KIKS 2014 Team Description Paper
Soya Okuda, Kosuke Matsuoka, Tetsuya Sano, Yu Yamauchi,
Hayato Yokota, Masato Watanabe and Toko Sugiura
Toyota National College of Technology,
Department of Electrical and Electronic engineering,
2-1 Eisei-cho, Toyota Aichi, 471-8525, Japansugi@toyota-ct.ac.jp
URL: http://www.ee.toyota-ct.ac.jp/~sugi/RoboCup.html

Abstract. This paper is used to qualify as participation to the RoboCup 2014
small size league about team "KIKS". Our robots and systems are designed under
the RoboCup 2014 rules in order to participate in the competition. The major improvements in this year are enhancements about the performance and robustnessof wheels, electrical circuit and motion control system. The overviews of them aredescribed.
Keywords: RoboCup, small-size league, engineering education, global vision

1.

Introduction

In last year, we made new robots to obtain better performance. But there weresome problems for running stability, ring-wheels and electronic circuits etc. of therobots. So we checked them this year, and redesigned for some term mentioned above.
In addition we also improved motion control method to obtain better acceleration
performance with only little skid. The main topics of development for robot in 2014
model are following terms,
・Improvement of the small ring wheels
・Improvement of the electric circuit
・Improvement of the motion controller on the AI system

2.

Hardware of the robot

The main configuration for hardware is basically same with the 2013 one. The
wheel was tried to improve for a stable travelling performance. In 2014 model, wealso use the brushless motors (maxon EC45 flat) as the driving motor, like manyteams. For the dribbling device, we use the brushless motor (maxon EC-max22)
again. Each robot has three solenoids. One is for straight kick and the other two arefor chip kick. The robot is able to shoot the ball at a speed of over 10[m/s], however,
it is down to 8[m/s] to keep to the regulations. The height and maximum projection on

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the ground for the robot is 148[mm] and 178[mm], respectively. And the maximum
percentage of ball coverage is 18%. The specification of the robot is summarized inTable 1.
Table 1. Specification of robot for 2014 model

WeightMain material
Driving motor
Gear ratio
Wheel diameter
Number of solenoids
Straight kick power
Chip kick power2014 version
2.3kg
Aluminum alloy
maxon EC45flat (30watt)
3.6 : 156mm
Straight kick: 1
Chip kick: 2Ball speed of 8[m/s]
Max 3.0m away from robot under the condition of initial angle 40°

2.1 Travelling performance of the wheel
Since 2011 competition, we have used the brushless motors as same as many teams
do. But, there was a problem in previous wheel for performance of straight-runningstability of the robot. That is, our robots were not able to run straight stably under thecondition of max speed of 2ms-1 and acceleration of 3ms-2. Figure 1 shows the presentwheel.

Fig. 1 Present wheel
The new small tire is constructed with wider urethane material, metal pin andwashers as shown in Fig. 2. A previous wire shaft connected with all small one ischanged into each metal pin in new wheel. By using of two washers in small wheel’s
house the friction of small tire is decreased drastically. The urethane tire with crosssection of rectangular is effective to enhance the friction between wheel and playing
field. As the results of wider width of small tire and more precise approximate ciradfa, p. 2, 2014.
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cumference in new wheel, the robot can run smoothly and turn quickly. In addition,
the resin material as outside shell for wheel is easy for cutting work, and is effective
for realization of high-speed rotation due to its light weight.
urethane material

coreless pipe
washersmall pin

Fig. 2 Component of small tire on wheel
It was manufactured new-type wheels in last year. But, the material of small tire ofwheel, i.e., urethane rings with hardness of SHORE A 70 were frequently worn and/or
broken in play. As the results, it caused adverse effect for the performance andmaintenance of robot. So, we tried to search and find the suitable form of wheel andmaterials of small tire to solve this problem.
As well as known, X-ring is a popular material for small tire. However, it is notavailable easily for X-ring, because the difficulty of getting and expensiveness of it inJapan. We have some X-ring for evaluation, but its size is different from our previous
small tire. So, we manufactured the experimental wheel to evaluate for the performance of materials of small tire with no change of diameter of the wheel. It is shownin Fig. 3. Through these wheels, we tried to investigate the difference among X ringand some materials for their performance.

Fig. 3Comparison of experimental wheel (left) with present one (right)

First, we evaluated about the performance of experimental wheel by using of small
tire which is same condition (urethane material with hardness of SHORE A 70). Figure 4 shows the result compared the velocity characteristic of experimental wheelwith the present one. It appears the average velocity under the condition of thirty
back-and-forth straight motions when the command value of trapezoidal accelerationis sent to robot. The agreement of result of both wheels is good. It means that theexperimental wheel is valid for evaluation.

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3500

Command value
Present wheel

3000

Velocity (mm/sec)

Experimental wheel

2500
2000
1500
1000
500
00 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 1.1 1.2 1.3 1.4 1.5 1.6 1.7Time (sec)Fig. 4 Characteristic comparison of present and experiment wheel

Next, we investigated about similar characteristics of (a)X-ring, urethane withhardness of SHORE A (b)70 and (c)90, (d)polychloroprene, (e)nitrile rubber for small
tire of wheel. The results are shown in Fig. 5.
3500

Command value(a)X Ring A70(b)Urethan A70(c)Urethan A90(d)Polychloroprene A65(e)Nitrile rubbre A70Velocity (mm/sec)

3000

2500
2000
1500
1000
500
00 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 1.1 1.2 1.3 1.4 1.5 1.6 1.7Time (sec)Fig. 5 Velocity characteristics of various materials for small tire

In Fig. 5, X-ring indicates the best performance among all materials. The(b)urethane A70 and (d)polychloroprene are second best one to X-ring. Thus, wemade experiments for durability of small tires made from their materials under theadfa, p. 4, 2014.
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condition of continuous rotation motion for twenty minutes. The results are shown in
Fig. 6 and Fig. 7. There are no serious attritions to expand to the breaking of small
ring in those figures. Therefore, they show that the performance of present wheels aregood within the range of our experimental confirmation. But, we can not confirm it inreal game. So, the performance shoud be confirmed as soon as possible.

Fig. 6．Small tire of urethane 70A , before experiment (left) and after that (right)

Fig. 7 Small tire of polychloroprene, before experiment (left) and after that (right)

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3.

Electrical design

The electronic circuit is mostly same with last year. The circuit block of base board
and FPGA are shown in Fig. 8, respectively.

Fig. 8 Circuit block of base board (upper) and FPGA (lower)
3.1 PC Software for New FPGA Board
We developed software to obtain the information of new circuit. All data (e.g. datasuch as battery voltage, capacitor voltage, angular velocity of each motor, and a current value etc.) of a circuit can be observed in this software. These data can be outputted to the file of CSV or VCD format, and also evaluated with gnuplot.
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The execution screen of the software is shown in Fig. 9 and the capture image ofgnuplot is shown in Fig. 10. This software can also write into micro-computer in
FPGA with HEX format program by means of two methods. One is a mode of completely stored in ROM, and another is that of temporarily stored. The temporary store
means that it will be back previous program when the power supply is shut down. By
applying this method, it will be convenient for debugging.

Fig. 9 Execution screen of software to obtain data for robot

Fig. 10 Capture image of gnuplot

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3.2 Inertial Measurement Unit for New Circuit
We built a scalable system for new circuit. One of them is a terminal connector for
add-in boards in a circuit. It is necessary for advanced control of robot to mount IMU(Inertial Measurement Unit). The pictures of new designed IMU and the FPGA board
are shown in Fig. 11 and Fig. 12, respectively. Thus, now we can use gyroscope sensor and accelerometer by using this add-in board. We have a plan to try new control
system by using the value from IMU with software descried in §3.1.

Fig. 11 new IMU circuit

Fig. 12 IMU circuit mounted on FPGA

3.3 Voltage booster circuit
The DC-DC converter is used to boost up voltage for the solenoid. The input voltage of 16V is converted to 200V output. This chopper circuit is controlled by PIC ineach robot. In kicking device, the output voltage of 200V is charged in 3mF capacitor.
The time to charge up to 200V from 16V is about 3 seconds.

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4.

Software design

Our AI server is called SIS (Strategy Information System). The SIS consists of four
threads as shown in Fig. 13. There are "Game Thread", "Sender Thread", "SSL-Vision
Receiver" and "Referee Box Receiver". The analysis of strategy and action for all
robots are executed in "Game Thread".

Fig. 13 Structure of SIS
In 2014, we tried to modify the structure of "Strategy System" in "Game Tread", andimprove the "Speed Controller" in "Sender Thread".
4.1.

Improvement of the structure of strategy system

Robots' action

Fig. 14 Previous structure of strategy system
A previous structure of the "Strategy System" shown in Fig. 13 is constructed fromthree modules. It is shown in Fig. 14. First, it is chosen the "Class Formation" corresponding to the Referee box’s signal in "Class Strategy". In next "Class Formation", itis chosen the "Support Action" corresponding to the game situation for each robot.
Finally, the "Support Action" makes a decision how do robots work. For example,
There are actions such like [kick a ball] and [move a robot] in the "Support Action"library. When the "Class Formation" decide to make kicking a ball for a robot, itchooses [kick a ball] in the "Support Action" against robots.
In previous structure, the "Class Formation" decided all robots’ action analyzing
from the situation of game. But, we have to construct more flexible "Class Formation"
to promote a smart and intelligent gameplay. It is difficult to develop more complex"Class Formation" because it is required many "Support Actions" and branch condition for intelligent behaviors. It is also hard to reuse the previous program. Therefore,
we tried to introduce newly-proposed "Class Agent" in new strategy system as shownin Fig. 15 to develop program more efficiently.

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Robots'action

Fig. 15 New structure of strategy system
The "Class Agent" is a class that selects appropriate Support Action depending on
given role in game. In new structure of Fig. 15, the "Class Formation" decides only
each robot’s role. The knowledge and intelligence to play a given role is kept in the"Class Agent". As the results, we could develop more efficiently programs whichhave flexible intelligence by introducing of this structure.
4.2.

About controller of RobotuFig. 16 The robotic control to last year.
Last year, we developed controller which has two control units as shown in Fig.
16. To realize stable and speedy robot’s motion, it is necessary to control within therobot's limitation of acceleration. It is achieved by using sliding mode control that isone of nonlinear control on the basis of explicit limitation of acceleration. We can get
the target velocity V* from target position P* and current position P in Unit1 of Fig.
16. The Unit2 is enable us to know current velocity V following V* by using twodegree-of-freedom control. In case of use of this theory, it is required a high following-performance for robots to make V≒V* in Unit 2. However, we could not construct appropriate structure of Unit2 last year. In this year, we tried to identify ideal
robot model by using genetic algorithm, and design ideal Unit2 on the basis of theresults after that.
4.2.1. Identification of model by using Genetic Algorithm
Velocity of the robot is expressed in transfer function as following equation,𝑘𝑠+𝑡
𝑉= 2(1),
2𝑢𝑠 +2𝜁𝜔𝑛 𝑠+𝜔𝑛where,
are constant coefficients that define characteristics of robot, and u
displays the manipulated variable in Fig. 16. Eq. (1) is equal to transfer function ofadfa, p. 10, 2014.
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speed control of motor with PI control. In this system identification process, the genetic algorithm (GA) is used to get most probable parameters of. Figure17
shows a program flow of system identification process with GA.

Manipulated
value ut
Observed velocity VPreparation

Initial parameter ()Mutations

Simulation
Estimated velocity VˆSelection
Final results,,,

Fig. 17 Identification process of parameterby using GA

At first of identification, the robot’s velocity V is investigated when the trapezoidal
acceleration command value is given as shown in Fig. 18. Next, it is analyzed
that robot’s estimated velocity Vˆ follows with trapezoidal velocity V. The
results for experiment of 1st and 400th generations on GA are also shown in Fig. 18.
It is found that the estimated velocity Vˆ is good agreement with the observed value Vin Fig. 18. All control logics in SIS are made by using results of identification mentioned above.

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command value v*observed value v

estimated value (1st gen.) v^

estimated value (400th gen.) v^

1500

Velocity (mm/sec)

1000
5000-500 0

0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 5.5 6 6.5 7

-1000
-1500
-2000-2500-3000

Time (sec)Fig. 18

Result of optimization by applying GA

4.2.2. Optimization of Unit2
We identified the appropriate parameter of control model for Unit2 in §4.2.1. As
mentioned above, the Unit2 ensure following performance by using two-degree-offreedom control. It is necessary to be equal to one for value of whole transfer functionof nominal plant in order to making V*≒V. Thus, C(s) in Unit2 is designed in following eq. (2) as reverse expression of control system.
𝑠 2 +2𝜁𝜔 𝑠+𝜔 2𝑛𝑛𝐶(𝑠) =(2)𝑘𝑠+𝑡
By using eq. (2), whole transfer function is theoretically equal to 1. In fact, however, the parameters
derived in GA are not strictly true. So, the Unit2 uses
PID control to reduce influence of various errors. A gain of this PID control is determined from pole assignment of nominal plant through a trial and error process.

5. Conclusions
Our robots have been continuously improved in every year. As the results, the motion and the performance of the robots are getting better.
We hope that our robots will perform better in this coming competition.

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