F12: Self-Driving GPS Following Car
Contents
Self-Driving GPS Following Car
Abstract
The objective of this project is to create an autonomous vehicle that follows another car. A leading car will continually inform the autonomous car of its location. The autonomous car will then drive to the target location while avoiding obstacles along the way.
Introduction and Objectives
The Self-Driving GPS Following Car follows another car by driving to the GPS coordinates of the leading car. A ZigBee communication link transmits the GPS data from the leading car to the following car. The following car utilizes a GPS and a compass to determine its own location and orientation relative to magnetic north. Using the two pairs of GPS coordinates and the orientation of the car, the bearing and distance necessary to be traveled is calculated. The car uses proximity sensors, so the car can avoid obstacles while navigating to the destination.
The project required the following objectives to be accomplished:
- Read GPS coordinates of the leading car and the following self-driving car
- Use XBee modules to send and receive GPS coordinates from the leading car to the following car
- Compute the true north bearing and distance necessary for the following car to reach the leading car
- Account for difference between true north and magnetic north in bearing calculation
- Read the magnetic north bearing using a compass
- Read the distance to objects using proximity sensors
- Control steering motor to steer left, right, and straight using a motor controller
- Control direction motor to move forward, backward, and stop using a motor controller
- Determine algorithm to drive toward destination
- Determine algorithm to avoid obstacles
Team Members and Responsibilities
- Elias Barboza
- PWM driver, motor controllers, and obstacle avoidance
- Caleb Chow
- Read compass, read GPS coordinates, and move toward target GPS coordinates
- Stephen Lu
- ADC driver, read proximity sensors, compute distance based on measurement, and obstacle avoidance
Schedule
| Week Number | Planned Items | Actual Items |
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| Week 1: Design
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| Week 2: Construction
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| Week 3: Drivers
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| Week 4: Coding
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| Week 5: Coding
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| Week 6: Testing
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| Week 7: Finalization
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Parts List & Cost
| Parts | Quantity | Cost | Link |
|---|---|---|---|
| RC Car -
| 2 | ~$25 | Previously owned |
| Microcontroller -
| 1 | ~$120 | |
| XBee Module -
| 2 | ~$24.95 |
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| GPS -
| 2 | $37.21 | |
| Motor Controller -
| 2 | ~$13 | |
| Compass -
| 1 | $50 | |
| Sonar Range Finder -
| 3 | $26.95 | |
Design & Implementation
Hardware Design The leading car consists of the following additional hardware:
- XBee module
- GPS module
- 3.3V regulator circuit
The leading car is responsible for sending its GPS coordinates to the following car. This is accomplished by sending the raw GPS data over ZigBee to the following car. The GPS and XBee modules both use UART to communicate, so no microcontroller is necessary. The paired XBee modules will take care of the data transfer. Both modules ran off the same 3.3V power supply, which came from a regulator off of the car’s battery pack.
File:CmpE146 F12 T7 Leading Car Block Diagram.png
Hardware Design
Discuss your hardware design here. Show detailed schematics, and the interface here.
Hardware Interface
In this section, you can describe how your hardware communicates, such as which BUSes used. You can discuss your driver implementation here, such that the Software Design section is isolated to talk about high level workings rather than inner working of your project.
Leading Car
Leading Car Block Diagram
- GPS – UART
- Outputs GPS data on Tx to XBee Rx
- XBee – UART
- Inputs data to send on Rx from GPS Tx
- Power Supply – 3.3V
- Supply power to GPS and XBee modules
- Add 3.3V voltage regulator with filtering capacitors to RC car’s battery pack
Following Car
Following Car Block Diagram
- Microcontroller
- 2012 SJSU One Board (LPC1758)
- GPS – UART
- P2.8 = Tx, P2.9 = Rx
- PINSEL4 = 0b10 for both
- Xbee – UART3
- P4.28 = Tx, P4.29 = Rx
- PINSEL9 = 0b11 for both
- I2C2 Devices
- P0.10 = SDA, P0.11 = SCL
- PINSEL0 = 0b10 for both
- Components :
- Proximity sensor (SRF08)
- Compass
- P0.10 = SDA, P0.11 = SCL
- Proximity Sensors (LV-MaxSonar-EZ4) – ADC4 and ADC5
- P1.30 = AD0.4
- P1.31 = AD0.5
- PINSEL3 = 11 for both
- Motor Controllers (2) – PWM
- P1.20 = PWM1.2
- P1.24 = PWM1.5
- PINSEL3 = 10 for both
- Power Supply – 5.0V from RC car's original battery pack
- Supply power to motor controllers for motors
- Supply power to SRF08 proximity sensor
- Power Supply – 3.3V
- Microcontroller 3.3V output
- Supply power to GPS, Xbee, and LV-MaxSonar-EZ4 proximity sensors
Software Design
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Implementation
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Testing & Technical Challenges
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Wifi Connection Issues
Many wifi connection issues were encountered. To solve this problem, a dedicated task was created to re-connect to wifi if the connection was ever lost.
Conclusion
The GPS Following Car is, in general, an embedded system that connects together five different components that are interfaced together in software through protocols such as I2C, UART, and ADC. The main objective of the project was to create a car that would be able to follow another car automatically by acquiring the necessary information from the leading car, such as GPS coordinates and heading. The challenge of the project was for the following car to be able to travel to its destination by itself without colliding with any external objects. This challenge was tackled by following a very strict and efficient object-avoiding algorithm. As a team of engineers, this project enhanced our programming skills by taking our knowledge of the C and C++ languages and putting them to use to ensuring that the system worked effectively and efficiently. We learned to communicate and share information with one another in a way that we were always productive and learned to manage our time effectively to make consistent progress throughout the semester. Also, our understanding of operating systems was challenged in this project because the system as a whole is based on FreeRTOS. By having an actual O.S. run our system we were challenged to meet acceptable CPU efficiency levels, to make use of the available memory efficiently by limiting our tasks to only using the amount of stack necessary to execute.
Project Video
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Project Source Code
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References
Acknowledgement
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References Used
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Appendix
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