🚗 Intelligent Obstacle-Avoiding and Line-Tracing Car System

Overview

This project showcases the design and implementation of an intelligent vehicle system, developed to perform three complex tasks: line tracing, obstacle avoidance, and object grasping. The project integrates advanced software algorithms and innovative hardware structures, ensuring efficiency and flexibility in real-world applications.

Below are the videos demonstrating the intelligent vehicle’s line-tracing and obstacle-avoidance tasks.

Project Highlights

Line-Tracing Task:
- Leveraged OpenMV for image-based navigation along pre-defined tracks, using dynamic thresholding for accurate path detection.
- Developed PID-based speed control to maintain stability on sharp turns and narrow paths.
Obstacle-Avoidance Task:
- Implemented a hybrid algorithm using ultrasonic sensors and IMU data to detect and bypass obstacles while navigating toward the destination.
- Used precise wall-following techniques to avoid getting trapped in loops during obstacle avoidance.
Object Grasping Integration:
- Designed a lightweight, adaptive gripper driven by SG90 servos, ensuring stability during transport.
- Integrated grasping and placing processes seamlessly into both line-tracing and obstacle-avoidance tasks.

Hardware Design

Constructed a two-layered chassis using 3D printing for efficient weight distribution, ensuring lightness and stability.
Adopted two-wheel differential drive for high maneuverability, supported by a rear omni-wheel for balance.
Integrated sensors (ultrasonic, IMU, OpenMV) with strategic placements for optimal data collection and processing.

Software Architecture

State-Machine Logic

graph TD A[Start] -->|Detect Object| B[Grasp Object] B --> C{Select Task} C -->|Line Tracing| D[Line-Tracing Mode] C -->|Obstacle Avoidance| E[Obstacle-Avoidance Mode] D --> F[Detect Destination] E --> F F --> G[Place Object] G --> H[End]

Key Features

Utilized OpenMV for real-time image processing and object recognition.
Communicated between modules using UART and Bluetooth protocols, ensuring real-time responsiveness.
Enhanced task precision through the fusion of dynamic state transitions and control algorithms.

Innovations

Developed a two-degree-of-freedom grasping mechanism, utilizing servo-driven claws with sponge linings for precision handling.
Implemented LAB color space processing to reduce lighting-related inaccuracies during line tracing.
Integrated adaptive algor56ithms to dynamically balance speed and accuracy for different tasks.

Challenges and Solutions

Line-Tracing Challenges

Sharp Turns: Improved PID tuning to handle tight curves without losing track.
Shadow Interference: Applied dynamic threshold adjustments to minimize errors caused by varying lighting.

Obstacle-Avoidance Challenges

Sensor Interference: Reduced ultrasonic sensor cross-talk through time delays between pings.
Navigation Deadlocks: Implemented wall-following corrections to bypass loop scenarios.

Thank you for exploring this project. Feel free to share your thoughts! 🙌