基于激光雷达360、超声波传感器和轮速编码器数据融合的自主移动机器人设计

S. Premnath, S. Mukund, K. Sivasankaran, R. Sidaarth, S. Adarsh
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引用次数: 9

摘要

如何提高自主移动机器人的导航效率是机器人领域的研究热点。路径规划和避障是自主移动机器人导航的重要方面。这需要高度精确和强大的传感器进行测距和障碍物检测。这些传感器的误差减小可以使用各种统计方法来实现。所提出的误差减小技术利用ANFIS系统来减小超声波传感器和轮速编码器的误差。利用不同的隶属函数对传感器的ANFIS模型进行评估,以寻找具有最佳RMSE的模型。经过训练的超声波传感器和轮速编码器与激光雷达集成,用于制造自主移动机器人。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Design of an Autonomous Mobile Robot based on the Sensor Data Fusion of Lidar 360, Ultrasonic sensor and Wheel Speed Encoder
The research in improving the efficiency of the navigation of autonomous mobile robot is escalating in the field of robotics. Path planning and Obstacle avoidance are important aspects of autonomous mobile robot navigation. This requires highly accurate and robust sensors for ranging and obstacle detection. Error reduction in these sensors can be achieved using various statistical methods. The proposed technique for error reduction utilizes ANFIS system for reducing error in ultrasonic sensor and wheel speed encoder. The ANFIS models for the sensors are evaluated with different membership function for finding the one with the best RMSE. The trained ultrasonic sensor and wheel speed encoder are integrated with LiDAR, used for building an autonomous mobile robot.
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