Autonomous Navigation: Smart RC Car With Obstacle Avoidance

Introduction

This application demonstrates a comprehensive system for controlling and autonomously navigating a 4WD RC car. The vehicle can be operated manually via an RC receiver or can navigate autonomously using data from a 360-degree LiDAR sensor, which enables real-time obstacle detection and path planning. The car is also equipped with an Serial Peripheral Interface (SPI) based ArduCAM® MEGA camera module for image capture and a 9DOF 3 Click board™ used as an Inertial Measurement Unit (IMU) for collecting motion and orientation data.

All sensor data—including live images from the camera, LiDAR readings, and IMU data—are transmitted wirelessly to a PC using a TCP server-client communication protocol. This allows the PC to receive and process real-time visual, spatial, and motion information from the vehicle. The system provides a robust platform for developing and testing advanced navigation algorithms, remote control solutions, sensor integration, and wireless data transmission techniques in mobile robotics applications.

Figure 1. Smart RC Car

Figure 2. System Block Diagram

Modules/Technology Used

• Peripheral modules

  • PORT
  • SYSTICK
  • SERCOM1 - UART
  • SERCOM2 - SPI
  • SERCOM3 - SPI
  • SERCOM4 - UART
  • SERCOM5 - I²C
  • TCC0
  • TCC9
  • EIC
  • EVSYS

• Drivers

  • I²C
  • SPI
  • USART

• Wireless

  • WINCS02
  • RNWF WINCS Wi-Fi Service
  • RNWF WINCS NET Service

• System Services

  • Time
  • CONSOLE
  • DEBUG

• Middleware libraries

  • Harmony Core

Figure 3. Project Graph

Related Documentation

• PIC32CZ8110CA90208 Product Page
• PIC32CZ8110CA90208 Code Examples on Discover
• PIC32CZ8110CA90208 Code Examples on Github
• Online Documentation of this Demo

Software Used

• MPLAB® X IDE v6.30 or newer
• MPLAB® XC32 Compiler v5.00 or newer
• MPLAB® Harmony v5.8.4
• MPLAB® Code Configurator (MCC) v5.6.4 or newer
• Microchip PIC32CZ-CA90 Series Device Support v1.7.168 or newer
• CSP v3.25.1
• CORE v3.16.0
• CMSIS_5 v5.9.0
• Wireless System RNWF v3.1.0
• Wireless WiFi v3.12.2
• MCC Core v5.8.4
• Smart RC Car GUI
• Python® v3.7.9 or newer

Hardware Used

• PIC32CZ CA90 Curiosity Ultra Development Board
• WINCS02 Add-on Board
• 4WD RC car chassis (RBC1063A)
• 360-degree LiDAR sensor
• ArduCAM® Camera Module (B0401)
• 9DOF 3 Click
• RC transmitter and receiver
• Cytron 3Amp Motor Driver MDD3A (381249)
• OLED Display (ELC2065-2)
• 4400 mAh Battery (1212508)

Software Setup

Run the requirements Python file in the command prompt to install the required packages needed for the Graphical User Interface.

Figure 4. Software Setup

Hardware Modification

Remove the Universal Asynchronous Receiver and Transmitter (UART) series resistors (R215 and R220) on the WINCS02 Add-on Board.

Figure 5. WINCS02 Setup

Hardware Setup

1. Attach the WINCS02 Add-on Board to the mikroBUS™ Extension of the PIC32CZ CA90 Curiosity Ultra development board.

   
   Figure 6. WINCS02 Add-on Board Connection

2. Place the custom Arduino® shield board onto the Arduino® extension of the PIC32CZ CA90 Curiosity Ultra development board.

   
   Figure 7. Custom Arduino® Shield Board Mounting

   Note: The Gerber file and schematic for the custom Arduino® shield are available in the design_files folder.

3. Attach the 9DOF 3 Click to the mikroBUS™ Extension of the Arduino® shield board.

   
   Figure 8. 9DOF 3 Click Board™ Connection

4. Feed the PWM signals from the board to the Motor Driver as per the following table:

   Table 1. Motor Driver Pinouts

   Output Pin	Motor Driver Pin
   OUT0	M1A and M2A
   OUT1	M1B and M2B
   GND	GND

   
   Figure 9. Motor Driver Pinouts on the Arduino® Shield

   
   Figure 10. Motor Driver Pinouts

5. Connect the Steering Servo motor to the PWM output (OUT2) as per the following table:

   Table 2. Servo Motor Pinouts

   Output Pin	Servo Motor Pin
   OUT2	PWM
   VCC	VCC
   GND	GND

   
   Figure 11. Servo Motor Connection

6. Use 5V via the excess power header in the PWPulse-Width Modulation (PWM) outputs.

   
   Figure 12. Power Input

7. Attach the LiDAR module to the PIC32CZ CA90 Curiosity Ultra development board using the LiDAR connector.

   
   Figure 13. LiDAR Module Connection

8. Use the PPM Input connector (fourth header) for the RC receiver Pulse Position Modulation (PPM) output as per the following table:

   Table 3. RC Receiver Pinouts

   Input Pin	RC Receiver Pin
   PIN 4	PPM
   VCC	VCC
   GND	GND

   
   Figure 14. Pulse Position Modulation (PPM) Input Connector

9. Attach the OLED display to the PIC32CZ CA90 Curiosity Ultra development board using the GFX connector.

   
   Figure 15. OLED Display Connection

10. Connect the ArduCAM® MEGA camera module to Extension 1 of the PIC32CZ CA90 Curiosity Ultra development board using the GFX connector as per the following table:

    Table 4. ArduCAM® Camera Module Pinouts

    EXT1 Pin	ArduCAM® Camera
    PIN16	MOSI
    PIN18	SCK
    PIN15	CS
    PIN17	MISO
    PIN20	VCC
    PIN19	GND

    
    Figure 16. ArduCAM® Camera Module Connection

How to Program the Hex File

The pre-built hex file can be programmed by following the below steps:

1. Open MPLAB® X IDE.
2. Close all existing projects in IDE, if any project is opened.
3. Go to File>Import>Hex/ELF File.
4. In the Import Image File window, in the Step 1 - Create Prebuilt Project section, click the Browse button to select the prebuilt hex file.
5. Choose PIC32CZ8110CA90208 under Select Device.
6. Ensure the proper tool is selected under Hardware Tool.
7. Click on Next button.
8. In the "Import Image File" window, Step 2 - Select Project Name and Folder, select appropriate project name and folder.
9. Click the Finish button.
10. In MPLAB® X IDE, click the Make and Program Device button to program the device.
11. Follow the steps in the Running the Demo section below.

Running the Demo

1. Before running the GUI application, ensure the steps Software Setup section have been executed.
2. Run the Smart_RC_Car_GUI application in the scripts folder and the GUI application will open as shown below.

Figure 17. Smart RC Car GUI

3. Get the IP address of the RC car from the OLED display and enter it in the TCP Server Details. Make sure the RC car and PC are in the same network.

Figure 18. Wi-Fi Connection Setup

4. Make sure the RC transmitter's joysticks and switches are in the default position, as below.

Figure 19. RC Transmitter Default Position

5. Turn on the RC transmitter by flipping the power switch as shown below.

Figure 20. RC Transmitter Power Up

6. Power on the RC car by flipping the toggle switch on the right side of the RC car. Make sure the battery voltage is above 9V.

Figure 21. RC Car Power Up

7. Wait for the status message of the RC car on the OLED display (left side of the RC car).

Figure 22. RC Car Start-up Status

8. The connection status will show in the OLED display.

Figure 23. Connection Status (Not Connected)

9. Once it is connected, use the Connect button for receiving the telemetry data of the Smart RC Car.

Figure 24. Telemetry Data Connection

10. The telemetry connection status will be displayed in the OLED display and the RC car will be ready once the system goes online.

Figure 25. Connection Status (Connected)

11. The OLED display also shows the disconnection of the telemetry data.

Figure 26. Telemetry Disconnection Status

12. Select the Lidar option in the drop-down menu of the TCP Client Details section, and the IMU, Motor and LiDAR data will appear after the Receive command from the GUI.

Figure 27. Image Preview in GUI

Note: Use the Stop button to stop the data transfer.

13. Select the Lidar option in the drop-down menu in the TCP Client Details, and the IMU, Motor and LiDAR data will appear after the Receive command from the GUI.

Figure 28. LiDAR Data Preview

Note: Use the Stop button to stop the data transfer.

14. The user can control the RC car manually by moving the joysticks in the RC transmitter.

Figure 29. Manual RC Car Control

15. User can view the LiDAR data in real time as a 360° map while the RC car is in motion.

Figure 30. Real-Time LiDAR Map

16. The user can choose between Manual or Autonomous modes by flipping the channel 7 toggle switch in the RC transmitter.

Figure 31. Mode Selection (Manual/Autonomous)

Note: User can remotely RESET the RC Car by moving the joysticks to the specified location on the RC transmitter as shown below.

Figure 32. Remote Reset via RC Transmitter

Pin Descriptions

• OLED display I/Os:

  Table 6. OLED I²C Pins

  Port Pin	Shield Pin	Pin Functionality	Peripheral Used
  PC25	D14	SDA	SERCOM5-PAD0
  PC26	D15	SCL	SERCOM5-PAD1

• WINCS02 Add-on Board I/Os:

  Table 7. WINCS02 Module SPI and I/O Pins

  Port Pin	mikroBUS™ Pin	Pin Functionality	Peripheral Used
  PC12	MOSI	MOSI	SERCOM3-PAD0
  PC13	SCK	SCK	SERCOM3-PAD1
  PC14	CS	CS	SERCOM3-PAD2
  PC15	MIS0	MIS0	SERCOM3-PAD3
  PA08	INT	IRQ	EIC-EXTINT8
  PB27	RST	RESET	GPIO

• LiDAR module I/Os:

  Table 8. LiDAR Module UART and I/O Pins

  Port Pin	Shield Pin	Pin Functionality	Peripheral Used
  PG10	D8	ENABLE	GPIO
  PC21	D1	TXD	SERCOM4-PAD0
  PC22	D0	RXD	SERCOM4-PAD1

• Motor control I/Os:

  Table 9. Motor Control PMW Pins

  Port Pin	Shield Pin	Pin Functionality	Peripheral Used
  PG05	D3	PWM	TCC9_WO0
  PG06	D2	PWM	TCC9_WO1
  PG07	D4	PWM	TCC9_WO2
  PG09	D7	PWM	TCC9_WO3

• RC Receiver Pulse Position Modulation (PPM) I/O:

  Table 10. RC Receiver Pulse Position Modulation (PPM) Pin

  Port Pin	Shield Pin	Pin Functionality	Peripheral Used
  PB11	D9	IRQ	TCC0 and EXTINT11

• Camera module I/Os:

  Table 11. Camera Module SPI Pins

  Port Pin	EXT1 Pin	Pin Functionality	Peripheral Used
  PC08	PIN16	MOSI	SERCOM2-PAD0
  PC09	PIN18	SCK	SERCOM2-PAD1
  PC10	PIN15	CS	GPIO
  PC11	PIN17	MISO	SERCOM2-PAD3

• Serial console I/Os:

  Table 12. Serial Console UART Pins

  Port Pin	Pin Functionality	Peripheral Used
  PC04	TX	SERCOM1-PAD0
  PC07	RX	SERCOM1-PAD3

Conclusion

The Smart RC Car with Autonomous Navigation and Obstacle Avoidance integrates advanced sensors, wireless communication, and real-time control on Microchip’s PIC32CZ CA90 platform. Featuring LiDAR, camera, IMU, and wireless telemetry, this project establishes a robust foundation for research and development in autonomous vehicles, robotics, and sensor fusion. Its modular hardware and software architecture enables straightforward customization and expansion, making it well-suited for mobile robotics and autonomous vehicles. This flexibility supports complex navigation and controls challenges in real-world environments.