Online Serial Manipulator Calibration Based on Multisensory Process Via Extended Kalman and Particle Filters

An online robot self-calibration method based on an inertial measurement unit (IMU) and a position sensor is presented in this paper. In this method, a position marker and an IMU are required to be rigidly attached to the robot tool to obtain the position of the manipulator from the position sensor and the orientation of the manipulator from the IMU in real time. An efficient approach that incorporates a Kalman filter (KF) and a particle filter to estimate the position and orientation of the manipulator is proposed in this paper. The use of these pose (orientation and position) estimation methods improves the reliability and accuracy of pose measurements. Finally, an extended KF is used to estimate the kinematic parameter errors. The primary advantage of this method over existing automated self-calibration methods is that it does not involve complex steps, such as camera calibration, corner detection, and laser alignment, which makes the proposed robot calibration procedure more autonomous in a dynamic manufacturing environment. Moreover, the reduction of complex steps improves the accuracy of calibration. Experimental studies on a GOOGOL GRB3016 robot show that the proposed method has better accuracy, convenience, and effectiveness.

[1]  Robert B. McGhee,et al.  A Simplified Quaternion-Based Algorithm for Orientation Estimation From Earth Gravity and Magnetic Field Measurements , 2008, IEEE Transactions on Instrumentation and Measurement.

[2]  Wisama Khalil,et al.  Self calibration of Stewart-Gough parallel robots without extra sensors , 1999, IEEE Trans. Robotics Autom..

[3]  Hanqi Zhuang,et al.  Self-calibration of parallel mechanisms with a case study on Stewart platforms , 1997, IEEE Trans. Robotics Autom..

[4]  In-Won Park,et al.  Laser-Based Kinematic Calibration of Robot Manipulator Using Differential Kinematics , 2012, IEEE/ASME Transactions on Mechatronics.

[5]  Ping Zhang,et al.  Online robot calibration based on vision measurement , 2013 .

[6]  Ronald Lumia,et al.  An Automated Method to Calibrate Industrial Robots Using a Virtual Closed Kinematic Chain , 2007, IEEE Transactions on Robotics.

[7]  C. Rizos,et al.  Improving Adaptive Kalman Estimation in GPS/INS Integration , 2007, Journal of Navigation.

[8]  Shuzi Yang,et al.  Kinematic-Parameter Identification for Serial-Robot Calibration Based on POE Formula , 2010, IEEE Transactions on Robotics.

[9]  R. Paul.  Robot manipulators : mathematics, programming, and control : the computer control of robot manipulators , 1981 .

[10]  Murat Barut,et al.  Real-Time Implementation of Bi Input-Extended Kalman Filter-Based Estimator for Speed-Sensorless Control of Induction Motors , 2012, IEEE Transactions on Industrial Electronics.

[11]  Vinay A. Bavdekar,et al.  Identification of process and measurement noise covariance for state and parameter estimation using extended Kalman filter , 2011 .

[12]  John E. Dennis,et al.  Numerical methods for unconstrained optimization and nonlinear equations , 1983, Prentice Hall series in computational mathematics.

[13]  Philippe Martinet,et al.  Unifying Kinematic Modeling, Identification, and Control of a Gough–Stewart Parallel Robot Into a Vision-Based Framework , 2006, IEEE Transactions on Robotics.

[14]  Abdul Rauf,et al.  Experimental results on kinematic calibration of parallel manipulators using a partial pose measurement device , 2006, IEEE Transactions on Robotics.

[15]  Fei Wang,et al.  Implementation of EKF for Vehicle Velocities Estimation on FPGA , 2013, IEEE Transactions on Industrial Electronics.

[16]  Yoichi Hori,et al.  Estimation of Sideslip and Roll Angles of Electric Vehicles Using Lateral Tire Force Sensors Through RLS and Kalman Filter Approaches , 2013, IEEE Transactions on Industrial Electronics.

[17]  Jinling Wang,et al.  STOCHASTIC MODELING FOR REAL-TIME KINEMATIC GPS/GLONASS POSITIONING. , 1999 .

[18]  James Diebel,et al.  Representing Attitude : Euler Angles , Unit Quaternions , and Rotation Vectors , 2006 .

[19]  Josep M. Guerrero,et al.  Industrial Applications of the Kalman Filter: A Review , 2013, IEEE Transactions on Industrial Electronics.

[20]  Jinchun Hu,et al.  Accuracy- and Simplicity-Oriented Self-Calibration Approach for Two-Dimensional Precision Stages , 2013, IEEE Transactions on Industrial Electronics.

[21]  Nicolas Andreff,et al.  Simplifying the kinematic calibration of parallel mechanisms using vision-based metrology , 2006, IEEE Transactions on Robotics.

[22]  Jessica K. Hodgins,et al.  Automatic Joint Parameter Estimation from Magnetic Motion Capture Data , 2023, Graphics Interface.

[23]  William Melek,et al.  Fastening tool tracking system using a Kalman filter and particle filter combination , 2011 .

[24]  Markus Vincze,et al.  A Laser Tracking System to Measure Position and Orientation of Robot End Effectors Under Motion , 1994, Int. J. Robotics Res..

[25]  Farid Golnaraghi,et al.  A Fastening Tool Tracking System Using an IMU and a Position Sensor With Kalman Filters and a Fuzzy Expert System , 2009, IEEE Transactions on Industrial Electronics.

[26]  John M. Hollerbach,et al.  Autonomous calibration of single-loop closed kinematic chains formed by manipulators with passive endpoint constraints , 1991, IEEE Trans. Robotics Autom..

[27]  Farid Golnaraghi,et al.  A Kalman/Particle Filter-Based Position and Orientation Estimation Method Using a Position Sensor/Inertial Measurement Unit Hybrid System , 2010, IEEE Transactions on Industrial Electronics.

[28]  G. Gatti,et al.  A practical approach to compensate for geometric errors in measuring arms: application to a six-degree-of-freedom kinematic structure , 2007 .

[29]  Jorge Santolaria,et al.  Kinematic parameter estimation technique for calibration and repeatability improvement of articulated arm coordinate measuring machines , 2008 .

[30]  John M. Hollerbach,et al.  Autonomous Robot Calibration for Hand-Eye Coordination , 1991, Int. J. Robotics Res..