Trajectory Optimization of Spherical Parallel Robots Using Artificial Neural Network
Publish place: International Journal of Advanced Design and Manufacturing Technology، Vol: 7، Issue: 1
Publish Year: 1393
نوع سند: مقاله ژورنالی
زبان: English
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شناسه ملی سند علمی:
JR_ADMTL-7-1_012
تاریخ نمایه سازی: 18 اردیبهشت 1400
Abstract:
This article addresses an efficient and novel method for singularity-free path planning and obstacle avoidance of parallel manipulator based on neural networks. A modified ۴-۵-۶-۷ interpolating polynomial is used to plan a trajectory for a spherical parallel manipulator. The polynomial function which is smooth and continuous in displacement, velocity, acceleration and jerk is used to find a path avoiding obstacles and singularities. The polynomial is further modified to plan a trajectory with minimum passing length through the obstacle and singularity, and the best kinematics conditioning index, as well. An artificial neural network is implemented to solve forward kinematics of the manipulator to estimate the distance between gripper and singularity or obstacle in Euler coordinate. Moreover, the simulation results prove the efficiency of the proposed algorithm.
Authors
Reza Alibakhshi
Babol Noshirvani University of Technology