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Development of an Effective Docking System for Modular Mobile Self-Reconfigurable Robots Using Extended Kalman Filter and Particle Filter

机译:使用扩展卡尔曼滤波器和粒子滤波器的模块化移动自重构机器人有效对接系统的开发

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This paper presents an autonomous docking system with novel integrated algorithms for mobile self-reconfigurable robots equipped with inexpensive sensors. A novel docking algorithm was developed to determine the initial distance and orientation of the two modules, and sensor models were established through experiments. Both Extended Kalman filter (EKF) and particle filter (PF) were deployed to fuse the measurements from IR and encoders and provide accurate estimates of orientation and distance. Simulation experiments were carried out first and then real experiments were conducted to verify the feasibility and good performance of the proposed docking algorithm and system. The proposed system provides a robust and reliable docking solution using low cost sensors.
机译:本文提出了一种具有新型集成算法的自治对接系统,用于配备有廉价传感器的移动自重配置机器人。开发了一种新颖的对接算法来确定两个模块的初始距离和方向,并通过实验建立了传感器模型。扩展卡尔曼滤波器(EKF)和粒子滤波器(PF)均被部署来融合红外和编码器的测量结果,并提供方向和距离的准确估计。首先进行了仿真实验,然后进行了实际实验,以验证所提出的对接算法和系统的可行性和良好的性能。所提出的系统使用低成本传感器提供了鲁棒且可靠的对接解决方案。

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