AALHASAN ALI JOODI

@atu.edu.iq

Technical Institute of Samawa
Al-Furat Al-Awsat Technical University



                    

https://researchid.co/ali83

RESEARCH, TEACHING, or OTHER INTERESTS

Mechanical Engineering, Automotive Engineering, Mechanical Engineering

4

Scopus Publications

Scopus Publications


  • Enhancing Motion Planning for Industrial Robots Using Hybrid Methods and Quaternion Representation
    Ali Joodi Aalhasan and Bao Song
    Societatea Română de Automatică și Informatică Tehnică

  • Collision-Free Algorithm for Industrial Robots Based GJK and OBB Theories
    Ali Joodi Aalhasan and Song Bao
    Springer Nature Singapore

  • Collision detection and trajectory planning for palletizing robots based OBB
    Ali Joodi Jasim Aalhasan, Tang XiaoQi, and Song Bao
    Institute of Advanced Engineering and Science
    This paper proposes an algorithm for Collision detection between two convex polyhedra (Boxes). It is assumed that the Palletizing robot’s end effector grasped the Box in accurate incremental method, by compare  the distances between objects in same space . The detections proposed by ignorance of time consumption, and make comparisons between performances of theories discussed this problem, like Axes Aligned Bounded Boxes (AABB) and Sphere theories. Oriented Bounded Boxes (OBB) theory is chosen because unspecified orientation of objects which meets the requirements for detecting collisions with accuracy and handling transformations. Transformation assumptions are based on Z-Y-Z Euler’s angles representation. The key factor for detecting collision between two OBB convex polyhedra is the Separating Axes Theorem (SAT). The trajectory algorithm presents incremental distance computation by implementing translation and spherical trajectory. The checking and simulations in C++ language and Auto CAD software, attests that implementations in both show accuracy results.

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