The excavator robot need to track bucket goal and its attitude real-time and dynamically during it’s autonomous mining. On the basis of analyzing basic action of mining operations, collected sequence image of mining process of bucket. To reduce the effect of light environment to image processing, use the target tracking method based on color characteristics to recognize color mark block. The bucket attitude angle can be recognized according to the mark of angle attitude of bucket; the bucket target can be recognized according to the mark block of bucket target. Due to sheltered phenomenon, use stripe color block to recognize bucket target while mining process. The color mark block resolve the target tracking problem for bucket, but also fussing the information of pressure sensor of bucket, thus establishing the foundation for subsequent realization based on behavior of autonomous mining.
To improve the trajectory planning control accuracy of the working device of excavator robot when working for excavation, reduce working device of excavator robot to be the two joints two dimension robot arm composed of arm and bucket when analyses. Creating inverse kinematics model, need to relate to terminal position and orientation space of bucket and joint space and cylinder space of working devices to plan trace, so that to control excavator robot in each space. Because of the geometry complexity of inverse kinematics, the nonlinear of electro-hydraulic system, the uncertainty and non-uniqueness for inverse mapping, lead to the difficulty of trajectory planning. To improve the precision for tracking desired trace, obtaining inverse kinematics mapping between terminal trace and joint angle, use two adaptive neural-fuzzy inference system(ANFIS) to learn inverse mapping relations between (x, y) two joint coordinate and joint angle, create ANFIS inverse mapping model. Select I/O curve data of inverse mapping to train ANFIS structure, obtain I/O mapping curve of fuzzy model, realize the aim of obtaining corresponding joint angle based on given desired excavation trace. Use the model to trace expected motion trace finally, indicate by simulation that trace precision can meet the actual demands.
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