Work

Aerial-Ground Collaborative Routing with Uncertain Exploration Value

Year: 2025

Type: article

Abstract: This study develops a novel framework for aerial-ground collaborative routing that addresses uncertainty in exploration value. The framework enables an unmanned aerial vehicle (UAV) to conduct rapid reconnaissance while a ground vehicle (GV) gathers profit, dynamically optimizing the GV’s route based on updated information. Two complementary approaches are presented: a mixed integer linear programming (MILP) formulation for optimal path selection and an adaptive two-phase method for robust, uncertain environment exploration. A case study validates these approaches, demonstrating how aerial-ground collaboration improves mission efficiency and information acquisition in uncertain environments.

Source: International Journal of Aeronautical and Space Sciences

DOI: 10.1007/s42405-025-00892-z

Authors: Chaehwan Moon, Euihyeon Choi, 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