A robust optical/inertial data fusion system for motion tracking of the robot manipulator

Chen, Jie; Yang, Canjun; Hofschulte, Jens; Jiang, Wanli; Cha, Zhang

doi:10.1631/jzus.c1300302

Cited by 5 publications

(3 citation statements)

References 16 publications

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“…From the perspective of mechanical kinematics, the upper limb is a multi-degree-of-freedom mechanical motion system with many complex structural joints [16], which should be simplified on the premise of rigid body hypothesis theory when analyzing the upper limb's motion ability. 7DOF model is the most universal model [17], since this model is the closest to the motion function of human upper limbs， which can well describe human motion [8]. In this model, shoulder joint has three degrees of freedom: abduction and adduction, medial rotation and lateral rotation, flexion and extension, elbow joint has one freedom: flexion and extension, wrist joint has three degrees of freedom: dorsal extension and palmar flexion, supination and pronation, abduction and adduction.…”

Section: Upper Limb Kinematics Modelmentioning

confidence: 99%

“…For instance, Chen at al. [8] propose a multi-rigid real-time tracking system based on the upper limb kinematic chain algorithm to achieve shoulder and elbow joint angle measurement, in which Kalman filter is used to improve the system robustness, while the algorithm does not involve the measurement of the wrist joint kinematic parameters. Since wrist joint injury has a great influence on the fine movement of the hand and even the activity of the upper limb [9], it is indispensable to distinguish the degree of wrist joint injury and adopt effective rehabilitation methods in time [10].…”

Section: Introductionmentioning

confidence: 99%

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A Novel Algorithm of Kinematics Parameters Measurement for Upper Limb Based on Motion Capture

2020

IJOMAM

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Joint position and joint angle are the basic kinematic parameters for the quantitative evaluation of upper limb motion ability, which are widely applied to calculate extremity reachable workspace and range of motion (ROM). The traditional measurement methods cannot meet the clinical requirements in accuracy, stability and real-time. This paper proposes a novel algorithm for measuring the kinematic parameters of upper limb by combining the kinematic chain method with the vector projection method. Firstly, the human upper limb motion model is simplified to a 7 degrees of freedom (DOF) motion model according to the anatomical principle, and the rigid body group is used to collect the upper limb kinematic parameters to realize the real-time tracking of trajectory and angle of the shoulder, elbow and wrist joints. Finally, a healthy volunteer experiment is designed, the results show that the algorithm can provide real-time and quantitative upper limb kinematic parameters, which can meet the data requirements of quantitative evaluation of upper limbs.

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Section: Upper Limb Kinematics Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Novel Algorithm of Kinematics Parameters Measurement for Upper Limb Based on Motion Capture

2020

IJOMAM

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“…Wiles et al 6 used the Northern Digital Inc. (NDI) Polaris OTSs to achieve the accuracy pose recognition and avoided cumulative error, but OTS still has its unavoidable problems: marked points lost caused by disturbance and obstruction from other objects and uneven error distribution in the workspace due to the distortion of camera's lens and other configurations of OTS. Chen et al 7 combined OTS with IMU, to compensate for pose tracking with IMU in the case of OTS mark point lost. The performance of the OTS was improved by data fusion with an IMU using a Kalman filter.…”

Section: Introductionmentioning

confidence: 99%

Inertial measurement unit–based iterative pose compensation algorithm for low-cost modular manipulator

Lin

Min

Wei

2016

Advances in Mechanical Engineering

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It is a necessary mean to realize the accurate motion control of the manipulator which uses end-effector pose correction method and compensation method. In this article, first, we established the kinematic model and error model of the modular manipulator (WUST-ARM), and then we discussed the measurement methods and precision of the inertial measurement unit sensor. The inertial measurement unit sensor is mounted on the end-effector of modular manipulator, to get the real-time pose of the end-effector. At last, a new inertial measurement unit-based iterative pose compensation algorithm is proposed. By applying this algorithm in the pose compensation experiment of modular manipulator which is composed of low-cost rotation joints, the results show that the inertial measurement unit can obtain a higher precision when in static state; it will accurately feedback to the control system with an accurate error compensation angle after a brief delay when the end-effector moves to the target point, and after compensation, the precision errors of roll angle, pitch angle, and yaw angle are reached at 0.05°, 0.01°, and 0.27°respectively. It proves that this low-cost method provides a new solution to improve the end-effector pose of low-cost modular manipulator.

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Improved state estimation of a robot end-effector using laser tracker and inertial sensor fusion

Cvitanic

Melkote

Balakirsky

2022

CIRP Journal of Manufacturing Science and Technology

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A robust optical/inertial data fusion system for motion tracking of the robot manipulator

Cited by 5 publications

References 16 publications

A Novel Algorithm of Kinematics Parameters Measurement for Upper Limb Based on Motion Capture

A Novel Algorithm of Kinematics Parameters Measurement for Upper Limb Based on Motion Capture

Inertial measurement unit–based iterative pose compensation algorithm for low-cost modular manipulator

Improved state estimation of a robot end-effector using laser tracker and inertial sensor fusion

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