College - Author 1
College of Engineering
Department - Author 1
Electrical Engineering Department
Degree Name - Author 1
BS in Electrical Engineering
College - Author 2
College of Engineering
Department - Author 2
Electrical Engineering Department
Degree - Author 2
BS in Electrical Engineering
College - Author 3
College of Engineering
Department - Author 3
Electrical Engineering Department
Degree - Author 3
BS in Electrical Engineering
College - Author 4
College of Engineering
Department - Author 4
Electrical Engineering Department
Degree - Author 4
BS in Electrical Engineering
Date
6-2021
Primary Advisor
Xiao-Hua Yu, College of Engineering, Electrical Engineering Department
Abstract/Summary
The future is autonomous. It is estimated that by 2025 there will be 8 million autonomous cars in the market. Millions more will be autonomous devices employed in homes, malls, offices, and warehouses. There are many aspects of these future devices that are necessary for proper autonomous functionality, with none potentially more critical than the devices’ path planning ability. This project aims to create an effective, reliable, and safe path planning algorithm for the autonomous devices of the future. Indoor autonomous devices, such as warehouse or office robots, benefit from being able to always use the same floor plan rather than facing a constant changing environment like cars. The algorithm proposed in this paper is specifically designed for this indoor type of deployment. For our project, we began by implementing a basic APF algorithm, eventually improving it with Higher Order Euclidean functions. The final version of our algorithm involved pivoting to a reinforcement-learning approach. Computer simulations for each step of the development process are provided in the report.
URL: https://digitalcommons.calpoly.edu/eesp/531