Multicopter swarms with decentralized structures offer more flexibility but efficient spatial-temporal trajectory planning for them can be challenging. Fei Gao and her team aim to change that. Their decentralized spatial-temporal trajectory planning system for multicopter Swarms ensures
high-quality local planning for each agent subject to any constraint from either the coordination of the swarm or safety requirements in cluttered environments. Then, the local trajectory generation is formulated as an unconstrained optimization problem that is efficiently solved in milliseconds. Moreover, a decentralized asynchronous mechanism is designed to trigger the local planning for each agent.
The below video gives you a better idea how this works:
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