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• W3201530632 abstract "For aerial swarms, navigation in a prescribed formation is widely practiced in various scenarios. However, the associated planning strategies typically lack the capability of avoiding obstacles in cluttered environments. To address this deficiency, we present an optimization-based method that ensures collision-free trajectory generation for formation flight. In this paper, a novel differentiable metric is proposed to quantify the overall similarity distance between formations. We then formulate this metric into an optimization framework, which achieves spatial-temporal planning using polynomial trajectories. Minimization over collision penalty is also incorporated into the framework, so that formation preservation and obstacle avoidance can be handled simultaneously. To validate the efficiency of our method, we conduct benchmark comparisons with other cutting-edge works. Integrated with an autonomous distributed aerial swarm system, the proposed method demonstrates its efficiency and robustness in real-world experiments with obstacle-rich surroundings <sup xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink>1</sup> 1https://www.youtube.com/watch?v=lFumtOrJci4. We will release the source code for the reference of the community <sup xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink>2</sup> 2https://github.com/ZJU-FAST-Lab/Swarm-Formation." @default.
• W3201530632 created "2021-09-27" @default.
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• W3201530632 date "2022-05-23" @default.
• W3201530632 modified "2023-10-18" @default.
• W3201530632 title "Distributed Swarm Trajectory Optimization for Formation Flight in Dense Environments" @default.
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• W3201530632 doi "https://doi.org/10.1109/icra46639.2022.9812050" @default.
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