Collision Detection and Trajectory Planning for Palletizing Robots Based OBB

Abstract

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.