Control Barrier Function Based Decentralized UAV Swarm Navigation While Preserving Connectivity Without Explicit Communication
Control Barrier Function Based Decentralized UAV Swarm Navigation While Preserving Connectivity Without Explicit Communication
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DOI：
10.23919/acc55779.2023.10156409
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发表时间：
2023-05
期刊：
影响因子：
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通讯作者：
Thiviyathinesvaran Palani;H. Fukushima;Shunsuke Izuhara
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文献类型：
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作者：
Thiviyathinesvaran Palani;H. Fukushima;Shunsuke Izuhara
针对无人机群在障碍物环境中的导航问题，提出了一种分散的领航者-跟随者导航方法。所提出的方法基于控制势垒函数(CBF)，旨在克服目前使用人工势函数(APF)的方法的局限性，在某些情况下可能会导致不期望的振动运动。本研究提出的算法只使用局部传感器信息计算控制输入，而不需要机器人之间的显式通信，目的是确保组内的碰撞避免、障碍物避免和连通性保持。控制输入的推导不依赖于数值求解技术，所提出的方法旨在防止约束违反发生在发生之前。将该方法与基于APF的方法在振动运动环境下的性能进行了比较，仿真结果表明该方法能够实现更平滑的机器人运动。此外，通过对四旋翼的实验验证，验证了该方法的有效性。
This paper proposes a decentralized leader-follower navigation method for a group of unmanned aerial vehicles (UAVs) in environments with obstacles. The proposed method is based on control barrier functions (CBFs) and is designed to overcome the limitations of current approaches that use artificial potential functions (APFs), which may in some cases cause undesired vibratory movements. The algorithm presented in this study computes control inputs using only local sensor information and without explicit communication between the robots, with the aim of ensuring collision avoidance, obstacle avoidance, and connectivity preservation in the group. The control inputs are derived without relying on numerical solution techniques, and the proposed approach aims to prevent constraint violations from occurring before they happen. The performance of the proposed approach is compared to the APF-based approach in the context of vibratory movements, and simulation results demonstrate its ability to achieve smoother robot movements. Moreover, the effectiveness of the proposed approach is confirmed through experimental validation with quadrotors.