東海大学紀要　情報通信学部.indd

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みりあひろき
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1 vol.4,no1,2011,pp 論文 ET 2010 PBL *1 *1 *1 *1 * 1 *1 *1 *2 *2 * 3 The Operation and valuation of Embedded System PBL in ET-robot contest 2010 by Tatsuya HOSOKAWA Hosokawa, *1, Toshihiro Kamikage, KAMIKAGE Hiroshi *1, Hiroshi Imai, Shigenori IMAI *1, Ozawa, Shigenori Ryota OZAWA Yamazaki, *1, Ryota Hiro YAMAZAKI Shiomitsu, *1, Hiro SHIOMITSU *1, Hiroki Hagisawa, HAGISAWA Takuya *1, Takuya Higuchi, HIGUCHI Junichiro *2, Junichiro Ogane, Naohiko OGANE Shimizu *2 and Naohiko SHIMIZU *3 (Received on October 2, 2010 & Accepted on September 12, 2011) Abstract Usually students study embedded system in lectures and adopt Project Based Learning(PBL). Therefore, we did practical learning for developing embedded system with using PBL. The project members were 7 senior students who had basic knowledge of embedded system and 2 graduate students as instructors. For practical learning, we participated the ET-robot contest As a result, students could have practical learning with PBL and get essential knowledge of embedded system. Therefore, we verified the efficiency of our method to learn embedded system comprehensively. Keyword: ET-robot contest Project-Based Learning Difference between simulation and real Schedule managements 1. ET ET 1) 2010 Project-Based Learning(PBL) PBL PBL PBL PBL 2) 2. ET ET LEGO MINDSTORM NXT(NXT) 4) Fig.1 nxtosek 5) NXT.. FIg.2 Fig.3 API on/off input output Light sensor Sonor Gyro sensor Motor Touch sensor Sonor Motor *1 4 *2 1 *3 Fig.1 List of sensors

2 out stop stop in Capture of unavoidable dangerours parts Finish a race Victory UML Most fast Capture of Acceptable refuge Line Trace Elements integrate A running car capture PID control Out course Commonness Victory Commonness Enigma A seesaw(stop) Garage in A seesaw(running) Steps A slope Fig.2 ETrobo2009 course Fig.5 Goal oriented model out in Goal & Halfway point Inside course start in out Outside course start Flagpole Obstacle Sonor Line trace Enigma decoding Seesaw Enigma Step Gyro sensor Seesaw Light sensor Steps θ = 11 r1 = 280mm r2 = 200mm Fig.3 ETrobo2010 course r2 Motor square Fig.6 Usecase model Motor encording r1 θ 3.1 Fig.4 Seesaw model ET Fig.7 3. PBL ET 7 9 PBL Fig.5 Fig.6 UML

3 ET 2010 PBL UML UML UML UML UML UML UML UML Making UML Model Implementation UML Extend Function Extend Function Day and Line Trace Motor Encoding Sonor Measurement Seesaw and Steps June, 3 July, 18 August, 1 September, 5 September, 11 Contest practice plan practice plan practice plan practice plan UML Fig.8 UML MARTE 7) MARTE UML UML MARTE UML UML MARTE MARTE NXT soft pwm_r; pwm_l; task_ryor turn; gyro_offset; buf_gyro; task_gyro task_senkai en() glovel_variable e_course; task_sonor Fig.7 Schedule of plan and practice jx; jy; body_yor; task_pid turn; ET hard left_p; right_p; motor s output pwm_r; pwm_l; API() Fig.8 blancer.c API() jv_l; jv_r; pwm_r; pwm_l; task_mort mort_enc_r; mort_enc_l; Motor s Revolution Gyro value; Swing of NXT task_ calibration mort_enc_r; mort_enc_l; Gyro value; API() API() Light_ sensor black; white; API() edge; pwm_r; pwm_l; black; white; Inverted pendulum control in class diagram sonor s value distance; API()

4 3.3.2 ON-OFF Fig.9 PID 6) Light Sensor Value Control Value Time Time x y Fig.11 2% 10 15cm Fig cm Fig.13 Course Line body w w:angle of rotation of motor l:radius of tire v:velocity of body NXT Traveling Line tire l ( ) w v = 2lπ 360 Fig.9 Relation between light sensor value and control value on the PID controls Fig.10 Velocity calculation of NXT NXT ω l υ υ = 2lπ ω 360 υ Fig

5 ET 2010 PBL tire body r dy = vsinθ θ Fig.11 B v dx = vcosθ dx:transferred quantity of the x-axis dy:transferred quantity of the Y-axis v:velocity Coordinate calculation of NXT A:current coordinate B:target coordinate r:radius of arc described A and B dy ϕ:central angle of arc described A and B dx:deflection of x-axis between A and B dy:deflection of y-axis between A and B dx A r = dx2 + dy 2 2 dy ϕ = 180 tan 1 dx dy 1ms Fig.15 Fig.16 Width of swing Body θ = 20 Fig.12 Method of calculating travel distance Tire Approach1 Approach2 Measurement part Measurement a value of motor encording Measurement a value of motor encording Fig.14 Swing figure of NXT Calculation of current coordinate Calculation distance to target coordinate Control part Calculation distance between target coordinate and current coordinate Calculation of controlled variable from distance to target point Simulation Speed falls too fast (v1 > v2) Real Tilt of NXT falls too large Calculation of controlled variable from distance between target coordinate and current coordinate NXT turn for turning value v1 v2 NXT turn for turning value [ NXT reach to target point ] [ NXT not reach to target point ] [ NXT reach to target coordinate ] [ NXT not reach to target coordinate ] Fig.15 Defference moving NXT between simulation and real Fig.13 Motor encoding flowchart 11 Fig Speed down Tilt too large Fig.16 Speed up NXT protected from falls to backward slope to speed up Action when running seesaw of NXT

6 Outside course Inside course ms cm 255cm Fig.17 10cm 30cm Fig.18 B sonor A Flat face Pattern sonor A B Oblique Pattern Fig ET Sonor s reflection A : Transmission wave B : Reflected wave Fig.18 Obstacle:A Measurement point Obstacle:B Measurement of barrier : Line Trace Running : Encode Running : Sonor Measurement ET 4. PBL PBL

7 ET 2010 PBL PID ET Got more skillful in comunication. 5.Got more skillful in the technical skill. 1.Tackled with problems positively Get more skillful ability to discover problems. Fig.19 A result of questionnaire 2.Got more skillful ability to logical thinking. 3.Got more skillful ability to solve problems. PBL 7 Fig PBL 1 2 PBL ET PBL ) ET 2010 < 2) : 3) 3) < pdf/- < char/ja/> pdf/- 5. PBL char/ja/> ( ) 4) LEGO ( ) MINDSTORMS 4) LEGO < MINDSTORMS ET 2010 PID PBL < 5) nxtosek 5) nxtosek < < 6) ( :PID ) [ ] 6) :PID (2005) [ ] 7) UML Profile (2005) for MARTE: Modeling and Analysis of Real- 7) UML Time Embedded Profile forsystems MARTE: Modeling and Analysis of Real- < Time Embedded Systems

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MDD PBL ET 9) 2) ET ET 2.2 2), 1 2 5) MDD PBL PBL MDD MDD MDD 10) MDD Executable UML 11) Executable UML MDD Executable UML

MDD PBL ET 9) 2) ET ET 2.2 2), 1 2 5) MDD PBL PBL MDD MDD MDD 10) MDD Executable UML 11) Executable UML MDD Executable UML PBL 1 2 3 4 (MDD) PBL Project Based Learning MDD PBL PBL PBL MDD PBL A Software Development PBL for Beginners using Project Facilitation Tools Seiko Akayama, 1 Shin Kuboaki, 2 Kenji Hisazumi 3 and Takao

東海大学紀要 情報通信学部.indd

東海大学紀要　情報通信学部.indd