Artificial Neural Network Controller for a Modular Robot Using a Software Defined Radio Communication System
Abstract
:1. Introduction
2. System Development
2.1. EMERGE Modular Robot
2.2. Modular Robot Simulator
2.3. Artificial Neural Network Controller
Algorithm 1. Control strategy | |
FunctionANN (in , out , margin of error ) | |
//Threshold as stop condition | |
//In vector layer | |
//Out vector layer | |
// is a gaussian function (Equation (1)) | |
//Matrix 10 neurons × 25 layers | |
//Initial weight assignment function | |
While do | |
//Validation of results | |
End While | |
return ANN | |
EndANN | |
Function Virtual enviroment () | |
Load libraries 3D enviroment | //Load virtual objects and robot |
Start SDR port | //Open port to establish communication |
Create communication port read thread | //Start communication routine |
Create communication port send thread | |
Start GUIO (Graphical User Interface Objects) | //Start program |
//Select robot morphologie | |
//Select enviroment | |
//Select routine test or ANN mode | |
//Start iterations | |
If then | |
//Read predefined movements (Table 1) | |
else | |
//Read ANN movements | |
//Note: inf is a initial value (can be > 10) | |
//for and start ANN weights | |
While do | |
← Generate movements in the virtual reality environment () | |
//Nomalize the value and fixes it | |
//on the actuator scale | |
Send via serial port () | //Send to each real module |
Run the move routine for 100 milliseconds | //Delay for the next movement |
++ | |
//Mean Squares Error routine (Equation (2)) | |
//Simulates the ANN and update weights | |
End While | |
End Virtual enviroment |
2.4. Software-Defined Radio Communication System
3. Results and Discussion
4. Conclusions
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
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Inputs | Outputs | |||||
---|---|---|---|---|---|---|
Scenario | Number of Modules | Module 1 | Module 2 | Module 3 | Module 4 | Module 5 |
Flat surface | 3 | 300 | 320 | 340 | - | - |
Flat surface | 4 | 325 | 345 | 365 | 385 | - |
Ladder | 4 | 350 | 370 | 390 | 410 | - |
L-shaped | 4 | 375 | 395 | 415 | 435 | - |
Flat surface | 5 | 400 | 420 | 440 | 460 | 480 |
Ladder | 5 | 425 | 445 | 465 | 485 | 505 |
Environment | Time Estimated by the Simulator | Time in Real Scenario | Error |
---|---|---|---|
Flat surface | 11 min | 11.6 min | 5.45% |
Ladder | 13 min | 13.75 min | 5.76% |
L-shaped | 13 min | 13.7 min | 5.38% |
Environment | Distance Estimated by the Simulator | Distance in Real Scenario | Error |
---|---|---|---|
Flat surface | 1.8 m | 1.77 m | 1.66% |
Ladder | 1.8 m | 1.71 m | 5% |
L-shaped | 1.8 m | 1.73 m | 3.88% |
Place Number | Average SNR (dB) |
---|---|
1 | 69 |
2 | 46 |
3 | 66 |
4 | 36 |
5 | 58 |
6 | 49 |
7 | 59 |
8 | 53 |
9 | 46 |
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Pedraza, L.F.; Hernández, H.A.; Hernández, C.A. Artificial Neural Network Controller for a Modular Robot Using a Software Defined Radio Communication System. Electronics 2020, 9, 1626. https://doi.org/10.3390/electronics9101626
Pedraza LF, Hernández HA, Hernández CA. Artificial Neural Network Controller for a Modular Robot Using a Software Defined Radio Communication System. Electronics. 2020; 9(10):1626. https://doi.org/10.3390/electronics9101626
Chicago/Turabian StylePedraza, Luis Fernando, Henry Alberto Hernández, and Cesar Augusto Hernández. 2020. "Artificial Neural Network Controller for a Modular Robot Using a Software Defined Radio Communication System" Electronics 9, no. 10: 1626. https://doi.org/10.3390/electronics9101626
APA StylePedraza, L. F., Hernández, H. A., & Hernández, C. A. (2020). Artificial Neural Network Controller for a Modular Robot Using a Software Defined Radio Communication System. Electronics, 9(10), 1626. https://doi.org/10.3390/electronics9101626