Work

Collaborative Path Planning of Energy-Sharing Drone-UGV Teams for Persistent Patrolling

Year: 2026

Type: article

Abstract: Teams of unmanned ground vehicles (UGVs) and drones are often proposed for various applications in autonomous transportation, where drones quickly move from one point of interest to the next while UGVs act as moving base stations that can both recharge and ferry the drones around. In this article, we look at how to plan collaborative actions among multiple teams of energy-sharing drones and UGVs for patrolling applications over an indefinite time horizon. We demonstrate how to form a second-order cone (SOC) program that finds optimal solutions, in polynomial time, when the order of drone and UGV actions are fixed. We propose an algorithm that uses various heuristics and our SOC program to find locally optimal solutions while considering the limited energy of both vehicle types. Additionally, we present a new nomenclature for classifying drone-UGV planning problems and propose a novel metric for evaluating multi-agent patrolling plans. We ran various numerical simulations using field data to evaluate our proposed approach. Our algorithm improves solution quality by up to 37.7% compared with a baseline method from the literature. Furthermore, we demonstrate the authenticity of our problem setup through a proof-of-concept experiment on a physical UGV and drone testbed.

Source: ACM Journal on Autonomous Transportation Systems

DOI: 10.1145/3788877

Authors: Jonathan Diller, Jack Sigler, Qi Han

Institutions: Colorado School of Mines, University of Pennsylvania

Language: English

Topic: Robotic Path Planning Algorithms

Subfield: Computer Vision and Pattern Recognition

Field: Computer Science

Domain: Physical Sciences

SDG: Industry, innovation and infrastructure

Open Access status: hybrid

Funder: Army Research Laboratory