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

被引：0

作者：

AbdElKhalek Y.M. ^{[1
]}

Awad M.I. ^{[2
,3
]}

Abd El Munim H.E. ^{[4
]}

Maged S.A. ^{[2
]}

机构：

[1] School of Electrical Engineering and Computer Science, KTH Royal Institute of Technology, Stockholm

[2] Mechatronics Engineering Department, Faculty of Engineering, Ain Shams University, Cairo

[3] Faculty of Engineering, Galala University

[4] Computer and Systems Engineering Department, Faculty of Engineering, Ain Shams University, Cairo

来源：

International Journal of Intelligent Systems Technologies and Applications | 2021年 / 20卷 / 02期

关键词：

Depth image processing; Infrared image processing; Object detection; Object tracking; Ping-pong ball; Real-time; Serial robot; Stereo vision; Table tennis; Trajectory prediction;

D O I：

10.1504/IJISTA.2021.119029

中图分类号：

学科分类号：

摘要：

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. Copyright © 2021 Inderscience Enterprises Ltd.

引用

页码：126 / 145

页数：19

共 32 条

[1]

Anderson R.L., A Robot Ping-pong Player: Experiment in Real-time Intelligent Control, (1988)

[2]

Balaji S.R., Karthikeyan S., A survey on moving object tracking using image processing, 2017 11th International Conference on Intelligent Systems and Control (ISCO), pp. 469-474, (2017)

[3]

Billingsley J., Robot ping pong, Pract. Comput, 6, 5, pp. 14-16, (1983)

[4]

Borji A., Cheng M., Hou Q., Et al., Salient object detection: a survey, Comp. Visual Media, 5, 2, pp. 117-150, (2019)

[5]

Chauhan A.K., Krishan P., Moving object tracking using Gaussian mixture model and optical flow, International Journal of Advanced Research in Computer Science and Software Engineering, 3, 4, pp. 243-246, (2013)

[6]

Fujita M., AIBO: toward the era of digital creatures, Int. J. Robot. Res, 20, 10, pp. 781-794, (2001)

[7]

Glover J., Kaelbling L.P., Tracking the spin on a ping pong ball with the quaternion bingham filter, IEEE Conference on Robotics and Automation, (2014)

[8]

He N-n., Du J-p., Study on method for efficient moving object detection in intelligent video surveillance, Journal of Beijing Technology and Business University(Natural Science Edition), 4, 4, pp. 34-37, (2009)

[9]

Herrero S., Bescos J., Background subtraction techniques: systematic evaluation and comparative analysis, Advanced Concepts for Intelligent Vision Systems. ACIVS 2009. Lecture Notes in Computer Science, 5807, (2009)

[10]

Huang Y., Xu D., Tan M., Su H., Trajectory prediction of spinning ball for pingpong player robot, 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 3434-3439, (2011)

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