Finding the optimal path in a 3D environment with predefined obstacles

Abstract

Robotics has substantially improved people's daily lives, especially industrial production and manufacturing. An offline programming method is proposed for robot's path planning in a 3D environment with obstacles. The purpose of this method is to find the shortest 3D path between two or more points avoiding obstacles. Two types of paths are created: in the first type, the shortest path between the points is created based on their input order; in the second type, the shortest path that connects the input points is formed. It is accomplished by using a hybrid algorithm that combines the ant colony optimisation algorithm with a genetic algorithm called the roulette wheel method. The proposed method takes into consideration the robot's capabilities and the variability of different environments, so that it can be effectively applied to a multitude of cases. The method has been tested and applied to real world industrial robots successfully.