用于移动机器人目标检测和里程计的激光雷达和IMU数据处理

Q4 Engineering
N. Giannoccaro, T. Nishida, A. Lay-Ekuakille, R. Velázquez, Paolo Visconti
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引用次数: 0

摘要

本文介绍了安装在移动机器人上的三维光探测和距离测量(LiDAR)传感器的数据处理,介绍了一种创新的方法来管理数据并提取有用的信息。激光雷达传感器安装在一个移动机器人上,该机器人采用模块化设计,可以轻松改变轮子的数量,设计用于在多种环境中行驶,并通过在每种环境中改变轮子的数量和排列来节省能源。此外,机器人还可以通过对激光雷达获取的每帧图像使用分类技术来识别结构化环境中的地标。在此基础上,结合实验测试,提出了一种基于LiDAR数据处理和惯性数据(IMU传感器)的卡尔曼滤波算法,通过周围环境的固定地标来表征机器人的姿态。最后,分析了所提出算法的局限性,强调了未来发展前景的新改进,即通过简单、模块化和低成本的设备实现自主导航和环境感知。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Processing of LiDAR and IMU Data for Target Detection and Odometry of a Mobile Robot
Abstract In this paper, the processing of the data of a 3D light detection and distance measurement (LiDAR) sensor mounted on a mobile robot is demonstrated, introducing an innovative methodology to manage the data and extract useful information. The LiDAR sensor is placed on a mobile robot which has a modular design that permits the easy change of the number of wheels, was designed to travel through several environments, and saves energy by changing the number and arrangement of the wheels in each environment. In addition, the robot can recognize landmarks in a structured environment by using a classification technique on each frame acquired by the LiDAR. Furthermore, considering the experimental tests, a new simple algorithm based on the LiDAR data processing together with the inertial data (IMU sensor) through a Kalman filter is proposed to characterize the robot’s pose by the surrounding environment with fixed landmarks. Finally, the limits of the proposed algorithm have been analyzed, highlighting new improvements in the future prospective development for permitting autonomous navigation and environment perception with a simple, modular, and low-cost device.
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来源期刊
Journal of Automation, Mobile Robotics and Intelligent Systems
Journal of Automation, Mobile Robotics and Intelligent Systems Engineering-Control and Systems Engineering
CiteScore
1.10
自引率
0.00%
发文量
25
期刊介绍: Fundamentals of automation and robotics Applied automatics Mobile robots control Distributed systems Navigation Mechatronics systems in robotics Sensors and actuators Data transmission Biomechatronics Mobile computing
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