粒子群优化
加速度计
惯性测量装置
校准
计算机科学
过程(计算)
陀螺仪
机器人
实时计算
模拟
人工智能
控制工程
工程类
算法
统计
数学
航空航天工程
操作系统
作者
Richárd Pesti,Peter Šarčević,Dominik Csík,Ákos Odry
标识
DOI:10.1109/saci58269.2023.10158655
摘要
Accelerometers, gyroscopes, and magnetometers, constituting the Inertial Measurement Unit (IMU), are among the most fundamental sensors utilized in localization problems. However, their utilization is a challenging task since the reliability of measurements depends on the precision of the executed calibration method. This paper proposes an industrial robot-based infield calibration process in a numerical optimization aided framework, which does not need turntable nor dedicated expensive laboratory setup. The proposed method utilizes a calibrated industrial robotic arm, which is programmed to execute wide variety of motions with comprehensive dynamical ranges. The end effector of the robotic arm is equipped with IMUs with predefined installation errors. The proposed calibration process records the ground truth accelerations and raw IMU data in a database in Robot Operating System (ROS) framework. Then, realistic sensor models are established, and the Particle Swarm optimization (PSO) algorithm is executed with a custom fitness function to obtain the between sensor misalignment and bias errors. The comprehensive analysis highlights that the proposed method effectively determines the calibration parameters. Mean squared error (MSE) performance metrics shows that the precision of these parameters mainly depends on the complexity of the executed dynamical motions.
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