自主移动机器人的运动规划与控制

To Xuan Dinh, Nguyen Thi Thu Huong, Nguyen Ngoc Tuan, Nguyen Thanh Tien
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引用次数: 0

摘要

自主移动机器人(AMR)具有提高生产效率和降低劳动力成本的优势,其应用已逐渐成为智能工厂的关键。运动规划一直是 AMR 控制开发的关键部分。本文介绍了以燃料电池和电池混合动力为动力的全向轮式 AMR 的运动规划和位置跟踪控制系统。首先,介绍了 AMR 的运动学和动力学模型。导航系统由三个回路组成,第一回路是电机控制,第二回路是位置跟踪控制,还有一个运动规划层。用于反馈控制的 AMR 位置数据是通过将来自惯性测量单元(IMU)传感器、编码器传感器和测距传感器的数据与同步定位和映射(SLAM)算法进行传感器融合而获得的。然后进行运动规划,以获得距离最短、无碰撞的最佳运动路径。此外,还设计了跟踪算法,以驱动 AMR 遵循最优路径并实现高精度。实验结果表明,与传统方法和连续工作 8 小时相比,跟踪精度提高了 30%,在工业应用中大有可为,而且在精度和效率要求方面都取得了令人满意的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Motion planning and control of an autonomous mobile robot
The application of autonomous mobile robots (AMRs) has gradually become crucial in smart factories due to the advantages of improving production efficiency and reducing labour costs. Motion planning has been a key part of AMR control development. This paper presents motion planning and position tracking control systems of an omnidirectional wheel AMR powered by a hybrid fuel cell and battery power source. First, the kinematical and dynamic models of the AMR are introduced. The navigation system comprises three loops, with the first loop being motor control, the second loop being position tracking control, and a motion planning layer. The position data of the AMR for feedback control is obtained through sensor fusion of data from the inertial measurement unit (IMU) sensor, encoder sensor, and ranging sensor with simultaneous localisation and mapping (SLAM) algorithm. The motion planning is then applied to obtain an optimal path with the shortest distance and collision-free movement. In addition, the tracking algorithm is designed to drive the AMR to follow the optimal path and achieve high accuracy. The experimental results show a 30% improvement in tracking accuracy compared to traditional approaches and 8 hours of continuous working, which is promising for industrial applications, and the results are satisfactory in terms of both accuracy and efficiency requirements.
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