Lo, Sheung-LaiSheung-LaiLoProf. LEUNG Kwong SakLeung, YeeYeeLeung2023-02-202023-02-2020212021 6th International Conference on Control and Robotics Engineering (ICCRE), 2021, pp. 91-95http://hdl.handle.net/20.500.11861/7394A multiple sensors platform is a commonly-used method for robotic application which can capture different types of environmental data. However, the calibration process through finding the geometric relationships is needed in order to integrate different sensors' data together in the same coordination system representation. In this study, we proposed and implemented a simple and yet accurate calibration method for estimating the extrinsic parameters in a transformation matrix representation between more than one sensor with 3D Point-Cloud data. Our calibration method uses both Kinect and LiDAR Point-Cloud scans based on a cuboid as a calibration object, which obtains efficient information with high-level feature points. Such extrinsic parameters can be distinguished with a single shot of capturing the Point-Cloud frame. To verify whether or not our method is practical in a real-life scenario, we evaluated the method and obtained the data using a homemade robot. With our proposed calibration methods, it enables a possibility to exchange the data between LiDAR and Kinect simply and robustly.enLight Detection and RangingCalibration MethodTransformation Matrix3D DataCalibration ProcessGeometric RelationshipPoint Cloud DataExtrinsic Parameters3D Point Cloud DataField of ViewLaser ScanningClustering AlgorithmEstimation ResultsHuman BoneSensor DataObject SizeCoordinate SpaceObject TrackingSensor CalibrationRGB CameraIterative Closest Point AlgorithmIterative Closest PointKinect SensorRobot Operating SystemAverage Error RateRobot SensorsSensor PlatformObjective ViewPeer Reviewed Journal Article10.1109/ICCRE51898.2021.9435662