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

arXiv: https://arxiv.org/abs/2011.01492 · HTML: https://mlsanity.com/paper/2011.01492/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 3 Nov 2020.

## Built on by (most cited first, 1 of 1)

- [A Convex Hull Cheapest Insertion Heuristic for the Non-Euclidean TSP](https://mlsanity.com/paper/2302.06582/) (2023)

## Abstract (arXiv)

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 mTSP 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.