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'SenseDrive: Lidar & Vision-Based Autonomous Navigation' dedicates to advancing autonomous vehicle localization and navigation to Autonomous Level 5 (AD LEVEL 5). Leveraging onboard sensors and high-definition geolocated maps, this project aims to develop robust solutions for seamless navigation in complex environments.

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SenseDrive: Lidar & Vision-Based Autonomous Navigation

SenseDrive is an open-source initiative aimed at advancing autonomous vehicle localization and navigation to achieve Autonomous Driving Level 5 (AD LEVEL 5). By leveraging onboard sensors and high-definition geolocated maps, the project aspires to develop robust solutions for seamless navigation in complex environments.


🚗 Key Features

  • Lidar-Based SLAM:Implements Lidar Simultaneous Localization and Mapping (SLAM) for real-time 3D environmental mapping
  • Visual SLAM:Utilizes camera data to perform Visual SLAM, enhancing perception in GPS-denied environments
  • Sensor Fusion:Combines data from multiple sensors to improve localization accuracy and reliability
  • Traffic Light Negotiation:Incorporates logic for interpreting and responding to traffic signals
  • Lane Following Controller:Provides algorithms for maintaining lane discipline under various driving conditions
  • Simulation Tools:Includes Simulink models and test benches for validating algorithms in simulated environments

📁 Repository Structure

The repository is organized as follow:

  • Lidar_SLAM/ Contains modules related to Lidar-based SLA.
  • Visual_SLAM/ Houses components for Visual SLAM implementatio.
  • sensorfusion/ Includes scripts and models for sensor data fusio.
  • traffic_light_negotiation/ Comprises logic for handling traffic light interaction.
  • slprj/ Generated files from Simulink project.
  • Simulink Models:
    • LaneFollowingController.slxc
    • LidarSLAMIn3DSimulation.slxc
    • TLNWithUnrealTestBench.slxc
    • TrafficLightDecisionLogic.slxc
    • localizeAndControlUsingLidar.slxc
    • localizeUsingLidar.slxc
  • Map Data:
    • lidarmap.fig
    • lidarmap.jpg
    • lidarmap.png
  • Utilities:
    • GenerateImageDataOfParkingLot.slxc Tool for generating parking lot image dat.

🛠️ Getting Started

  1. Prerequisites:
  • MATLAB with Simulink suppot.
  • Toolboxes for Robotics, Computer Vision, and Automated Drivig.
  1. Installation:
  • Clone the repositoy:
    git clone https://github.com/krmahi/SenseDrive.git
  1. Usage:
  • Open desired .slxc models in Simulik.
  • Run simulations to test specific moduls.

📄 Licene

This project is licensed under the Apache 2.0 License.


🤝 Contributng

Contributions are welcome! Please fork the repository and submit a pull request. For major changes, open an issue first to discuss proposed modificatons.


📬 Conact

For questions or collaborations, reach out to Mahesh Kumar at mahesh.kr.2277@gmail.com.

Note: This README is based on the current structure and available information in the repository. As the project evolves, please update this document accordigly.


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'SenseDrive: Lidar & Vision-Based Autonomous Navigation' dedicates to advancing autonomous vehicle localization and navigation to Autonomous Level 5 (AD LEVEL 5). Leveraging onboard sensors and high-definition geolocated maps, this project aims to develop robust solutions for seamless navigation in complex environments.

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