通过并行策略加速微型无人机群控制器调参，提升稳定性与效率
On rapid parallel tuning of controllers of a swarm of MAVs -- distribution strategies of the updated gains
- 采用相同参数平均反馈结果，降低测量噪声影响
- 多组参数并行测试，使调参时间显著缩短
- 适用于需要快速可靠调参的无人机集群场景
本文提出一种可靠、可扩展且时间确定性的无模型方法，用于基于基础传感数据调优微型飞行器（MAVs）集群的控制器。提出了两种利用并行调参的方法：一是对具有相同增益的集群各成员性能指标进行平均，以减小测量噪声的负面影响；二是让集群内不同个体并行测试不同增益组合，从而大幅减少调参时间。所提方法在仿真和真实实验中均得到验证，结果表明该方法能在缩短调参时间的同时提升调参效果，并确保调参过程的可靠性。
原文摘要 · Abstract (English)
In this paper, we present a reliable, scalable, time deterministic, model-free procedure to tune swarms of Micro Aerial Vehicles (MAVs) using basic sensory data. Two approaches to taking advantage of parallel tuning are presented. First, the tuning with averaging of the results on the basis of performance indices reported from the swarm with identical gains to decrease the negative effect of the noise in the measurements. Second, the tuning with parallel testing of varying set of gains across the swarm to reduce the tuning time. The presented methods were evaluated both in simulation and real-world experiments. The achieved results show the ability of the proposed approach to improve the results of the tuning while decreasing the tuning time, ensuring at the same time a reliable tuning mechanism.
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