1. Brendon Knapp, Edmund Sannda, Carlton Allred, Kyle Upton
PROJECT MUNINN
Autonomous 3D Mapping Drone University of North Texas, Department of Computer Science and Engineering
Brendon Knapp, Edmund Sannda, Carlton Allred, Kyle Upton
Client: Jim Buchanan
BECK
TECK
DESIGN
VISION
COMPONENTS
The goal of Project Muninn is to develop an Unmanned Aerial Vehicle that is capable of autonomously navigating and generating 3D images of an indoor space. Such a device has potential applications in various fields such as commercial surveying, geographic surveying, real estate, architectural design and national defense.
We modified the A.R. Parrot 2.0 drone with ultrasonic sensors to aid in autonomous navigation. The LIDAR- Lite v2 laser range finder was attached to a servo mechanism allowing the sensor to capture distinct values in three-dimensional space. Using Node.js software, the sensor data is sent to the computer to control the drone and generate a 3D object file.
To make the autonomous navigation function, we used ultrasonic ping sensors to determine the drones proximity to a wall. The drone will orient itself to a wall and follow it until it reaches a corner. From here the drone rotates itself 90 degrees, it scans the area then continues traversing the perimeter of the room.
The user can initiate or deactivate the drone via our proprietary Graphical User Interface.
Our project takes laser and ultrasonic sensors and pairs it with custom software to produce a fully autonomous 3D mapping drone.
Lidar-Lite v2
Arduino 101
3x HC-SR04 Ultrasonic
AR Drone 2.0
 79P-Tiny-Cam-PTZ-9G
SYSTEM INTEGRATION
DESIGN DIAGRAMS
The LIDAR Lite V2 is attached to the 79P-Tiny-Cam-PTZ-9G pan-tile servo
Three ultrasonic sensors are attached at 90 degrees on the left, right and forward facing positions.
TESTING
Weight tests were necessary to ensure the drone could lift the attached components. The max carrying weight of the drone is roughly100 grams, and our initial component tests totaled 94 grams.
After design modifications using the available hardware, the total weight ultimately exceeded the drone weight limit.
Software was modified to adequately map out the coordinates of a room. This proved possible, however there is slight variance due to the hovering of the drone and the movement of the servo as it scans. This can be corrected by determining the varied x, y, and z position between each sensor poll.
We had to mount the ultrasonic sensors in a position that would optimize the autonomy of the drone. We took into considering placing them at a 90° angle and placing them at a 45°. The 90° angle proved to be more successful because it allows the drone to orient itself using the corners of the room.
To ensure stability, we mounted the LIDAR/Servo mechanism underneath, and as close to the center of the drone as possible. We needed to extend the landing legs of the drone to accommodate this module.
Prototype: Muninn 1.0
RESULTS
GOING FORWARD
THE TEAM
Future Development of Muninn will be in upgrades to issues in the drone battery life, motor strength, and accuracy. We were able to use the ultrasonic sensors to generate 3D images, allowing us to reduce weight at the expense of accuracy.