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基于 IB-LBM 的多仿生蛇机器人在流场中的协同避障算法。

Collaborative obstacle avoidance algorithm of multiple bionic snake robots in fluid based on IB-LBM.

机构信息

Fuzhou university, Fuzhou, Fujian, China; Beijing Institute of Technology, Beijing, China.

Beijing Institute of Technology, Beijing, China.

出版信息

ISA Trans. 2022 Mar;122:271-280. doi: 10.1016/j.isatra.2021.04.048. Epub 2021 May 10.

DOI:10.1016/j.isatra.2021.04.048
PMID:33992419
Abstract

This paper presents a collaborative obstacle avoidance algorithm of multiple bionic snake robots in fluid based on IB-LBM. The method can make the multiple bionic snake robots avoid different obstacles in the fluid under the control of the improved Serpenoid curve function. The proposed method has high parallelism, can simulate the complex non-linear phenomenon of the multiple snake robots, deal with the complex boundary conditions of the robot, and reduce the conversion of the computational grid. Firstly, a non-linear fluid model is established by LBM, which solves the non-linear problem that the classical Navier-Stokes equations cannot explain the random motion. Secondly, the force source boundary model of multiple bionic snake robots is established by IBM, which saves the calculation time, improves the calculation efficiency and system stability. After that, each bionic snake robot is given a special force to make the robots collaborate with each other and non-colliding with each other in the process of the obstacle avoidance. Finally, through simulation experiments, the trajectory of multiple bionic snake robots avoiding different number of the obstacles in the fluid is analyzed and the collaborative obstacle avoidance process of multiple bionic snake robots in fluid is observed. The validity of the collaborative obstacle avoidance algorithm of multiple bionic snake robots in fluid based on the IB-LBM is verified.

摘要

本文提出了一种基于 IB-LBM 的多仿生蛇机器人在流体中的协同避障算法。该方法可以在改进的 Serpenoid 曲线函数的控制下,使多仿生蛇机器人在流体内避开不同的障碍物。所提出的方法具有高度的并行性,可以模拟多蛇机器人的复杂非线性现象,处理机器人的复杂边界条件,并减少计算网格的转换。首先,通过 LBM 建立非线性流体模型,解决了经典 Navier-Stokes 方程无法解释随机运动的非线性问题。其次,通过 IBM 建立多仿生蛇机器人的力源边界模型,节省了计算时间,提高了计算效率和系统稳定性。然后,为每个仿生蛇机器人赋予特殊的力,使机器人在避障过程中相互协作且不发生碰撞。最后,通过仿真实验,分析了多仿生蛇机器人在流体内避开不同数量障碍物的轨迹,观察了多仿生蛇机器人在流体内的协同避障过程。验证了基于 IB-LBM 的多仿生蛇机器人在流体中的协同避障算法的有效性。

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