ROSep 1, 2018

Robust 3D Distributed Formation Control with Application to Quadrotors

arXiv:1809.00093v1
Originality Incremental advance
AI Analysis

This addresses formation control for quadrotor teams, which is incremental as it builds on existing distributed control methods with robustness to measurement inaccuracies.

The paper tackled the problem of enabling a team of quadrotors to autonomously achieve a desired 3D formation using a distributed control strategy based on local relative position measurements without global information or communication, and demonstrated its validity in experiments.

We present a distributed control strategy for a team of quadrotors to autonomously achieve a desired 3D formation. Our approach is based on local relative position measurements and does not require global position information or inter-vehicle communication. We assume that quadrotors have a common sense of direction, which is chosen as the direction of gravitational force measured by their onboard IMU sensors. However, this assumption is not crucial, and our approach is robust to inaccuracies and effects of acceleration on gravitational measurements. In particular, converge to the desired formation is unaffected if each quadrotor has a velocity vector that projects positively onto the desired velocity vector provided by the formation control strategy. We demonstrate the validity of proposed approach in an experimental setup and show that a team of quadrotors achieve a desired 3D formation.

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