Earticle

초록

영어

The objective of this work is to propose two new algorithms for collision detection for real-time 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.

목차

Abstract
 1. Introduction
 2. Construction of the Hierarchy of the Bounding Volumes
 3. The OBB Method
 4. Notion of the Separating Axis
 5. Improved of the Detection Collision Time by Changing the Base Frame
 6. Triangle-Triangle Intersection Test
 7. Control of the Manipulator Arms and Fingers
 8. Linearization and Decoupling of the Dynamic Model
 9. Simulation Results of the Collision Detection
 10. Neuro-SAT Algorithm
 11. Implementation of the Algorithms to a Hand and an Object Formed by Triangles
 12. Conclusion
 References

키워드

저자

• Redha Fourar [ Department of Electrical Engineering, Batna University, Algeria ]
• Djamel Melaab [ Department of Electrical Engineering, Batna University, Algeria ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Control and Automation

• 간기

  월간

• pISSN

  2005-4297

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605