Title: Trajectory-based fast ball detection and tracking for an autonomous industrial robot system

Authors: Youssef M. AbdElKhalek; Mohammed Ibrahim Awad; Hossam E. Abd El Munim; Shady A. Maged

Addresses: School of Electrical Engineering and Computer Science, KTH Royal Institute of Technology, Stockholm, Sweden ' Mechatronics Engineering Department, Faculty of Engineering, Ain Shams University, Cairo, Egypt; Faculty of Engineering, Galala University, Egypt ' Computer and Systems Engineering Department, Faculty of Engineering, Ain Shams University, Cairo, Egypt ' Mechatronics Engineering Department, Faculty of Engineering, Ain Shams University, Cairo, Egypt

Abstract: Autonomising industrial robots is the main goal in this paper; imagine humanoid robots that have several degrees of freedom (DOF) mechanisms as their arms. What if the humanoid's arms could be programmed to be responsive to their surrounding environment, without any hard-coding assigned? This paper presents the idea of an autonomous system, where the system observes the surrounding environment and takes action on its observation. The application here is that of rebuffing an object that is thrown towards a robotic arm's workspace. This application mimics the idea of high dynamic responsiveness of a robot's arm. This paper will present a trajectory generation framework for rebuffing incoming flying objects. The framework bases its assumptions on inputs acquired through image processing and object detection. After extensive testing, it can be said that the proposed framework managed to fulfil the real-time system requirements for this application, with an 80% successful rebuffing rate.

Keywords: object detection; stereo vision; object tracking; ping-pong ball; trajectory prediction; table tennis; real-time; depth image processing; infrared image processing; serial robot.

DOI: 10.1504/IJISTA.2021.119029

International Journal of Intelligent Systems Technologies and Applications, 2021 Vol.20 No.2, pp.126 - 145

Received: 29 Apr 2020
Accepted: 25 Oct 2020
Published online: 18 Nov 2021 *

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