B. L. Widjiantoro, K. Indriawati, T. S. N. Alexander Buyung, Kadek Dwi Wahyuadnyana
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引用次数: 0
摘要
本研究通过使用扩展卡尔曼滤波器整合 MPU6050 传感器和编码器数据的实验,验证了 EKF-SLAM 在室内自动驾驶汽车中的应用。实际测试表明,EKF-SLAM 在 X 轴和 Y 轴上的误差仅为 1%和 3%,达到了很高的精度。RPLiDAR A1M8 用于测绘,通过 RViz-ROS 生成可视化的精确地图。这项研究证明了 EKF-SLAM 在实际应用场景中的新颖性和实用性,展示了前所未有的有效性和精确性。
Experimental Validation: Perception and Localization Systems for Autonomous Vehicles using the Extended Kalman Filter Algorithm
This study validates EKF-SLAM for indoor autonomous vehicles by experimentally integrating the MPU6050 sensor and encoder data using an extended Kalman filter. Real-world tests show significant improvements, achieving high accuracy with just 1% and 3% errors in the X and Y axes. RPLiDAR A1M8 is utilized for mapping, producing accurate maps visualized through RViz-ROS. The research demonstrates the novelty and practical utility of EKF-SLAM in real-world scenarios, showcasing unprecedented effectiveness and precision.
期刊介绍:
nternational Journal on Smart Sensing and Intelligent Systems (S2IS) is a rapid and high-quality international forum wherein academics, researchers and practitioners may publish their high-quality, original, and state-of-the-art papers describing theoretical aspects, system architectures, analysis and design techniques, and implementation experiences in intelligent sensing technologies. The journal publishes articles reporting substantive results on a wide range of smart sensing approaches applied to variety of domain problems, including but not limited to: Ambient Intelligence and Smart Environment Analysis, Evaluation, and Test of Smart Sensors Intelligent Management of Sensors Fundamentals of Smart Sensing Principles and Mechanisms Materials and its Applications for Smart Sensors Smart Sensing Applications, Hardware, Software, Systems, and Technologies Smart Sensors in Multidisciplinary Domains and Problems Smart Sensors in Science and Engineering Smart Sensors in Social Science and Humanity