Vaibhav Gurunathan

Instructor Assistant - Autonomous Robotics (Winter 2025)

During Winter 2025 (January - May), I served as an instructor assistant for the Autonomous Robotics course at the University of Michigan. This role involved supporting students in a challenging course that covered fundamental concepts in autonomous systems, robotics algorithms, and practical implementation.

Course Focus Areas

The Autonomous Robotics course covered essential topics in robotics and autonomous systems:

  • Motion Planning: Path planning algorithms, obstacle avoidance, and trajectory optimization
  • Localization & Mapping: Sensor fusion, Kalman filtering, and SLAM fundamentals
  • Control Systems: PID control, feedback systems, and stability analysis
  • Sensor Integration: Working with LIDAR, cameras, IMU, and GPS systems
  • Robot Operating System (ROS): Framework for building complex robot behaviors

Teaching Assistant Responsibilities

My role involved comprehensive support for students throughout the semester:

  • Weekly Lab Sessions: Leading hands-on lab exercises where students implemented autonomous behaviors on robotic platforms
  • Office Hours: Providing one-on-one assistance with difficult concepts and debugging help
  • Assignment Grading: Evaluating student submissions and providing detailed feedback
  • Demo Preparation: Setting up robotics equipment and ensuring all systems functioned properly
  • Student Mentoring: Guiding students through complex robotics projects and career advice

Technical Skills Enhanced

This teaching role significantly deepened my expertise in autonomous systems:

  • ROS Proficiency: Advanced ROS development, custom nodes, and system integration
  • Debugging Expertise: Identifying and resolving complex robotics system issues
  • Algorithm Explanation: Breaking down sophisticated algorithms into understandable concepts
  • Hardware Troubleshooting: Working with motors, sensors, and embedded systems
  • Project Management: Coordinating multi-week robotics projects with multiple components

Student Projects Supported

I assisted students with various challenging projects including:

  • Autonomous Navigation: Implementing path planning and obstacle avoidance algorithms
  • SLAM Implementation: Building mapping and localization systems from scratch
  • Sensor Fusion: Integrating multiple sensor inputs for robust state estimation
  • Control Systems: Designing controllers for stable robot movement
  • Computer Vision: Implementing object detection and tracking for robotics applications

Lab Exercises Developed

I contributed to creating several key lab exercises:

  • Basic Motion Control: PID controller implementation and tuning
  • Sensor Processing: Data acquisition and processing from multiple sensors
  • Path Following: Implementing trajectory tracking algorithms
  • Obstacle Avoidance: Reactive navigation using proximity sensors
  • System Integration: Combining all components into a complete autonomous system

Impact on Students

The role allowed me to make a meaningful impact on students' learning:

  • Concept Clarification: Helping students understand fundamental robotics principles
  • Practical Skills: Teaching hands-on implementation and debugging techniques
  • Problem-Solving: Guiding students through complex technical challenges
  • Project Success: Supporting students in completing ambitious robotics projects
  • Career Guidance: Sharing insights about robotics industry and research opportunities

Robotics Equipment Managed

The course utilized advanced robotics equipment that I helped maintain and demonstrate:

  • TurtleBot Platforms: Wheeled robots for indoor navigation tasks
  • Custom Robotics Kits: Modular systems for sensor integration experiments
  • LIDAR Systems: Laser scanning for environment mapping
  • Camera Systems: Vision processing for object detection and tracking
  • Motion Capture: Precise position tracking for algorithm validation

Professional Development

This teaching experience was invaluable for my own professional growth:

  • Communication Skills: Explaining complex technical concepts clearly and effectively
  • Leadership Experience: Managing lab sessions and guiding student teams
  • Technical Depth: Gaining deeper understanding through teaching others
  • Mentorship Abilities: Developing skills in technical mentoring and career guidance
  • Educational Philosophy: Understanding effective teaching methods in STEM fields

Course Outcomes

Students in the course gained comprehensive skills in autonomous robotics:

  • Algorithm Implementation: Practical experience with robotics algorithms
  • System Integration: Combining hardware and software components
  • Problem Solving: Tackling real-world robotics challenges
  • Technical Communication: Documenting and presenting technical work
  • Research Skills: Exploring current trends in autonomous systems

This teaching assistant role during Winter 2025 was an incredibly rewarding experience that allowed me to contribute to the next generation of robotics engineers while further developing my own expertise in autonomous systems.