Ball Position Estimation in Goal Keeper Robots Using Neural Network

Setiawardhana, Setiawardhana; Dikairono, Rudy; Purwanto, Djoko; Sardjono, Tri Arief

doi:10.15866/ireaco.v13i1.18504

Cited by 6 publications

(4 citation statements)

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“…The neural network architecture used here is a BPNN, which consists of three layers: the input layer, the hidden layer, and the output layer [25], [26]. Those three layers are input 1 2 , hidden layer 3 2 4 , and the output layer 3 2 4 .…”

Section: A Modeling Based On Neural Networkmentioning

confidence: 99%

Design an Intelligent Balanced Control of Quadruped Legs Based on Adaptive Neuro-Fuzzy Inference System (ANFIS)

Wasista¹,

Tjandrasa²,

Djanali³

2023

Int. J. Adv. Sci. Eng. Inf. Technol.

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This study discusses the 12 DoF stability control algorithm for Quadruped robot legs to adjust the balance on irregular terrain. The source of the instability is the irregularity of the ground surface and external forces. Therefore, dynamic stability criteria are needed to plan the robot's movement and restore balance for the movement of a four-legged robot with a dynamic gait over an irregular terrain. The novelty of this study is the use of 12 ANFIS at once to manage the 12 DoF of each leg, which are grouped into four sections, and each section consists of 3 ANFIS. The ANFIS method is used as an algorithm to move the 12-DoF robot legs by training some robot leg movement data based on the slope angle of the surface. The results of training with the ANFIS method can be optimal if the number of rules is close to the given training data. From 29 body tilt angle position data and 12-DOF robot legs, good results will be obtained if the 5x5 number membership function is used for each input which will produce 25 ANFIS rules and combined using the Gaussian type so that it can produce RMSE = 0.068233. The next research is to develop reliable methods such as Zero Moment Point (ZMP) combined with the BPNN or ANFIS methods so that it is expected to get a reliable robot body balance.

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Section: A Modeling Based On Neural Networkmentioning

confidence: 99%

Design an Intelligent Balanced Control of Quadruped Legs Based on Adaptive Neuro-Fuzzy Inference System (ANFIS)

Wasista¹,

Tjandrasa²,

Djanali³

2023

Int. J. Adv. Sci. Eng. Inf. Technol.

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“…This cooperative role assignment game provides optimization for the deployment of robots in the field but still requires additional strategies to win matches. Related research on artificial intelligence has been also carried out for ball position mapping [8] and intelligent navigation [9]. The robot can map and navigate the ball in the goal and this technique has been implemented on the IRIS goalkeeper robot.…”

Section: Introductionmentioning

confidence: 99%

Advance Attack and Defense Strategy Algorithm With Dynamic Role Assignment for Wheeled Soccer Robot

Dikairono

Setiawardhana

Budiman

et al. 2021

kursor

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Game strategy is one of the most critical parts of winning a soccer robot match and cannot be separated from the cooperation among robots in making movements to score goals. In this paper, a wheeled soccer robot game strategy called advance attack and defense has been developed. The strategy is combined with dynamic role assignment, in which robot can change from an attacker to a defender and vice versa. Defender robots are not only based on defensive area but will always block opposing attacker to score goal. The attack strategy performs a rotational trajectory for attacker robot to overpass opponent robot. This strategy has been proven to increase defense and attack effectiveness. Test results using soccer robot gameplay environment simulator developed by Institut Teknologi Sepuluh Nopember Robot with Intelligent System (IRIS) team show that the advance strategies are superior compared with basic strategies. In 30 matches, the advance dynamic strategy won 80%, drew 6.7%, and obtained the highest goal difference, 85 goals. The test was then verified with the implementation in the IRIS robots and showed the same performance. The developed game algorithms were tested in 2019 Indonesian wheeled soccer robot contest (KRSBI-B) and the IRIS team won the title.

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“…There are two competitions in RoboCup for wheeled soccer robot, which are Small-Size League (SSL) and Middle-Size League (MSL). Research on ball position for MSL Goal Keeper robot has been discussed in [2]. Studies on motion controls of SSL soccer robot with four wheeled omnidirectional has been conducted in [3,4].…”

Section: Introductionmentioning

confidence: 99%

CNN-Based Self Localization Using Visual Modelling of a Gyrocompass Line Mark and Omni-Vision Image for a Wheeled Soccer Robot Application

Dikairono¹,

Setiawardhana²,

Purwanto³

et al. 2020

IJIES

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The Convolutional Neural Network (CNN) is an object classification method that has been widely used in recent research. In this paper, we propose CNN for use in the self-localization of wheeled soccer robots on a soccer field. If the soccer field is divided into equally sized quadrants with imaginary vertical and horizontal lines intersecting in the middle of the field, then the soccer field has an identical shape for each quadrant. Every quadrant is a reflection of the other quadrants. Superficially similar images appearing in different positions may result in positioning mistakes. This paper proposes a solution to this problem by using a visual modelling of the gyrocompass line mark and omni-vision image for the CNN-based self-localization system. A gyrocompass is used to obtain the angle of the robot on the soccer field. A 360° omni-vision camera is used to capture images that cover all parts of the soccer field wherever the robot is located. The angle of the robot is added to the omni-vision image using the visual modelling method. The implementation of self-localization without visual modelling gives accuracy rates of 0.3262, and this result is increased to 0.6827 with the proposed methods. The experiment was carried out in the robotics laboratory of the Institut Teknologi Sepuluh Nopember (ITS) with the ITS Robot with Intelligent System (IRIS) robot.

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Ball Position Estimation in Goal Keeper Robots Using Neural Network

Cited by 6 publications

References 0 publications

Design an Intelligent Balanced Control of Quadruped Legs Based on Adaptive Neuro-Fuzzy Inference System (ANFIS)

Design an Intelligent Balanced Control of Quadruped Legs Based on Adaptive Neuro-Fuzzy Inference System (ANFIS)

Advance Attack and Defense Strategy Algorithm With Dynamic Role Assignment for Wheeled Soccer Robot

CNN-Based Self Localization Using Visual Modelling of a Gyrocompass Line Mark and Omni-Vision Image for a Wheeled Soccer Robot Application

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