Ball tracking and goal detection for middle size soccer robot using omnidirectional camera

Author(s):  
Anton Kurniawan Mulya ◽  
Fernando Ardilla ◽  
Dadet Pramadihanto
Jurnal INFORM ◽  
2020 ◽  
Vol 5 (2) ◽  
pp. 86-91
Author(s):  
Mochamad Mobed Bachtiar ◽  
Iwan Kurnianto Wibowo ◽  
Rakasiwi Bangun Hamarsudi

The ERSOW robot is a soccer robot developed by Politeknik Elektronika Negeri Surabaya, Indonesia. One important ability of a soccer robot is the ability to find the goal in the field. Goal Post is often used as a sign by soccer robots in a match. The mark is a reference robot in the field to be used in determining the strategy. By knowing the location of the goal in a field, the soccer robot can make the decision to maneuver in the match to get the right goal kick. There are various methods of detecting goal. One of them is to detect goal post using vision. In this study the radial search lines method is used to detect the goalposts as markers. Image input is generated from an omnidirectional camera. The goal area that is detected is the front side of the goal area. With experiments from 10 robot position points in the field, only 1 position point cannot detect the goal. The robot cannot detect the goal because what is seen from the camera is the side of the goal, so the front side of the goal area is not visible.Keywords— omnidirectional camera, vision, radial search lines, goal detection, ersow soccer robot


2020 ◽  
Author(s):  
Winarno ◽  
Ali Suryaperdana Agoes ◽  
Eva Inaiyah Agustin ◽  
Deny Arifianto

Jurnal INFORM ◽  
2020 ◽  
Vol 5 (2) ◽  
pp. 86
Author(s):  
Mochamad Mobed Bachtiar ◽  
Iwan Kurnianto Wibowo ◽  
Rakasiwi Bangun Hamarsudi

The ERSOW robot is a soccer robot developed by Politeknik Elektronika Negeri Surabaya, Indonesia. One important ability of a soccer robot is the ability to find the goal in the field. Goal Post is often used as a sign by soccer robots in a match. The mark is a reference robot in the field to be used in determining the strategy. By knowing the location of the goal in a field, the soccer robot can decide to maneuver in the match to get the right goal kick. There are various methods of detecting goals. One of them is to detect goal posts using vision. In this study, the radial search lines method is used to detect the goalposts as markers. Image input is generated from an omnidirectional camera. The goal area is detected on the front side of the goal area. With experiments from 10 robot position points in the field, only 1 position point cannot detect the goal. The robot cannot detect the goal because what is seen from the camera is the side of the goal, so the front side of the goal area is not visible.


2018 ◽  
Vol 62 (3) ◽  
pp. 304011-3040111 ◽  
Author(s):  
Shih-An Li ◽  
Hsuan-Ming Feng ◽  
Sheng-Po Huang ◽  
Chen-You Chu

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Blake W. Saurels ◽  
Wiremu Hohaia ◽  
Kielan Yarrow ◽  
Alan Johnston ◽  
Derek H. Arnold

AbstractPrediction is a core function of the human visual system. Contemporary research suggests the brain builds predictive internal models of the world to facilitate interactions with our dynamic environment. Here, we wanted to examine the behavioural and neurological consequences of disrupting a core property of peoples’ internal models, using naturalistic stimuli. We had people view videos of basketball and asked them to track the moving ball and predict jump shot outcomes, all while we recorded eye movements and brain activity. To disrupt people’s predictive internal models, we inverted footage on half the trials, so dynamics were inconsistent with how movements should be shaped by gravity. When viewing upright videos people were better at predicting shot outcomes, at tracking the ball position, and they had enhanced alpha-band oscillatory activity in occipital brain regions. The advantage for predicting upright shot outcomes scaled with improvements in ball tracking and occipital alpha-band activity. Occipital alpha-band activity has been linked to selective attention and spatially-mapped inhibitions of visual brain activity. We propose that when people have a more accurate predictive model of the environment, they can more easily parse what is relevant, allowing them to better target irrelevant positions for suppression—resulting in both better predictive performance and in neural markers of inhibited information processing.


2021 ◽  
Vol 1952 (4) ◽  
pp. 042100
Author(s):  
Jinhua Du ◽  
Shuang Li ◽  
Hang Wang ◽  
Zhaoming Sun ◽  
Gang Du

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