基于Cross-EKF定位的多机器人协作围捕策略研究

Multi-robots cooperative hunting strategy based on Cross-EKF localization

针对目前多机器人协作围捕过程中收敛速度慢、稳定性差、定位精度低的问题,提出一种新的围捕策略.设计出Cross-EKF定位算法,对目标位置的后验估计协方差进行交叉计算,以取得最小协方差区域.以区域边缘点到均值中心最大距离为半径,构建收敛圆,将对动态点的收敛扩展为对动态面的收敛.实验结果表明,系统能快速平稳地收敛该圆,从而实现对目标的精确围捕,该方法具有较高的实用价值.

A new multi-robots cooperative hunting strategy based on Cross-EKF localization is proposed for enhancing convergence rate, robustness and precision. In this strategy, the posterior estimate covariance for target location estimated by multi-robots is crossly calculated, and a minimum covariance is obtained. The maximum distance from edge points to mean center is used as radius to construct a convergence circle. The convergence to dynamic point is expanded to circle surface. The experimental results show that the circle is quickly and smoothly converged and the target is accurately hunted. The method possesses high practical value.