Michelle Yang

Hello! My name is Michelle, a fourth-year Electrical Computer Engineering student at Cornell. I am interested in assistive robotics, microcontroller gadgets, and clean energy technology.

Labs

Lab 1: The Artemis Board and Bluetooth

1/21/2026

Setting up the Arduino IDE, testing the Artemis board peripherals, and establishing Bluetooth Low Energy communication.

Arduino IDE Artemis Nano Bluetooth Low Energy Serial Communication

Lab 2: IMU

2/3/2026

Reading data from IMU, get roll, pitch, yaw angle values from low passed filtered accelerometer, complementary filter of accel and gyro reading.

IMU Accelerometer Gyroscope Low Pass Filter Complementary Filter Fourier Transform Two-point Calibration

Lab 3: ToF

2/10/2026

Equip robot with 2 ToF, in varying ranging distance, sampled to find difference between measured and expected ToF distance.

I2C ToF VL53L1X

Lab 4: Motors and Open Loop Control

2/24/2026

Wiring dual motor drivers with parallel-coupled channels, testing PWM control, assembling the robot, and demonstrating open-loop control sequences.

Motor Drivers PWM DRV8833 Open Loop Control Robot Assembly

Lab 5: Linear PID Control

3/3/2026

Implementing P control to drive the robot toward a wall and stop exactly 1ft (304mm) away, using ToF sensor feedback and deadband-compensated motor control.

PID Control ToF Deadband Motor Calibration BLE Data Collection

Lab 6: Orientation Control

3/10/2026

Implementing P orientation control using gyroscope integration. Robot holds a target yaw angle and corrects via differential drive when disturbed.

PID Control IMU Gyroscope Yaw Integration Differential Drive

Lab 7: Kalman Filter

3/24/2026

Implement P & D linear pid + KF to increase control loop speed

PID KF Feedback control loop

Lab 8: Stunts

4/7/2026

Combining KF, PID, and full-speed motor control to execute a flip stunt: driving toward a wall at 255 PWM and reversing hard to flip the car end-over-end.

Stunts Kalman Filter Full-Speed Control ToF

Built a static map by placing the robot at marked positions and performing on-axis 360° rotation scans using ToF distance readings. Scans merged into a global map via coordinate transformation matrices.

Mapping Orientation PID ToF Sensor

Lab 10

4/21/2026

Implemented grid localization using a Bayes filter on a virtual robot. Prediction step uses an odometry motion model; update step uses 18-ray sensor observations precomputed via raytracing across a 12×9×18 discrete pose grid.

Bayes Filter Grid Localization Simulator

Lab 11

4/28/2026

Implemented grid localization using a Bayes filter on a real physical robot.

Bayes Filter Grid Localization Physical Robot in Real Environment

Lab 12

5/5/2026

Implement path planning and execution, where robot navigate through a set of waypoints as quickly and accurately as possible.

Open-loop Linear Control PID Orientation Control Path Planing and Execution