UAV Path Planning for Object Observation with Quality Constraints: A Dynamic Programming Approach

TL;DR

This paper presents a dynamic programming algorithm for UAV path planning that efficiently observes multiple objects with quality constraints, achieving near-optimal solutions in polynomial time and validated in a realistic simulation environment.

Contribution

The paper introduces a novel dynamic programming approach for UAV path planning that guarantees a near-optimal solution under observation quality constraints.

Findings

Algorithm achieves $(1+psilon)$-approximation ratio.

Runs in polynomial time.

Validated in Airsim simulator with near-optimal results.

Abstract

This paper addresses a UAV path planning task that seeks to observe a set of objects while satisfying the observation quality constraint. A dynamic programming algorithm is proposed that enables the UAV to observe the target objects with the shortest path while subjecting to the observation quality constraint. The objects have their own facing direction and restricted observation range. With an observing order, the algorithm achieves $(1+\epsilon)$-approximation ratio in theory and runs in polynomial time. The extensive results demonstrate that the algorithm produces near-optimal solutions, the effectiveness of which is also tested and proved in the Airsim simulator, a realistic virtual environment.