PRE2017 3 Group 17 - State of the Art

State of the art report for the project of PRE2017 3 Groep17.

Image stitching

During this project we make the assumption that image stitching is as sophisticated as we expect it to be. The first article demonstrates full 3D modelling capability based on a photogrammetric system. In this article images are obtained by 2 autonomous drones circling a nucleair storage drum, much like this project, and are then stitched together by Autodesk’s 123D Catch software. This not only shows that the simple image stitching this project requires is possible, it also shows that this project could even be elaborated with 3D Model Generation.

Drone movement and control

This project has mostly been focussed on airborn drones. However, the submarine drones used for the search of the MH370 jet show that the project can easily be applied to similar underwater activities.

Swarm Technology

We found an article describing two “cleaning” algorithms for swarms of robots. It explains how these algorithms can be used as “hunting” protocols to, for instance, find lost humans. The first of the two algorithms, Parallel Path Search, works on rectangular areas only and requires them to have no “leakage”, but is computationally quite light. Leakage is a term used to describe the phenomenon of dirt leaking from dirty sectors to clean sectors or, closer to the example, the opportunity for a fugitive to escape when gaps between drones are too large. The second, the SWEEP protocol, on the other hand, will work on any non-disconnected area and can work around "leakage", but is computationally quite expensive at times and requires an overview of the entire area. The DDDAS framework uses the best of Parallel Path Search and the SWEEP protocol to create a better framework, that also takes potential loss of drones into account. All in all, some very interesting algorithms already exist for the theme in mind.

Another article found describes a framework for multi-agent research. The platform used for the development of this framework were low-cost quadcopters. The demonstration of the platform on environment exploration and collision avoidance showed that the platform is decent. The largest problem is data loss when using wireless communication over larger distances. This means that the platform still needs improving to make it more robust, consistent and reliable.

A recent study has also researched the possibility to train models based on fluid dynamics. In this study a model was created (based on fluid dynamics) upon which the individual robots based their movement. The advantages and disadvantages of this approach is that the robots choose the same path a fluid particle would.

This brings with it a couple of advantages. The fluid particles (and thus the swarm of robots) always choose the path of least resistance. Every fluid particle and thus the robot behave the same as every other particle. This means that the robots do not need to be numbered, and thus is the code for every robot the same. The nature of particles also implies that the model makes use of a decentralized architecture, and that the approach is robust to the dynamic deletion and addition of new agents. The study also mentioned a couple of disadvantages associated to this approach. First of all a lot of parameters are needed for the model to be used. If these parameters are not correctly adapted at the task at hand deadlocks may occur. Another disadvantage this approach brings with it is the fact that every robot needs a complete map of the environment it is going to function in. This flaw is inherent to the decentralized structure, but is present nonetheless. Lastly, each robot needs information about its surroundings which are normally provided (in the case of the particle) by physics. The needed info is the range, bearing, and velocity of neighboring robots. The writers do remark that the requirements are consistent with multirobot path planning approaches, and are thus not necessarily disadvantageous to this particular approach.

Sensors and analysis methods

The first article belonging to the category presents a list of different sensors and camera's that are currently available for drone flight and sectors where they are used often. These consist of, but are not limited to, accellerometers, cameras (both infrared and normal) and GPS.

Another article we discovered shows the development of imaging spectroscopy in multi-temporal environments using a multitude of drones. In layman words, a way to perform analysis on a series of high-resolution photos that have been taken from different directions. This technique is quite promising and seems to perform equally to or better than other techniques.

A third article found discussed the evolution of photogrammetric and remote sensing technologies in the field of Unmanned Aerial Systems. It shows that drones are ready for use, but that large regulatory issues still have to be dealt with. However the European Union has hatched a multi-annual plan to integrate the use of drones for mapping, which would remove most current issues. It also shows that the navigation systems are generally ready, but improvement is still possible. Sensors have been developed to the point that they are small and lightweight enough to be used on drones. Additionally, the market of interested parties is growing with the day. In conclusion: additional research and technologies are defininitely required and are being conducted. We will definitely see more new UAS technologies and applications in photogrammetry and remote sensing in coming years.