This is Paradigm Engineering’s final control board with 48V intake. Main components include:

• An ESP32 MCU. This sends all necessary PWM and output signals to the motors based on signals received by the connected Pixhawk.
• A USB to UART bridge, allowing the ESP to use the firmware written on a USB-connected laptop via UART.
• A logic level shifter, shifting the 3V3 ESP outputs to 5V for motor inputs that require 5V.
• Two USB connectors, one for the UART bridge and one directly connected to the ESP.
• A 48 to 12V buck converter, a 12 to 5V linear regulator, and 5 to 3V3 LDO.
• A hot-swap IC to safely connect and remove the battery connection. The IC is connected to a sense resistor for overcurrent protection, a voltage divider for under-voltage protection, and a switch to toggle the system.
• Outputs to power two motors, complete with a fuse for current protection, and a flyback diode to protect inductive loads from high voltage spikes, and a barrel jack connector for a Nvidia Jetson.

This is an auxiliary board with 48V intake. Main components include:

• A hot-swap IC to safely connect and remove the battery connection.
• Outputs to power to a Jetson computer, lidar, braking and steering motors.
• LoRa receiver module to stop the car if remotely triggered.
• A 48 to 12V buck converter and a 12 to 5V linear regulator.

This is a STM32 DevKit with Bluetooth capability. Main components include:

• An STM32WB MCU.
• Connectors for debugging purposes: USB, UART, JTAG.
• RF circuit with connector for an external antenna.
• Two external crystals (Low and high-speed) for clock.

I implemented a 2D controller for the CARLA simulator to control the vehicle to follow a racetrack by navigating through preset waypoints. The simulated car has to reach these waypoints at certain desired speeds, which requires both longitudinal and lateral control.

• Developed a 2D controller for a simulated autonomous vehicle with Python. The controller record waypoint variables in each simulation step and outputs the throttle, steer, and brake accordingly.
• Trajectory feedback sends the car and track information to controller for updates. Controls feedback compare the desired speed and actually speed to adjust accordingly (close loop).
• The trajectory is recorded in a .txt file and passed into a Python script to plot position and velocity at each waypoint.

I designed a system that processes human verbal commands and controls the lighting circuits with an ESP32 DevKit This product is an ESP32, Sinric Pro and Google Assistant module that allows users to activate three lights control system.

• ESP32 is programmed to output signals and to control the relays. The lights turn on/off when the relays close/open the lighting circuits individually or at once.
• Real-time monitor and dashboard for the lighting system on both computer and mobile phone. Displays are available on SinricPro and Google Home.