Robotics Olympiad Coaching Needed
Budget: ₹3,000 – ₹5,000 INR
I’m preparing two motivated 7th- and 8th-grade students for an upcoming Robotics Olympiad. They already understand the basics of coding and can assemble and drive a simple robotic car, but they now need a mentor who can take them to the next level.
*Trainer Must Know Hindi and English
The core of the engagement is hands-on, challenge-driven coaching delivered online (preferred) or in person if you are nearby. Sessions should steadily deepen their knowledge while producing small, demonstrable projects they can refine into a competition-ready solution.
Focus areas
• Advanced programming techniques (efficient C/C++ for embedded systems)
• Sensor integration—ultrasonic, IR, line-tracking, IMU, or similar modules
• Working confidently with Arduino Uno and Nano boards using the Arduino IDE
If you can weave in elements of mechanical design or strategy for competition scoring, even better, but the items above are mandatory.
What I’d like to see from you
• A brief outline of a 3 week training roadmap with milestones
• Examples (video or repo links) of student projects you have supervised that involve multiple sensors and clean, well-commented code
• Your availability for 1- to 1.5-hour sessions
• Any suggestions for low-cost components or kits that keep parts sourcing simple
Other Technical Requirements:
The training will focus specifically on the Arduino Nano microcontroller. The trainer must be proficient in working with the following components and sensors:
Microcontroller: Arduino Nano.
Sensors: Dual IR Sensors (Line Following), Ultrasonic Sensor HC-SR04 (Obstacle Avoidance), and LDR (Light Intensity Detection).
Actuators: DC Motors with L298N/L293D Motor Drivers.
Concepts: PWM Speed Control, Sensor Fusion, and Nested Conditional Logic.
Key Learning Objectives:
The students need to master complex tasks where multiple sensors work simultaneously. The trainer must be able to teach:
Advanced Line Following: Smooth navigation and T-junction detection.
Obstacle Detour Logic: Detecting an obstacle, navigating around it, and successfully recovering the line.
Environmental Adaptation: Using LDR sensors to trigger actions (like turning on headlights or adjusting speed in tunnels).
Integrated Missions: Combining Line Following + Obstacle Avoidance + Auto-Lighting + Parking into one seamless code.
Troubleshooting & Calibration: How to adjust sensor thresholds and motor speeds based on competition floor conditions.
The students learn quickly and enjoy experimenting, so I value a coach who is patient, encouraging, and willing to push them with real debugging tasks rather than pre-baked solutions. If this sounds like a good fit, let’s discuss your approach and timeline.
*Trainer Must Know Hindi and English
The core of the engagement is hands-on, challenge-driven coaching delivered online (preferred) or in person if you are nearby. Sessions should steadily deepen their knowledge while producing small, demonstrable projects they can refine into a competition-ready solution.
Focus areas
• Advanced programming techniques (efficient C/C++ for embedded systems)
• Sensor integration—ultrasonic, IR, line-tracking, IMU, or similar modules
• Working confidently with Arduino Uno and Nano boards using the Arduino IDE
If you can weave in elements of mechanical design or strategy for competition scoring, even better, but the items above are mandatory.
What I’d like to see from you
• A brief outline of a 3 week training roadmap with milestones
• Examples (video or repo links) of student projects you have supervised that involve multiple sensors and clean, well-commented code
• Your availability for 1- to 1.5-hour sessions
• Any suggestions for low-cost components or kits that keep parts sourcing simple
Other Technical Requirements:
The training will focus specifically on the Arduino Nano microcontroller. The trainer must be proficient in working with the following components and sensors:
Microcontroller: Arduino Nano.
Sensors: Dual IR Sensors (Line Following), Ultrasonic Sensor HC-SR04 (Obstacle Avoidance), and LDR (Light Intensity Detection).
Actuators: DC Motors with L298N/L293D Motor Drivers.
Concepts: PWM Speed Control, Sensor Fusion, and Nested Conditional Logic.
Key Learning Objectives:
The students need to master complex tasks where multiple sensors work simultaneously. The trainer must be able to teach:
Advanced Line Following: Smooth navigation and T-junction detection.
Obstacle Detour Logic: Detecting an obstacle, navigating around it, and successfully recovering the line.
Environmental Adaptation: Using LDR sensors to trigger actions (like turning on headlights or adjusting speed in tunnels).
Integrated Missions: Combining Line Following + Obstacle Avoidance + Auto-Lighting + Parking into one seamless code.
Troubleshooting & Calibration: How to adjust sensor thresholds and motor speeds based on competition floor conditions.
The students learn quickly and enjoy experimenting, so I value a coach who is patient, encouraging, and willing to push them with real debugging tasks rather than pre-baked solutions. If this sounds like a good fit, let’s discuss your approach and timeline.