Self-navigating robot – In this system, RP Lidar is interfaced with the Raspberry pi to localize the object. By using python programming, the application is developed to drive the vehicle based on the object in the environment. In this project, the Navigation system is deployed without using ROS (Robotic Operating System) autonomous Vehicle.
In every industry, every application is turning autonomous. In the automobile industry, autonomous-based development is very popular. For autonomous applications, we can use LIDAR, camera, or other sensors for Navigating the Vehicle. Self-navigating robot
In the existing system, the object in the environment gets located using the Ultrasonic sensor or IR sensor and the decision will be made to drive the car without colliding the obstacle.
- Hard to setup
- Needs more components
- The accuracy of output is less
- Not a user-friendly system
In this proposed system, RP Lidar is used. It is a 360-degree lidar, which can localize the object around 360 degrees of the vehicle. Then the vehicle is driven based on the obstacle in the environment.
- Accuracy of output is increased
- Easy to setup compared to old methods
- Very little chance of colliding with obstacles
- User-friendly system
BLOCK DIAGRAM DESCRIPTION
- In this project, RPLidar is interfaced with the Raspberry Pi via USB.
- The driver circuit will be interfaced with the Raspberry Pi to drive the vehicle.
- This project initially takes the Laser scan from the RP Lidar, 360 degrees. It returns the distance and angle of the Lidar scan.
- First, it initializes the Lidar, to monitor the 180 degrees of the car, then the object present at a certain angle makes the decision to choose the right angle to turn.
- Then the vehicle will be moved forward on the available free space.
- Raspberry Pi
- 16 GB SD card
- RPLidar A1
- Power supply
- Driver circuit
- Robot setup
- Raspbian Jessie OS with libraries installed
- Python IDE
- SD Card Formatter
- Etcher/Win32 Disk imager
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