Humidity Module

Autonomous-Crawlspace-Inspection-Robot

This GitHub contains all relevant files used during development. For a comprehensive guide to the repository set up see the bottom of the document.

Executive Summary

Crawl spaces grant convenient access to the plumbing, duct work, and electrical wiring of a house, but they often present unique dangers to maintenance professionals and residents alike. Exposure to harsh breathing conditions, hanging obstacles, uncomfortable working positions, and even animals can cause non-ideal conditions. This capstone project will focus on the design and assembly of a robot prototype that can perform these inspections autonomously. The end product will be an autonomous, mobile robot that can be left unattended in a crawlspace by an inspector. It will navigate through the space, create a map and model of the space, compile an image of the entire crawlspace ceiling, and collect sensor data. This sensor data will include humidity, temperature, and wood moisture content.

Current Robot Capabilities

The first iteration of the project focused on setting up the hardware systems. Sensors, microcontrollers, motors, and power circuits were designed and implemented as part of a larger multi-group project. The following details the current capabilities of the robot.

• Low-level autonomy which allows the robot to navigate through an enclosed area
• Creating a map of the area using the SLAM algorithm
• Take pictures throughout an area and stitch simple areas into a singular, larger image
• Collect humidity, temperature, and moisture content data and overlay information on images
• Supply power for consistent operation across all components
• Robot movement through serial commands and return encoder data to the main microcontroller
• Manual control through text-based commands while also streaming live video to the operator

For more detail on current designs, see files in sub-system directories

Salient Outcomes

Although this project includes lofty long-term goals, many exceptional systems were able to be incorporated in the first iteration of the project.

• The mapping was found to be accurate to 93% or more in each test that was run. While this is useful information for an inspector to have, it will also provide an invaluable framework for future updates to the autonomy
• Power was successfully applied to all parts of the system with no over-currents or under-voltages experienced by the system. All back EMF from the motors was successfully filtered out as well.
• Environmental sensing was found to be exceptionally accurate. Temperature and Humidity were both found to be 96% accurate or greater while moisture content was successfully measured to within 2.5% moisture.

Pictures and Videos

The final system demo in the crawlspace can be found here

A picture of the final system can also be found below

Who Are We? Mr. Jesse Robert's ECE 4961 Capstone Team 1

• James (Jim) Camp - Senior Electrical Engineering Major, Mechatronics Concentration - Environmental Sensor Subsystem Developer - Delegator

• John-Caleb (JC) Williams - Senior Electrical Engineering Major, Electromagnetics Concentration - Navigation Subsystem Developer - Treasurer

• John Harris - Senior Electrical Engineering Major, Controls Concentration - Power Subsystem Developer - Secretary

• Joseph Thomas - Senior Electrical Engineering Major, Power Concentration - Movement Subsystem Developer - Social

• Mr. Jesse Roberts - Professor and Faculty Advisor

• Project Stakeholders - This project was developed for anyone who needs to inspect their crawlspace. This includes homeowners, building inspectors, and renovators. The system is also a great solution for anyone experiencing issues with mold or unsafe crawlspace conditions.

Repo Guide

This repository contains the entirety of the Autonomous Crawlspace Inspection Robot’s REV1 design files. The folder breakdown is as follows

• Design Files – Contains files that represent the final design state of the project. This is made up of an overall system schematic and the bill of materials (BOM).
• Documentation – Contains all written submissions created throughout both semesters of the course. Also included are the presentations used at the end of the project.
• Environmental Sensing – This subsystem is responsible for the data collection which occurs throughout the crawlspace. Additionally, image stitching is also included within this folder.
• Movement – This subsystem is responsible for controlling the physical motion and positioning of the robot.
• Navigation – This system handles the mapping and autonomy. Interfacing with the Raspberry Pi, LIDAR, distance sensors, and remote access are also included in this subsystem.
• Pictures and Videos – A repository for all the pictures and videos taken throughout the experimentation and testing.
• Power - This subsystem is responsible for providing continuous power to all the components. Circuit protection and power filtering are also integrated into this subsystem.