Planning Method of Near-Minimum-Time Task Tour for Industrial Point-to-Point Robot

This paper introduces a near-optimal path planning for industrial robot for multiple point tasks. For instance, spot welding, drilling, screwing and inspection with camera are popular multiple point work for industrial robots. How to decide the sequence of robot motions is important issue for factory automation because it directory influences to system productivity. Though getting optimal tour is not easy because this is kind of Traveling Salesman Problem (TSP) that is almost impossible to solve in polynomial time. In TSP the cost between two cities is given by geometrical distance though in robotics time for moving between two task points is gets cost. This article adopts heuristic algorithm that is often used to solve TSP to solve about 50 task points path planning for industrial robot. As a result, the algorithm gives under 1% gap solution against best known solutions. For actual robot tasks, it generates about 6 to 10% efficient results compared with human task planners path.