GA‐based camera calibration for vision‐assisted robotic assembly system
Vision sensors are employed in robotic assembly system to sense the dynamic environment and to position the manipulator precisely based on the sensor feedback. This process is termed as visual servoing. Precise calibration of the camera and camera/robot system are required to estimate the desired ve...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2017-02-01
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| Series: | IET Computer Vision |
| Subjects: | |
| Online Access: | https://doi.org/10.1049/iet-cvi.2016.0004 |
| _version_ | 1797685068434505728 |
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| author | Nagarajan Pitchandi Saravana Perumaal Subramanian |
| author_facet | Nagarajan Pitchandi Saravana Perumaal Subramanian |
| author_sort | Nagarajan Pitchandi |
| collection | DOAJ |
| description | Vision sensors are employed in robotic assembly system to sense the dynamic environment and to position the manipulator precisely based on the sensor feedback. This process is termed as visual servoing. Precise calibration of the camera and camera/robot system are required to estimate the desired velocity of the robot and accurate positioning of the mating parts. In position‐based visual servoing, roughly calibrated camera leads to errors in robot/camera pose identification that affects the positional accuracy and time to reach the target position. A camera calibration procedure based on genetic algorithm (GA) is proposed in this study to estimate the intrinsic and extrinsic parameters of the camera model for improving positional accuracy and faster convergence. The proposed algorithm is implemented with two‐stage procedure and it comprises: determination of the camera parameters for distortion‐less model and reduction of re‐projection error through GA with linearly determined camera distortion‐less parameters as an initial solution. The proposed camera calibration algorithm has been tested and compared with the dataset images in the literature for its performance in terms of measurement accuracy. The result shows that the proposed algorithm has the capability to calibrate the distorted images with minimum re‐projection error using single image. |
| first_indexed | 2024-03-12T00:38:59Z |
| format | Article |
| id | doaj.art-44cb1a0b132e44718fe5848e44bf1820 |
| institution | Directory Open Access Journal |
| issn | 1751-9632 1751-9640 |
| language | English |
| last_indexed | 2024-03-12T00:38:59Z |
| publishDate | 2017-02-01 |
| publisher | Wiley |
| record_format | Article |
| series | IET Computer Vision |
| spelling | doaj.art-44cb1a0b132e44718fe5848e44bf18202023-09-15T09:02:20ZengWileyIET Computer Vision1751-96321751-96402017-02-01111505910.1049/iet-cvi.2016.0004GA‐based camera calibration for vision‐assisted robotic assembly systemNagarajan Pitchandi0Saravana Perumaal Subramanian1Department of Mechanical EngineeringThiagarajar College of EngineeringMaduraiIndiaDepartment of Mechanical EngineeringThiagarajar College of EngineeringMaduraiIndiaVision sensors are employed in robotic assembly system to sense the dynamic environment and to position the manipulator precisely based on the sensor feedback. This process is termed as visual servoing. Precise calibration of the camera and camera/robot system are required to estimate the desired velocity of the robot and accurate positioning of the mating parts. In position‐based visual servoing, roughly calibrated camera leads to errors in robot/camera pose identification that affects the positional accuracy and time to reach the target position. A camera calibration procedure based on genetic algorithm (GA) is proposed in this study to estimate the intrinsic and extrinsic parameters of the camera model for improving positional accuracy and faster convergence. The proposed algorithm is implemented with two‐stage procedure and it comprises: determination of the camera parameters for distortion‐less model and reduction of re‐projection error through GA with linearly determined camera distortion‐less parameters as an initial solution. The proposed camera calibration algorithm has been tested and compared with the dataset images in the literature for its performance in terms of measurement accuracy. The result shows that the proposed algorithm has the capability to calibrate the distorted images with minimum re‐projection error using single image.https://doi.org/10.1049/iet-cvi.2016.0004image distortioncamera distortionless parameterreprojection error reductionparameter estimationgenetic algorithmrobot-camera pose identification |
| spellingShingle | Nagarajan Pitchandi Saravana Perumaal Subramanian GA‐based camera calibration for vision‐assisted robotic assembly system IET Computer Vision image distortion camera distortionless parameter reprojection error reduction parameter estimation genetic algorithm robot-camera pose identification |
| title | GA‐based camera calibration for vision‐assisted robotic assembly system |
| title_full | GA‐based camera calibration for vision‐assisted robotic assembly system |
| title_fullStr | GA‐based camera calibration for vision‐assisted robotic assembly system |
| title_full_unstemmed | GA‐based camera calibration for vision‐assisted robotic assembly system |
| title_short | GA‐based camera calibration for vision‐assisted robotic assembly system |
| title_sort | ga based camera calibration for vision assisted robotic assembly system |
| topic | image distortion camera distortionless parameter reprojection error reduction parameter estimation genetic algorithm robot-camera pose identification |
| url | https://doi.org/10.1049/iet-cvi.2016.0004 |
| work_keys_str_mv | AT nagarajanpitchandi gabasedcameracalibrationforvisionassistedroboticassemblysystem AT saravanaperumaalsubramanian gabasedcameracalibrationforvisionassistedroboticassemblysystem |