Viewpoint-driven Formation Control of Airships for Cooperative Target Tracking

TL;DR

This paper presents a model predictive control approach for airship formations to optimize multi-object tracking and motion capture, considering airship dynamics and environmental factors, validated through simulations and real-world tests.

Contribution

It introduces a novel MPC-based formation control method tailored for airships, addressing their non-holonomic constraints and wind effects for improved target tracking.

Findings

Effective formation control demonstrated in simulations.

Successful real-world airship tracking experiment.

Open-source code and demonstration videos provided.

Abstract

For tracking and motion capture (MoCap) of animals in their natural habitat, a formation of safe and silent aerial platforms, such as airships with on-board cameras, is well suited. In our prior work we derived formation properties for optimal MoCap, which include maintaining constant angular separation between observers w.r.t. the subject, threshold distance to it and keeping it centered in the camera view. Unlike multi-rotors, airships have non-holonomic constrains and are affected by ambient wind. Their orientation and flight direction are also tightly coupled. Therefore a control scheme for multicopters that assumes independence of motion direction and orientation is not applicable. In this paper, we address this problem by first exploiting a periodic relationship between the airspeed of an airship and its distance to the subject. We use it to derive analytical and numeric solutions that satisfy the formation properties for optimal MoCap. Based on this, we develop an MPC-based formation controller. We perform theoretical analysis of our solution, boundary conditions of its applicability, extensive simulation experiments and a real world demonstration of our control method with an unmanned airship. Open source code https://tinyurl.com/AsMPCCode and a video of our method is provided at https://tinyurl.com/AsMPCVid .