Autonomous-Robotics

Autonomous Mobile Robot - Grand Challenge

Overview

This project involves building an autonomous mobile robot capable of self-navigation and perception. The final goal is to complete the Grand Challenge, where the robot must navigate a Martian-like environment, pick nine colored blocks (red, green, blue) in order, and deliver them to a designated construction zone.

Grand Challenge Video 👇

Table of Contents

• Hardware Design
• Software Implementation
  • Stop Sign Detection
  • Arrow Detection
  • Motion Control
  • Localization
  • Distance Detection
• Grand Challenge Execution
• Lessons Learned

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Hardware Design

The robot is built using a mobile platform kit and consists of the following components:

• Chassis: Mobile base with four DC motors
• Encoders: Magnetic encoders for speed monitoring
• Processing Unit: Raspberry Pi 3B+
• Motor Control: H-Bridge for motor actuation
• Gripper: Servo motor for pick-and-place operations
• Sensors:
  • Camera (for object detection and navigation)
  • Ultrasonic sensor (for obstacle avoidance and repositioning)
  • Inertial Measurement Unit (IMU) (for orientation tracking)

Software Implementation

The software was developed in incremental steps with weekly progress updates.

Stop Sign Detection

• Used HSV masking to detect green traffic lights.
• Fine-tuning HSV values was crucial for accuracy.

Arrow Detection

• Detected arrows using contour detection.
• Determined the direction of the arrow for navigation decisions.

Motion Control

• Compared robot movement using only encoders vs. IMU-assisted motion.
• Found that integrating IMU feedback resulted in more accurate trajectory tracking.

Localization

• Implemented basic math operations to calculate the next position of the robot.
• Faced issues with accumulated errors affecting long-term trajectory.
• Improved accuracy by repositioning the robot using ultrasonic sensors after each run.

Distance Detection

• Collected data points on the centroid position of blocks in the image frame.
• Used interpolation to estimate real-time distances for precise pick-up.

Grand Challenge Execution

Rules:

• Correct block placement: +1 point
• Incorrect block placement: -1 point

Final Run Summary:

• The robot successfully followed the trajectory but encountered issues:
  • False positive detection when picking the second red block.
  • Failure in stopping logic caused an early stop before reaching the construction zone.
  • Ultrasonic sensor limitation led to an unhandled error.

A simple if-condition could have fixed the error, allowing the robot to complete the task perfectly.

Lessons Learned

Through this project, I gained hands-on experience in:

• Perception (image processing and object detection)
• Navigation (localization, and sensor fusion)
• Motion Control (PID control, trajectory tracking, and feedback loops)

This project has been a fantastic learning experience, and I’m grateful for the guidance of Dr. Michell throughout the semester.

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Acknowledgments

Thanks to Dr. Michell for his support in this project!

Peace! ✌️