Unmanned Aerial Spatial Scanning

Unmanned Aerial Spatial Scanning

Emery Bacon

ABSTRACT (100-200 words)

This is a group project that will be developed by Jack Blaes and Emery Bacon. The goal is to create a sophisticated mapping drone capable of providing sufficient data to create a three dimensional model of the scanned environment. It combines my field of Computer Science with mypartner’s field of Aerospace Engineering. I am able to supply the knowledge of computer programming and robotics to facilitate the development of the code required to create an autonomous vehicle capable of collecting and distributing large amounts of data. My partner is able to bring his knowledge of flight systems and robotics to help assemble the vehicle effectively. With our combined efforts we hope to create something truly innovative.

INTRODUCTION

In the 21st century, drones are being used in a variety of ways around the world. While the versatile flight capabilities of these machines have been exploited for everything from surveillance to delivery, they have not been used for precision mapping. There have been projects that use drones to survey areas for construction purposes, but this lacks the fine detail needed for certain applications. In this project, drones will be utilized to take precise distance measurements to map areas. The maps can be used to allow the user or the drone to locate specific points of interest. The applications of this system are promising. One could use the capabilities of these drones to autonomously map out an area that humans cannot easily access. For example, if a team of geologists were to send a drone into a cave, it could generate a map of the cave down to fine details before they even had to set foot inside, reducing the risks of going in without knowing anything about the structure. This project has a great deal of potential and will grow the abilities of drone technology to tackle everyday problems in the real world.

PROJECT DESCRIPTION (250-300 words)

This project will seek to design and build an autonomous aircraft (a drone) capable of mapping out its environment in three dimensions using a series of measurements from proximity sensors. Using these measurements a program can then generate a model of the space. To accomplish this, a drone will be fitted with proximity sensors that will be taking measurements as it flies. The drone will be programmed to methodically make sweeps of the space that it is in, avoiding obstacles and measuring the distance between itself and walls and objects in the area. A base station located somewhere nearby–possibly at the center or entrance of the area–will keep track of the drone’s position relative to itself using triangulation with another receiver located a short distance from the base. This base station will communicate with the drone and assign it a set of 3-dimensional coordinates, with the base station being the origin. The base station will also receive incoming data from the drone as it takes measurements and transmits them. Combining the data from the proximity sensors on the drone with the coordinate data from the base station, each measured point can accurately be given coordinates relative to the base station. Using these coordinates, a program can generate a point cloud depicting the space that the drone mapped. This point cloud can then be turned into a wireframe model, which will be an accurate representation of the space. Ideally, the wireframe could then be converted into a more detailed mesh that would result in a sophisticated 3-dimensional model of the mapped space.

HISTORY

Aerospace Engineering has expanded rapidly in the short amount of time it has existed in the world. From ideas on paper, to gliders and balloons, to the first actual sustained flight, Aerospace has focused on giving humans the ability to fly. This dream of humanity having been realized, a great amount of focus in the field now shifts to allowing the removal of the human element from the sky. Unmanned Aerial Vehicles, drones, and RC helicopters have all become very popular in the short amount of time that they have existed. Most notably, drones are widely used for military purposes. Initially intended to create unmanned planes that could ram other aircraft, the drone program has become an integral part of the United States Military. As of 2015, the US Air Force had 150 predator drones in inventory to use against enemy targets (USAF.2016). Each predator drone costs 50 million dollars, making the total cost of the fleet 7.5 billion dollars.

The true success of drones, however, lies in the commercial arena. Drone technology has taken off in the private sector, thanks to a great deal of research from universities and aerospace firms. New methods of controlling drones are constantly being researched. This is partially because on the computer science side, drones represent a complex pathfinding problem. The problem of efficient pathing is very important in programming, as it is applicable to more than just drones. In fact, almost every piece of software that involves interconnectivity uses the same graph structure and algorithms that drones do to navigate (Sathyaraj.2008). If the algorithms in one field, for example for drone navigation, are improved, those improvements can be applied to all other fields that use similar graph structures.

Perhaps this is why autonomous flight has “taken off.”From research universitiesachieving breakthroughs in simultaneous localization and navigation (also called SLAM) (Dijkshoorn.2012), to hobbyists putting together a drone that follows them around using their phone signal, fullautonomy seems like the next huge leap in drone technology. In fact, researchers are beginning to apply something called genetic algorithms to drone pathing (CEKMEZ.2014). Genetic algorithms are algorithms designed not only to find the best solution for a given problem, but are also designed to take that solution and optimize it. If applied to a drone, a genetic algorithm can find a pathing solution which a normal pathing algorithm would simply overlook or be incapable of considering, and which a human might never consider. These algorithms, if designed as such, allow autonomous aircraft to improve their own flight patterns using a system similar to natural selection and evolution (hence the name “genetic algorithm”). Currently, drones are capable filling a number of roles in the public and private sectors, from reconnaissance to delivery. Improved pathing and flight code will only lead to them becoming even more ubiquitous than they are now.

SIGNIFICANCE AND DISTINCTION

The biggest distinction between this project and the majority of laser scanning devices is that this scanner will move to see around corners and objects. While conventional laser scanning systems are powerful and effective for visualizing larger structures that are free of obstructions, they run into problems when there are objects in the way or if the structure has a shape such that the scanner does not have a good line of sight. There are also a number of aerial surveillance drones available capable of surveying landscapes and large structures from high above. The point where these two meet, however, is not widely explored. Combining the versatility of a helicopter drone with the power and accuracy of a laser scanner, we could send a drone into a space–for example, a cave or catacomb– and have it scan that space while moving to see around corners and objects. We could then use that data to create an accurate reconstruction of the space and everything in it without ever having to step foot inside. This is advantageous in the case of catacombs and caves, where there is the risk of getting lost or stuck. Someone might send the drone into a catacomb to scan the interior structure, with little risk to the person operating the drone. Additionally, 3D scanning technology is prohibitively expensive for most people–laser scanners often cost thousands of dollars. While not the primary aspect, this project will also distinguish itself by being a low-cost alternative to current methods of 3D scanning.

EXPERTISE AND SKILLS

My skills lie mainly in programming for this project, but also in the construction and wiring of the drone. I have used Arduino a number of times before, including wiring and programming an autonomous utility robot. I have a general understanding of control systems and the RF systems that will be utilized in this project, as well as a basic understanding of electrical engineering. On the programming side, I consider myself a skilled programmer in Java, but I will need to improve my skills in C++, the language Arduino uses.

APPROACH (aka “methods”)

The best suited approach for this project is very hands-on and science-oriented. Since our goal is to create a drone capable of scanning a space and creating an accurate spatial representation of that space using the data from the scan, we will attempt to do exactly that. The project will entail building the drone and running live tests. It will likely take a number of different iterations of the drone, so we will test the drone and modify it as needed depending on the outcome of the tests.

WORK PLAN AND TIMELINE

(See attached PDF)

AUDIENCE

This project is going to be built with a number of different fields in mind, but will primarily be built for fields such as archaeology and geology. In these fields, scientists often need to create accurate 3-dimensional models of spaces. For example, an archaeologist might need to scan a series of catacombs too expansive for a stationary laser scanner. Currently there is no other way to do this than with stationary machinery or by hand. However, a UAV such as the one we intend to build could navigate the catacombs and generate an accurate 3D map as it flies.

BUDGET

(See attached Excel spreadsheet)

OUTCOMES

This project connects directly with my long-term goals because I hope to make a career out of programming drones and other autonomous vehicles. I have been consideringthis specific project for quite some time now, and I plan to continue developing it throughout my time at UMD, and possibly after. This project is not something that can be worked on in the span of a semester and then discarded; while it will be a working product after the capstone is done, a great deal of refining will likely need to be done. I plan to continue that even after my time at DCC is over. This project allows me, in the most literal sense, to reimagine space as we strive to in DCC: it is an attempt to create a new way of looking at any space by creating a digital 3-dimensional representation of the spaces around us. With that in mind, this project means that my time at DCC will affect the rest of my time at college, and the rest of my life.

BIBLIOGRAPHY

Non-Academic Sources:

• Panoptes – Aurora Flight Sciences. (n.d.). Retrieved November 21, 2016, from
• News. (n.d.). Retrieved November 21, 2016, from
• Digitize your world. (n.d.). Retrieved November 21, 2016, from
• Blom, J. D. (2010). Unmanned aerial systems: A historical perspective. Fort Leavenworth, Kan.: Combat Studies Institute Press.
• CyArk. (n.d.). Retrieved November 21, 2016, from

Academic Sources:

• CEKMEZ, U., OZSIGINAN, M., AYDIN, M., & SAHINGOZ, O. K. (2014). UAV Path Planning with Parallel Genetic Algorithms on CUDA Architecture. InProceedings of the World Congress on Engineering(Vol. 1).

• Sathyaraj, B. M., Jain, L. C., Finn, A., & Drake, S. (2008). Multiple UAVs path planning algorithms: a comparative study.Fuzzy Optimization and Decision Making,7(3), 257-267.

• Haddad, N. A. (2011). From ground surveying to 3D laser scanner: A review of techniques used for spatial documentation of historic sites.Journal of King Saud University-Engineering Sciences,23(2), 109-118.

• Fowler, A., France, J. I., & Truong, M. (2011). Applications of advanced laser scanning technology in geology.Riegl USA. Rieglusa.com/pdf/applications-ofadvanced-laser-scanning-technology-in-geology-ananda-fowler-final.pdf.

• Dijkshoorn, N. (2012). Simultaneous localization and mapping with the ar. drone.PhD diss., Masters thesis, Universiteit van Amsterdam.

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