Making industrial robots smarter with adaptive reasoning and autonomous thinking for real-time tasks in dynamic environments : a case study

Zabalza, Jaime and Fei, Zixiang and Wong, Cuebong and Yan, Yijun and Mineo, Carmelo and Yang, Erfu and Rodden, Tony and Mehnen, Jorn and Pham, Quang-Cuong and Ren, Jinchang (2018) Making industrial robots smarter with adaptive reasoning and autonomous thinking for real-time tasks in dynamic environments : a case study. In: The 9th International Conference on Brain-Inspired Cognitive System​, 2018-07-07 - 2018-07-08, Guangcheng Hotel.

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    Abstract

    In order to extend the abilities of current robots in industrial applications towards more autonomous and flexible manufacturing, this work presents an integrated system comprising real-time sensing, path-planning and control of industrial robots to provide them with adaptive reasoning, autonomous thinking and environment interaction under dynamic and challenging conditions. The developed system consists of an intelligent motion planner for a 6 degrees-of-freedom robotic manipulator, which performs pick-and-place tasks according to an optimized path computed in real-time while avoiding a moving obstacle in the workspace. This moving obstacle is tracked by a sensing strategy based on ma-chine vision, working on the HSV space for color detection in order to deal with changing conditions including non-uniform background, lighting reflections and shadows projection. The proposed machine vision is implemented by an off-board scheme with two low-cost cameras, where the second camera is aimed at solving the problem of vision obstruction when the robot invades the field of view of the main sensor. Real-time performance of the overall system has been experimentally tested, using a KUKA KR90 R3100 robot.