شماره ركورد كنفرانس :
3222
عنوان مقاله :
A Neural Network Approach for Optimal Grasp Planning
پديدآورندگان :
Mesgari Hamed Advanced Robotics & Automated Systems (ARAS) Laboratory Dept. of Mechanical Eng - K. N. Toosi Univ. of Tech , Cheraghpour Samavati Farzad Advanced Robotics & Automated Systems (ARAS) Laboratory Dept. of Mechanical Eng - K. N. Toosi Univ. of Tech , Eddin Shoori Jazeh Hesam Advanced Robotics & Automated Systems (ARAS) Laboratory Dept. of Mechanical Eng - K. N. Toosi Univ. of Tech , A. Moosavian Ali Advanced Robotics & Automated Systems (ARAS) Laboratory Dept. of Mechanical Eng - K. N. Toosi Univ. of Tech
كليدواژه :
Grasp planning , Optimization , object manipulation , neural networks , MSC. ADAMS , MATLAB Co-simulation
عنوان كنفرانس :
دومين كنفرانس بين المللي كنترل، ابزار دقيق و اتوماسيون
چكيده لاتين :
In this paper, the Neural Network (NN) Approach is used to find the best point on the object, for executing object
manipulation task by a manipulator. The MAG performance index is calculated for some sample points of objects
heuristically by MSC.ADAMS and MATLAB co-simulation for the 6DOF Stäubli© TX40 arm. These samples then would be
used to train a feed-forward back propagation neural networks. The result is the dynamics model of the robot and the
grasped object in which the MAG performance index value is the input and the position of the best grasping point of the
objects which maximizes the MAG index is the output
