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A Time-Optimal Motion Planning Algorithm for Multiple Aerial Transportation Systems Based on Compact Capsule Volume
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AI
DOI：10.1109/jsyst.2026.3682509.png)
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Abstract
En 中文
This work develops a motion planning algorithm for multiple aerial transportation systems that generates time-optimal and collision-aware trajectories, addressing strong dynamic coupling, complex collision conditions, and the conservatism of traditional bounding volumes. First, the complicated nonlinear and underactuated characteristics of the multiple aerial transportation systems are managed through model transforming without any linearization, thereby retaining all dynamic model information. Second, a novel capsule bounding volume is developed that explicitly incorporates the payload state into the geometric encapsulation of each aerial transportation system, which reflects the specific payload state in anti-collision. Compared to existing methods, the proposed bounding volume method fully considers the system dynamics, which brings greater safety to real-world experiments. Furthermore, the proposed volume is more compact, thereby resulting in a larger solution space during motion planning. Then, an idea of scale is presented, which assists in the detection of collisions. Finally, the dynamics and all the constrains are equivalently transformed to formulate the to-be-solved optimal problem, which is finally solved by Gauss pseudospectral method-based algorithms. Comparative experiments verify that the proposed method yields safer and more aggressive trajectories than existing approaches, ensuring strict compliance with swing angle constraints even during time-optimal flight.
Keywords:
Aerial transportation system (ATS)
motion planning
underactuated systems
uncrewed aerial vehicle (UAV)