Acceleration of the Collision Detection for the Grasping of Objects by a Robotic Hand
Redha Fourar, Djamel Melaab · International Journal of Control and Automation · 2015
The objective of this work is to propose two new algorithms for collision detection for realtime application.They are applicable to rigid objects enclosed in boxes in order to improve the time of collision detection.The proposed algorithms, called Neuro-SAT and perceptron learning with displacement of the base frame, will be compared with the algorithm Separating Axis Test (SAT) based on the hierarchy of the OBB tree.A grasping operation of an object, with a robotic hand, was executed to test the developed algorithms.The results, of simulation experiments, reveal a great improvement in the time of collision detection.