Kinematic Self-Calibration Method for Dual-Manipulators Based on Optical Axis Constraint

Zhu, Qidan; Xie, Xinru; Li, Chao; Xia, Guihua; Liu, Qi

doi:10.1109/access.2018.2890123

Cited by 28 publications

(11 citation statements)

References 34 publications

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“…Q i is a 4×m matrix that contains the transformed spatial coordinates of the ith group of point clouds. It can be represented as (20) where, X represents the constant homogeneous transformation matrix from {E 1 } to {S}. Y is the constant homogeneous transformation matrix from {O 1 } to {O 2 }.…”

Section: Cutting Scheme Of Sheep Carcassmentioning

confidence: 99%

“…There are 25 groups of 3D point clouds in {S}. The 3D model of the sheep carcass in {O 2 } is obtained after the spatial coordinates transformation of point clouds has been completed according to Equation (20). Figure 14 shows the different views of the 3D model of the sheep carcass.…”

Section: D Modeling Experiments Of Sheep Carcassmentioning

confidence: 99%

“…The calibration of a dual-robot system mainly involves flange-sensor, base-base, and flange-tool transformation matrices calibrations. Qiao et al [18] , Zhao et al [19] , Zhu et al [20,21] , Wang et al [22] researched the calibration problem of a dual-robot system using step-by-step calibration methods. To reduce the calibration errors in step-by-step calibration methods.…”

Section: Introduction mentioning

confidence: 99%

See 2 more Smart Citations

Cutting of sheep carcass using 3D point cloud with dual-robot system

Bao

Leng

Mao

et al. 2022

International Journal of Agricultural and Biological Engineering

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The precise and automatic cutting of sheep carcasses can improve the quality of mutton. Robots are widely used in meat processing because of their good repeatability and high precision. Two essential problems encountered in robot working of sheep carcass processing are robot calibration and cutting trajectory planning. A method of cutting sheep carcasses based on 3D point clouds with a dual-robot system was proposed in this study. The dual-robot system consists of a 3D scanning system, a fixing device for sheep carcasses, and a cutting robot. The calibration of the dual-robot system was completed by solving the matrix problem AXB=YCZ using the iterative method and the closed-form method. The 3D model of a sheep carcass was constructed using a 3D scanner. The cutting scheme of the cutting robot was planned based on the processed 3D point clouds. To show the feasibility of the proposed sheep carcass processing scheme, practical experiments were carried out. The results of the experiments show that the cutting robot can accurately perform the cutting actions according to the planned cutting scheme. The system proposed in this study can improve the efficiency and precision of sheep carcass cutting.

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Section: Cutting Scheme Of Sheep Carcassmentioning

confidence: 99%

Section: D Modeling Experiments Of Sheep Carcassmentioning

confidence: 99%

Section: Introduction mentioning

confidence: 99%

See 1 more Smart Citation

Cutting of sheep carcass using 3D point cloud with dual-robot system

Bao

Leng

Mao

et al. 2022

International Journal of Agricultural and Biological Engineering

View full text Add to dashboard Cite

show abstract

“…The vision-based on-line calibration method in [10] was utilized to calibrate the robot itself kinematics parameters and the hand-eye relationship simultaneously in a robot-based inspecting system. An effective kinematic self-calibration method for dual-manipulators is presented to estimate the actual kinematic parameters in [27]. The on-line self-calibration approaches mentioned significantly improve the efficiency and accuracy of calibration, but the calibrated objects are still fixed-base robots rather than the AIMM with a mobile platform.…”

Section: Related Workmentioning

confidence: 99%

On-Line Precision Calibration of Mobile Manipulators Based on the Multi-Level Measurement Strategy

et al. 2021

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Autonomous industrial mobile manipulator (AIMM), which is composed of a mobile platform and a robot arm of six degrees of freedom (DoFs), can move autonomously and perform dexterous tasks independently in the industrial environment. A novel on-line calibration system for AIMM in real manufacturing workshop is proposed in this paper. Compared to calibration scenarios of fixed-base robot, we focus on the large-space autonomous calibration for AIMM. To cope with the issue of high precision calibration in large space, we propose a multi-level guided-based measurement strategy, which includes the low-cost vision positioning and guidance system, and the high-precision distributed base station (BS) measurement system. The corresponding experiment proves that the total uncertainty of measurement system is less than 0.1 mm. Based on the measured data of end-effector installed at the end of robot arm, the AIMM can perform on-line calibration tasks anywhere automatically without taking into account the expensive devices for the high-precision location of mobile platform and the downtime for the robotic off-line calibration. The mean positioning error of AIMM after calibration reduces 93% based on the calibration experiment.

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“…The online calibration firstly builds the error model. One or more sensors, such as the inertial measurement unit [9], position mark [10] and camera [11][12], are adopted to collect the pose of moving platform in real time. After identifying the errors, the actuation joints are designed to adjust the values autonomously [13].…”

Section: Introductionmentioning

confidence: 99%

An Error Identification and Compensation Method of a 6-DoF Parallel Kinematic Machine

Lian

Li³

et al. 2020

IEEE Access

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Kinematic Calibration is an effective and economical way to improve the accuracy of the six degreeof-freedom (DoF) parallel kinematic machine (PKM), named as Stewart platform, for the large component assembly in aviation or aerospace. The conventional online calibration requires a powerful and complicated control system, whereas the current offline calibration methods are not satisfactory in terms of the compromise between efficiency and accuracy. This paper proposes a semi-online calibration method in which the geometric errors are identified offline and compensated online. The geometric errors are inserted into the inverse kinematic model. Instead of formulating the linear mapping model between geometric errors and the pose error of moving platform, the error model is written as the function of geometric errors with respect to the actuation inputs. Hence, a nonlinear error model is obtained. Without worrying about the identifiability, the error identification equations are converted into an optimization problem and solved by the hybrid genetic algorithm (HGA). In the traditional offline compensation, the identified kinematic parameters are adopted to modify the nominal kinematic model, which is inconvenient when the control system is not transparent to the users. A new control block that calculating the equivalent actuation inputs from the identified errors is added to the control flow. The errors are compensated in an efficient manner. Simulations and experiments are implemented to validate the accuracy, efficiency and convenience of the proposed method. The results indicates that our approach improves position and orientation accuracy of the Stewart platform by 85.1% and 91.0%.

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Kinematic Self-Calibration Method for Dual-Manipulators Based on Optical Axis Constraint

Cited by 28 publications

References 34 publications

Cutting of sheep carcass using 3D point cloud with dual-robot system

Cutting of sheep carcass using 3D point cloud with dual-robot system

On-Line Precision Calibration of Mobile Manipulators Based on the Multi-Level Measurement Strategy

An Error Identification and Compensation Method of a 6-DoF Parallel Kinematic Machine

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