基于CKF的移动辅助机器人轨迹规划研究

Fucheng Cao, Yuan-chun Li, Lirong Wang
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引用次数: 2

摘要

针对移动辅助机器人的跟踪规划问题,提出了一种基于卡尔曼滤波(KF)的跟踪规划方法。基于已知的移动辅助机器人非完整动力学模型,采用稳态卡尔曼滤波(cuature kalman filter, CKF)来改善非线性系统的影响,实现了移动辅助机器人的自主导航与控制。实验结果表明,该方法在稳定性、精度和计算复杂度方面都优于扩展卡尔曼滤波和无气味卡尔曼滤波。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Research of Trajectory Planning for Mobility Assistance Robot Based on CKF
According to the problem on tracking planning of mobility assistance robot, a tracking planning method was presented using the kalman filter (KF). Based on known nonholonomic dynamic model of mobility assistance robot, the cubature kalman filter (CKF) was used to improve the influence of nonlinear system, and the autonomous navigation and control of mobility assistance robot was realized. The experimental results indicate that the method presented in this paper was excellent than extended kalman filter (EKF) and unscented kalman filter (UKF) in the stability, precision and computational complexity.
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