
This paper presents a scheme based on Adaptive Neuro-Fuzzy Inference Systems (ANFIS) to generate trajectory for excavator arm. Firstly, the trajectory is predesigned with some specific points in the work space to meet the requirements about the shape. Next, the inverse kinematic is used and optimization problems are solved to generate the via-points in the joint space. These via-points are used as training set for ANFIS to synthesis the smooth curve. In this scheme, the outcome trajectory satisfies the requirements about both shape and optimization problems. Moreover, the algorithm is simple in calculation as the numbers of via-points are large. Finally, the simulation is done for two cases to test the effect of ANFIS structure on the generated trajectory. The simulation results demonstrate that, by using suitable structure of ANFIS, the proposed scheme can build the smooth trajectory which has the good matching with desired trajectory even that the desired trajectory has the complicated shape.
Artificial intelligence, Kinematics, Path Planning, Astronomy, Kinematic and Dynamic Analysis of Robot Manipulators, Trajectory, FOS: Mechanical engineering, Set (abstract data type), Control (management), Hydraulic Systems Control and Optimization, Adaptive neuro fuzzy inference system, Sampling-Based Motion Planning Algorithms, Mathematical analysis, Engineering, TJ1-1570, Control theory (sociology), FOS: Mathematics, Mechanical engineering and machinery, Classical mechanics, Scheme (mathematics), Inference system, Mechanical Engineering, Physics, Mathematical optimization, Path (computing), Adaptive, Computer science, Mechanical engineering, Optimal Motion Planning, Programming language, Fuzzy logic, Trajectory Planning, Trajectory optimization, Fuzzy control system, Control and Systems Engineering, Computer Science, Physical Sciences, Computer Vision and Pattern Recognition, Excavator, Mathematics
Artificial intelligence, Kinematics, Path Planning, Astronomy, Kinematic and Dynamic Analysis of Robot Manipulators, Trajectory, FOS: Mechanical engineering, Set (abstract data type), Control (management), Hydraulic Systems Control and Optimization, Adaptive neuro fuzzy inference system, Sampling-Based Motion Planning Algorithms, Mathematical analysis, Engineering, TJ1-1570, Control theory (sociology), FOS: Mathematics, Mechanical engineering and machinery, Classical mechanics, Scheme (mathematics), Inference system, Mechanical Engineering, Physics, Mathematical optimization, Path (computing), Adaptive, Computer science, Mechanical engineering, Optimal Motion Planning, Programming language, Fuzzy logic, Trajectory Planning, Trajectory optimization, Fuzzy control system, Control and Systems Engineering, Computer Science, Physical Sciences, Computer Vision and Pattern Recognition, Excavator, Mathematics
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