Work

Adaptive Planning for Multiple UAVs with In-Flight Refueling

Year: 2026

Type: article

Abstract: This paper presents a rolling-horizon replanning framework for multi-UAV missions considering fuel constraints in dynamic environments. At each decision epoch, a re-optimization subproblem is solved to minimize the total travel distance of all agents (UAVs) while visiting remaining task locations, considering en-route refueling depots. A mixed-integer linear programming formulation of the subproblem is proposed to find the optimal solution. In addition, to enable real-time computation, we develop a heuristic-based solver framework: an extended sequential greedy algorithm provides a quick baseline, while a reinforcement learning (RL) approach using an attention model and long short-term memory aims to overcome the local optimality of the greedy method. A case study and numerical experiments demonstrate the effectiveness of the proposed framework and the performance of the solution methods.

Source: International Journal of Aeronautical and Space Sciences

DOI: 10.1007/s42405-026-01249-w

Authors: Beomjin Gwon, Euihyeon Choi, Jeonghun Lee, Jaemyung Ahn

Institutions: Korea Advanced Institute of Science and Technology, Georgia Institute of Technology

Language: English

Topic: Vehicle Routing Optimization Methods

Subfield: Industrial and Manufacturing Engineering

Field: Engineering

Domain: Physical Sciences

SDG: Industry, innovation and infrastructure

Open Access status: hybrid

Estimated APC paid: $3,490