Planning for Aerial Robot Teams for Wide-Area Biometric and Phenotypic Data Collection

TL;DR

This paper introduces a hierarchical approach for joint task allocation and path planning in multi-UAV systems for wide-area biometric data collection, addressing a complex sensing-constrained vehicle routing problem.

Contribution

It proposes a novel hierarchical solution combining clustering-based target allocation with decoupled routing, suitable for real-time multi-UAV biometric data collection.

Findings

Effective multi-UAV path planning with sensing constraints.

Hierarchical approach reduces computational complexity.

Successful implementation on quadcopter platforms.

Abstract

This work presents an efficient and implementable solution to the problem of joint task allocation and path planning in a multi-UAV platform deployed for biometric data collection in-the-wild. The sensing requirement associated with the task gives rise to an uncanny variant of the traditional vehicle routing problem with coverage/sensing constraints. As is the case in several multi-robot path-planning problems, our problem reduces to an $m$TSP problem. In order to tame the computational challenges associated with the problem, we propose a hierarchical solution that decouples the vehicle routing problem from the target allocation problem. As a tangible solution to the allocation problem, we use a clustering-based technique that incorporates temporal uncertainty in the cardinality and position of the robots. Finally, we implement the proposed techniques on our multi-quadcopter platforms.