Multi-robot Task Assignment for Aerial Tracking with Viewpoint Constraints

Conference paper (2021)

Authors

Aaron Ray Massachusetts Institute of Technology
Alyssa Pierson Massachusetts Institute of Technology
H. Zhu Learning & Autonomous Control - Mechanical, Maritime and Materials Engineering
J. Alonso-Mora Learning & Autonomous Control - Mechanical, Maritime and Materials Engineering
Daniela Rus Massachusetts Institute of Technology
Research Group
Learning & Autonomous Control (Mechanical, Maritime and Materials Engineering) (TU Delft)
Copyright: © 2021 Aaron Ray, Alyssa Pierson, H. Zhu, J. Alonso-Mora, Daniela Rus
DOI
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https://doi.org/10.1109/IROS51168.2021.9636719
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Published Date

2021

Language

English

Reuse Rights

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Faculty

Mechanical, Maritime and Materials Engineering

Department

Cognitive Robotics

Research Group

Learning & Autonomous Control

Abstract

We address the problem of assigning a team of drones to autonomously capture a set desired shots of a dynamic target in the presence of obstacles. We present a two-stage planning pipeline that generates offline an assignment of drone to shots and locally optimizes online the viewpoint. Given desired shot parameters, the high-level planner uses a visibility heuristic to predict good times for capturing each shot and uses an Integer Linear Program to compute drone assignments. An online Model Predictive Control algorithm uses the assignments as reference to capture the shots. The algorithm is validated in hardware with a pair of drones and a remote controlled car.