Swarm Navigation Based on Smoothed Particle Hydrodynamics in Complex Obstacle Environments

IF 4.6 2区 计算机科学 Q2 ROBOTICS
Ruocheng Li;Bin Xin;Shuai Zhang;Mingzhe Lyu;Jinqiang Cui
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引用次数: 0

Abstract

In this letter, we propose a method for the navigation of swarm uncrewed aerial vehicles (UAVs) in complex environments with obstacles. We propose an algorithmic framework based on Smoothed Particle Hydrodynamics (SPH). In this framework, each UAV is considered a particle, computing its motion information through local interactions with surrounding particles. Based on SPH, the UAV swarm can interactively adjust itself, allowing the entire cluster to advance in the flow pattern of an incompressible fluid. We introduce the Euclidean Signed Distance Field (ESDF) as a representation of the environment. The ESDF is constructed based on the obstacle information in the environment, enabling the swarm to deform and avoid obstacles within the environment. Simultaneously, we propose a swarm navigation function based on B-splines, rapidly obtaining executable trajectories by solving an unconstrained gradient optimization problem. Compared with existing methods, our algorithm exhibits significant improvements in success rate, stability, and scalability. Extensive simulations and physical experiments in both 2D and 3D environments have demonstrated the effectiveness of the proposed method.
复杂障碍环境下基于光滑粒子流体力学的群体导航
在这封信中,我们提出了一种在复杂环境中具有障碍物的蜂群无人机(uav)导航方法。提出了一种基于光滑粒子流体力学(SPH)的算法框架。在这个框架中,每个无人机都被认为是一个粒子,通过与周围粒子的局部相互作用计算其运动信息。基于SPH,无人机群可以进行自我交互调整,使整个集群在不可压缩流体的流动模式中前进。我们引入欧几里得符号距离场(ESDF)作为环境的表示。ESDF是基于环境中的障碍物信息构建的,使蜂群能够变形并避开环境中的障碍物。同时,我们提出了一种基于b样条的群体导航函数,通过求解无约束梯度优化问题快速获得可执行轨迹。与现有方法相比,我们的算法在成功率、稳定性和可扩展性方面都有显著提高。在二维和三维环境下的大量仿真和物理实验证明了该方法的有效性。
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来源期刊
IEEE Robotics and Automation Letters
IEEE Robotics and Automation Letters Computer Science-Computer Science Applications
CiteScore
9.60
自引率
15.40%
发文量
1428
期刊介绍: The scope of this journal is to publish peer-reviewed articles that provide a timely and concise account of innovative research ideas and application results, reporting significant theoretical findings and application case studies in areas of robotics and automation.
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