Project Title
Turing Board
Team Name
Runtime Terrors
Demo Video
Timeline
Fall 2021 – Spring 2022
Students
| Name | Major | Responsibilities |
| Sahaj Amatya | BSCS | Computer Vision, Object Detection, Path Finding, Fullstack iOS/Android/web app |
| Sarker Nadir Afridi Azmi | BSCpE | Motor Control, IoT, UART Communication |
| Kendall Buchanan | BSCpE | Turning Mechanism, Power Circuitry, Board Layout, LED, Micro-Controller Integration, Hardware Assembly |
| Happy Ndikumana | BSCpE | Turning Mechanism, RTOS, Micro-Controller Integration, UART Communication, Stepper motor circuitry |
| Keaton Koehler | BSCpE | Turning Mechanism, Motor Control, Power Circuitry, Board Layout, Micro-Controller Integration, Hardware Assembly |
| Lydia Sarver | BSCpE | SCRUM Manager, LED, Power Circuity |
Sponsor
Department of Computer Science and Engineering, UTA
Abstract
The Turing Board is a concept autonomous longboard which is capable of exhibiting self-driving capabilities using computer vision. Users of the Turing Board are able to take advantage of various features such as having the board follow you autonomously and having the board summon itself to you from a parked location, in addition to functioning as a standard electric longboard capable of recording and analyzing all trip data. The Turing Board may also function as a load carrier, relieving them from the burden of carrying everyday items like backpacks, boxes, etc. if desired.
Background
The purpose of the Turing Board is to improve the overall user experience of an electric longboard using highly interactive software as a catalyzing agent. The user interfaces with the board via either a native Android or iOS app on their mobile device. It is through the mobile app that the user will be able to control the speed of the board when in manual mode and send requests to the board to perform tasks it is able to do autonomously.
Project Requirements
Customer Requirements:
- Forward Propulsion System
- Turning Mechanism
- Remote (iOS/Android app)
- Computer Vision
- GPS
Packaging Requirements:
- Board Design
- Frontend software
- Dampeners
Performance Requirements:
- Turning Angle
- Battery
System Overview
The Turing Board will have two primary modes of operation: rider mode and autonomous mode.
While in rider mode the electric longboard will be controlled entirely by the rider who is responsible for speed control. In autonomous mode the board will have the capability of being summoned from a parked location and self-navigating to the user. Following the user is another function that will only be available while the electric longboard is autonomous.
Results
We were able to successfully have the board follow us in straight as well as irregular paths. We were also able to use it as an electric skateboard with the custom fullstack iOS/Android app that we built. The underglow LEDs successfully indicate the mode the board is in giving it a more premium aesthetic.
Future Work
- Improve ride analytics
- Scale path-finding to work indoors
Project Files
Project Charter (link)
System Requirements Specification (link)
Architectural Design Specification (link)
Detailed Design Specification (link)
Poster (link)
