Team Description Paper

This team description paper describes the recent developments of Dagozilla's MSL robots. The 2022 Team Description Paper can be found in the link below.

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Putra, C. S., Fahleraz, F., Widyotriatmo, A., & Mutijarsa, K. (2019). Multilayer Control for Coordinating Three - Wheeled Omnidirectional Mobile Robots. 2019 6th International Conference on Instrumentation, Control, and Automation (ICA). Bandung: IEEE.

Operating multiple robots in an environment presents a challenge on how to coordinate each robot to be able to work together while still reaching their maximum performance. To do so, the right control system needs to be designed. On this challenge, we take the RoboCup Middle Size League environment as a case study as it requires both individual robot's performance as well as good coordination to do well in this setting. Our goal is to design a control system that enables the robots to coordinate, avoid obstacles and collisions, as well as performing velocity tracking to control each of the robot's movement. We developed a communication framework using socket.io to manage high-level coordination. While we used an A*-based path generating an algorithm to handle each robot's navigation. To enable velocity tracking, we used a cascade PID algorithm with acceleration feed-forward. The resulting control system can successfully coordinate and navigate each robot safely. The velocity tracking algorithm is also able to successfully achieve a velocity error of about 1.5% and a distance error of about 2%.

Publication Link

Febrianto, E., Priandiri, V. P., & Mutijarsa, K. (2018). Hardware Implementation in Developing Wheeled Soccer Robot for Middle Size League. 2018 International Conference on Information Technology Systems and Innovation (ICITSI). Bandung: IEEE.

The mechanical design of a robot will affect the performance that a robot can provide. In order to reach the maximum limitation on robot performance, the consideration of hardware components must be well implemented. Our robot has 3 bases. The first base is used as locomotion part, the second base for ball handling and kicking mechanism, and the third base is used as the upper body for vision placement. The average error generated by odometry reading of the on the x and y-axes is about 9.764%. The resulting overshoot on the dribbler motor is 24.77% with a maximum error of 0.34697 m/s. We obtained the correlation between the PWM signal and initial velocity of the ball kicked. For the vision system, it has successfully captured almost 360 degrees views of the field and it accurately locates the ball position to the robot itself. The maximum view of this vision system is 6.5 meter.

Publication Link

Hartanto, M. I., & Mutijarsa, K. (2017). Design and Implementation of Behavior-based Coordination System on Soccer Robot. 2017 Internasional Conference on Information Technology System and Innovation. Bandung: IEEE.

Autonomous mobile robot soccer is a very popular field of research. The complexity of robot designs that include perception systems, processing systems, drive systems, inter-subsystem coordination systems, and intelligence in game strategies, make the development of soccer robots even more exciting and challenging. This paper discussed the design results of the coordination system of soccer robot. The coordination system is responsible for integrating information from the perception system into game strategies. Then the game strategy processing generates information to the locomotion system, dribbler, and kicker. The coordination system between subsystems is implemented using behavior-based intelligent systems. This selection is based on intelligent behavior-based system design designed by bottom-up, starting from simple behavior. So it allows researchers to develop it in a sustainable manner. The implementation of this system is using Finite State Machine (FSM) with the help of fuzzy logic as the basis of decision making. This soccer robot coordination system has been implemented on a robot platform named Devara. From the test results in the field in the game, the robot can recognize the ball, move towards the ball, dribble, and kick the ball towards the goal. The average time needed by the robot in the game to find the ball placed in several positions, then dribble and score the goal is 13.2 seconds.

Publication Link

Kusumawardhana, D. B., & Mutijarsa, K. (2017). Object Recognition Using Multidirectional Vision System on Soccer Robot. 2017 International Conference on Information Technology Systems and Innovation . Bandung: IEEE.

An autonomous mobile robot should be equipped by a sensory system for sensing the environment before making any decision. In soccer robots, the sensory system uses cameras as the vision system device to recognise the objects on its working environment. The objects to be considered are the ball, goalpost, and the marks on the field. The vision system of a soccer robot usually has its limitations while capturing object due to the camera specification. This paper discusses a method to recognise object in a better way by using multiple camera for detecting object in different direction and distance. The distant objects can be detected by using a camera which is focused on a straight line, and able to detect capture object in long distance. Otherwise, the close objects can be detected by using a camera which is focused on nearby location, yet able to capture multiple direction in the same time to broaden the ability to detect certain objects. Digital image processing techniques such as image thresholding, Gaussian blur, Canny edge detector and Hough transform are implemented using OpenCV to process image captured by the cameras. The information then forwarded to the robot coordination system to make decision. Testing has been done to prove that the vision system is able to extract information about the objects on the field. Overall, the vision system using cameras is able to extract the information needed by soccer robots to recognise the environment. Integration testing of the whole soccer robot system shows that the robot is able to recognise, approach, then herd and kick the ball toward the goal.

Publication Link

Widodo, F. A., & Mutijarsa, K. (2017). Design and Implementation of Movement, Dribbler, and Kicker for Wheeled Soccer Robot. 2017 International Conference on Information Technology Systems and Innovation . Bandung: IEEE.

The actuator system of soccer robot consists of movement system, dribbler system, and kicker sytem. The whole system of movement, dribbler and kicker on soccer robot successfully built and integrated in soccer robot. Based on the results of the overall robot function test in playing the ball, obtained movement system can perform the movement in accordance with the instructions given with an average error of less than 5%. The dribbling system can keep the ball always in front of the robot and rotate according to the natural motion of the ball. The kicker system can kick the ball with an average distance of 6.15 meters.

Publication Link

Mechanical, Electrical, and Software Description

The mechanical, electrical and software description paper describes the inner workings of the Dagozilla MSL robots. The documents also include mechanical design, electrical drawings and software schemes. The documents can be found in the link below.

Download Mechanical Description Download Electrical & Software Description


List of results and awards obtained by the team in the last 3 years.

  • 2021
    • 4th place in Kontes Robot Indonesia Regional I
    • 3rd place in RoboCup Asia Pacific 2021 category Scientific Challenge
    • 3rd place in RoboCup Asia Pacific 2021 category Video Challenge
  • 2020
    • 4th place in Kontes Robot Indonesia Regional I
  • 2019
    • 4th place in Kontes Robot Indonesia Nasional
    • 1st place in Kontes Robot Indonesia Regional II
    • Best Strategy in Kontes Robot Indonesia Regional II

Qualification Video

The following video showcases the Dagozilla MSL robots abilities in a minute.

List of MAC Address

The following MAC addresses are subject to change.

# Name Type MAC Address
1 Faraday Robot 14:4f:8a:6a:4e:a1
2 Gauss Robot
3 Halliday Robot d0:c5:d3:33:93:a7
4 WiFi Dongle 1 Robot 10:7b:44:e9:64:aa
5 WiFi Dongle 2 Robot 10:7b:44:e9:64:a7
6 WiFi Dongle 3 Robot 10:7b:44:e9:64:ac
7 Kirchhoff Robot b0:68:e6:e1:f1:2b
8 Maxwell Robot 40:23:43:b7:68:af
9 Laplace Robot 7c:c2:c6:1c:b9:66
10 Laptop 1 Development Computer 9c:b6:d0:d8:f4:83
11 Laptop 2 Development Computer b4:d5:bd:b8:eb:e2
12 Emyr Development Computer a4:97:b1:90:cb:f5
13 Sky Development Computer c0:e4:34:72:4e:63

Additional Information

This team would not be a part of a mixed team.
This team requires 802.11b access-point.