TSP-O) seeks an obstacle-free trajectory for an agent that intercepts a given set of moving targets, each within spe…

cs.RO2025

A Mixed-Integer Conic Program for the Multi-Agent Moving-Target Traveling Salesman Problem

Allen George Philip, Zhongqiang Ren, Sivakumar Rathinam +1

The Moving-Target Traveling Salesman Problem (MT-TSP) seeks a shortest path for an agent that starts at a stationary depot, visits a set of moving targets exactly once, each within…

cs.RO2025

Heuristic Search for Path Finding with Refuelling

Shizhe Zhao, Anushtup Nandy, Howie Choset +2

This paper considers a generalization of the Path Finding (PF) problem with refuelling constraints referred to as the Gas Station Problem (GSP). Similar to PF, given a graph where…

cs.RO2025

A Mixed-Integer Conic Program for the Moving-Target Traveling Salesman Problem based on a Graph of Convex Sets

Allen George Philip, Zhongqiang Ren, Sivakumar Rathinam +1

This paper introduces a new formulation that finds the optimum for the Moving-Target Traveling Salesman Problem (MT-TSP), which seeks to find a shortest path for an agent, that sta…