AN FPGA BASED SOC DESIGN FOR AN AUTONOMOUS VEHICLE

The project focuses on design of an autonomous vehicle which is capable of building the map of any unknown environment and localize itself within the environment using Simultaneous Localization and Mapping (SLAM) algorithm. This implementation will be done on Zynq-7020 System-on-Chip (SoC) call

Project Title

AN FPGA BASED SOC DESIGN FOR AN AUTONOMOUS VEHICLE

Project Area of Specialization

Electrical/Electronic Engineering

Project Summary

The project focuses on design of an autonomous vehicle which is capable of building the map of any unknown environment and localize itself within the environment using Simultaneous Localization and Mapping (SLAM) algorithm. This implementation will be done on Zynq-7020 System-on-Chip (SoC) called as PYNQ which consists of an ARM processor and Xilinx 7020 FPGA. The vehicle should also be capable of Autonomous navigation so for this purpose Neo 6m GPS module is used along with Arduino/Raspberry Pi through which it can position itself and navigate to reqiured position. The obstacle avoidance will be performed using LiDAR sensor and ultrasonic sensors. 

Project Objectives

The project has following objectives.

1) To make an autonomous vehicle which can navigate to any specified position.

2) The vehicle should be capable of building map of any unknown environment and avoid the obstacles which may come in its way.

3) The implementation of this algorithm to be done on a System on Chip (SoC) such as PYNQ board.

4) The part of algorithm to be implemented on ARM processor and then will be accelerated using an FPGA.

5) The vehicle should be cost effective and compact in size.

Project Implementation Method

A LiDAR sensor is used to get the information of surroundings and encoders are used to generate the odometry details. Using this information, the SLAM algorithm builds the map of environment and localizes the vehicle in that environment. As the robot moves the map builds itself, giving the map and information of surroundings. At the same time, the GPS module is capturing the coordinates from satellites and matching them with the required coordinates to which the vehicle should navigate. The vehicle will keep moving and avoiding all obstacles which comes in its way using the ultrasonic sensors until the required coordinates are reached. The SLAM algorithm part is implemented on PYNQ System on Chip (SoC) while the navigation portion is implemented on Arduino/Raspberry Pi. 

Benefits of the Project

The project will be beneficial as it is composed of two latest technologies

1) Self-driving cars

2) System on Chips

Both these technologies are highly beneficial in future as the developed countries are working continuously in both these domains and will help Pakistani industry to compete in near future.

Technical Details of Final Deliverable

The final deliverable will be a vehicle which will be equipped with LiDAR sensors and ultrasonic sensors which will sense the environment for creation of map and avoiding the obstacles. Further, the implementation of this project on PYNQ is highly beneficial. It is one of latest SoC available in market having Python integrity. The technical concept of self driving cars and SoC is of a great value for future endeavours of Pakistani Industry.

Final Deliverable of the Project

Hardware System

Core Industry

Transportation

Other Industries

Core Technology

Robotics

Other Technologies

Sustainable Development Goals

Industry, Innovation and Infrastructure

Required Resources

If you need this project, please contact me on contact@adikhanofficial.com