Welcome to the GitHub repository for the Dynamic Autonomous Navigation and Obstacle Avoidance System designed specifically for Waveshare Rovers. This advanced system leverages the FHL-LD19 LiDAR sensor, integrating real-time spatial mapping and obstacle detection with dynamic adjustments based on scanning speed and angular resolution. Aimed at enhancing educational, developmental, and research applications, this project embodies the cutting edge in hobbyist autonomous navigation technology.
- Dynamic Obstacle Detection: Utilizes real-time LiDAR data for responsive and accurate obstacle recognition.
- Adaptive Navigation: Dynamically adjusts safety margins based on LiDAR scanning speed and data point density, enabling flexible and intelligent maneuvering.
- Enhanced Environmental Perception: Analyzes light intensity and point cloud data for comprehensive environmental understanding.
- Speed and Angular Resolution Analysis: Leverages scanning speed and angular resolution for improved navigation decisions.
- Sophisticated Decision Making: Integrates advanced algorithms and considers the rover's orientation for precise movement and obstacle engagement.
- Modular Design: Offers a structured, easily customizable codebase suitable for a variety of applications.
- Raspberry Pi 4
- Python 3.x
- pyserial package
- FHL-LD19 LiDAR sensor
Distributed under the MIT License. See LICENSE for more information.
Copyright (2024) (FigTroniX)
- Waveshare
- FHL-LD19 LiDAR Sensor Documentation
- Chat-GPT4 by OpenAI, for assistance in code improvement and documentation.
- And everyone who has contributed to the project!
We hope this project inspires and serves as a valuable tool for anyone interested in advancing autonomous navigation technologies. Happy coding!