Prof. Zhihong Feng Profile

Prof. Zhihong Feng

at Guangzhou Huali College

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Proceedings Article | 15 October 2021 Paper

Robot path planning based on external parameter calibration and parameter fusion

Zhihong Feng

Proceedings Volume 11933, 1193321 (2021) https://doi.org/10.1117/12.2615743

KEYWORDS: Error analysis, Motion models, Calibration, Motion analysis, Automatic tracking, Visual process modeling, Kinematics, Motion controllers, Statistical modeling, Detection and tracking algorithms

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In order to realize the automatic planning and automatic control of path tracking error of robot with dual-mode rigid body unit hybrid control, an automatic planning method for path tracking error of robot with dual-mode rigid body unit based on external parameter expression parameter calibration and parameter fusion is proposed. The motion parameter distribution model of the hybrid control robot with dual-mode transmission rigid body unit is constructed, the motion information of the hybrid control robot is sampled by adopting the spatial attitude parameter acquisition method of the dual-mode transmission rigid body unit robot, the adaptive area parameter control of the hybrid control robot with dualmode transmission rigid body unit is carried out by combining RBF neural network and external parameter expression calibration algorithm, the kinematics analytical model of the dual-mode rigid-body unit hybrid control robot is established by using the method of 3D vision distributed fusion. The structural parameters of the dual-mode rigid-body unit hybrid control robot are identified by autonomous fusion control of structural parameters and motion parameters, and improved external parameter expression calibration algorithm and attitude parameter fusion method, thus realizing path tracking control and error adjustment of the dual-mode rigid-body unit hybrid control robot and realizing automatic path planning. The test results show that the automatic path tracking error planning of the robot with dual-mode transmission rigid-body unit hybrid control has good adaptability and low proofreading error.

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