Energy-Aware Collaborative Exploration for a UAV-UGV Team

TL;DR

This paper introduces an energy-aware exploration framework for UAV-UGV teams, optimizing collaborative tours within energy constraints to maximize environmental information gathering.

Contribution

It proposes a novel layered probabilistic roadmap and coupled orienteering problem formulation for energy-aware UAV-UGV exploration.

Findings

Effective energy management extends UAV operational time.

Collaborative exploration improves coverage efficiency.

Simulation and real-world tests validate the approach.

Abstract

We present an energy-aware collaborative exploration framework for a UAV-UGV team operating in unknown environments, where the UAV's energy constraint is modeled as a maximum flight-time limit. The UAV executes a sequence of energy-bounded exploration tours, while the UGV simultaneously explores on the ground and serves as a mobile charging station. Rendezvous is enforced under a shared time budget so that the vehicles meet at the end of each tour before the UAV reaches its flight-time limit. We construct a sparsely coupled air-ground roadmap using a density-aware layered probabilistic roadmap (PRM) and formulate tour selection over the roadmap as coupled orienteering problems (OPs) to maximize information gain subject to the rendezvous constraint. The resulting tours are constructed over collision-validated roadmap edges. We validate our method through simulation studies, benchmark comparisons, and real-world experiments.