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Autonomous Maze-Solving Robot — Real-Time Sensing & Planning

2023 · University of Toronto · Coursework Project

Arduino Python A* Planning Sensor Fusion Ultrasonic IR Line Trackers Encoders PID Control Breadboard Prototyping SolidWorks 3D Printing

Gallery

Maze run demonstration Sensor layout and wiring A* path planning visualization

Overview

  • Real-Time Sensing: Integrated 5 ultrasonic sensors, dual wheel encoders, and IR line trackers on an Arduino-based platform for continuous obstacle detection and localization.
  • Planning & Control: Implemented A* path planning with waypoint tracking and PID velocity control for smooth, collision-free navigation in narrow corridors.
  • Performance: Achieved < 2 cm positional error at 10 Hz update rate and a > 95% task completion rate across varied maze layouts.
  • Hardware: Designed a compact chassis in SolidWorks, 3D-printed mounts, and breadboard-prototyped motor drivers and sensor harnesses for rapid iteration.

Highlights

  • Multi-sensor fusion (ultrasonic + encoders + IR) at 10 Hz
  • A* planner with waypoint tracking and PID velocity loop
  • < 2 cm positional error; > 95% completion rate
  • SolidWorks chassis, 3D-printed mounts, breadboard electronics