PRE2017 3 Group 17 - State of the Art

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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. <ref>[https://ac-els-cdn-com.dianus.libr.tue.nl/S0262407914607545/1-s2.0-S0262407914607545-main.pdf?_tid=8320553a-0c4f-11e8-9b0e-00000aacb35f&acdnat=1518039808_a38e434108e2b128df11e71965e51fa2 Submarine drone dives into search for MH370 jet (2014) ]</ref>
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. <ref>[https://ac-els-cdn-com.dianus.libr.tue.nl/S0262407914607545/1-s2.0-S0262407914607545-main.pdf?_tid=8320553a-0c4f-11e8-9b0e-00000aacb35f&acdnat=1518039808_a38e434108e2b128df11e71965e51fa2 Submarine drone dives into search for MH370 jet (2014) ]</ref>
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Instead of avoiding collisions between drones and between drones and other objects at all costs this article proposes a collision resilient drone. This drone should survive more crashes and is still able to operate like a "normal" drone. It does this with rings around a drone body and a gimbal system allowing it to keep moving even when it hits a wall.<ref name="crashresdrone">[http://onlinelibrary.wiley.com/doi/10.1002/rob.21495/epdf A Collision-resilient Flying Robot (2014)]</ref>
== Swarm Technology ==
== Swarm Technology ==

Revision as of 12:28, 21 February 2018

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

Contents

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.[1] 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. [2] 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

Drones need a way to be controlled, so they can more efficiently perform the task they were designed to do. Since this project revolves mostly around getting visual feedback from drones, articles with that subject were sought. A recent patent about Automated drone systems [3] in automated security systems shows that companies are already busy trying to achieve with one drone what this project tries to achieve with multiple. Besides that it shows that there are systems capable of navigating one drone to a desired location, and that it has a smart way to scan surfaces.

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. [4]

Instead of avoiding collisions between drones and between drones and other objects at all costs this article proposes a collision resilient drone. This drone should survive more crashes and is still able to operate like a "normal" drone. It does this with rings around a drone body and a gimbal system allowing it to keep moving even when it hits a wall.[5]

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. [6]

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. [7]


A recent study has also researched the possibility to train models based on fluid dynamics. [8] 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.

When implementing this system on airborne drones, however, another issue occurs. Airborn drones create airflow which influences other drones. In the case of 3D model generation using airborne swarms [1], three drones where already creating enough turbulence, and thus instability to render them useless for the purposes of this project.

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.[1][9]

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.[10]

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 definitely required and are being conducted. We will definitely see more new UAS technologies and applications in photogrammetry and remote sensing in coming years.[11]

A fourth article about the analysis of the images made by the drones. Using a Fuzzy unordered rule induction algorithm the accuracy of detection of objects and type of land usage went from around 70% for the currently used methods to 90%. [12]

Another article about analysis of the footage captured by drones discusses ways to analyze crowds. This article talks more about what could be possible then what is possible at the moment using already established object recognition algorithms. These algorithms could be extended to capture things like the flow of a crowd and potential spots where people are slower which could indicate trouble.[13]

Ethics

During this project we look into the possibility of drones scanning areas, however this has no meaning if it is ethically unjust or even illegal to do so. The technological advancement of these flying objects has already sparked some debate on whether the law needs to be changed, and if so by whom. [14]

A few ethical papers were analysed to get the state of the art with respect to ethics on this subject. Unmanned aerial systems: Consideration of the use of force for law enforcement applications claims that the use of force by a UAV is allowed provided that the amount of force is not excessive. This can be achieved through the codification of a decision making model for law enforcement engagement. Since the purpose of the drones used in this project are solely capable of surveillance, they are always within the maximal allowed use of force in any situation. With regard to privacy the article proposes to obtain a warrant when it is expected that privacy will be intruded upon. [15]

All tasks drones are expected to be doing during this project would normally be done by helicopter or manual inspection, so in that case the drone just becomes a tool for a task. The underlying ethics debate is then not about the drones anymore, but about the task, which is outside the scope of this project.

References

  1. 1.0 1.1 1.2 3D Model Generation using an Airborne Swarm (2015)
  2. AutoDesk 123D Catch
  3. Automated drone systems (2015)
  4. Submarine drone dives into search for MH370 jet (2014)
  5. A Collision-resilient Flying Robot (2014)
  6. Swarm Control of UAVs for Cooperative Hunting with DDDAS (2013)
  7. Multi-agent Environment Exploration with AR.Drones (2014)
  8. Swarm coordination based on smoothed particle hydrodynamics technique (2013)
  9. Sensor solutions play critical roles in enabling innovation in drones
  10. Multi-temporal high-resolution imaging spectroscopy with hyperspectral 2D imagers – From theory to application (2018)
  11. Unmanned aerial systems for photogrammetry and remote sensing: A review (2014)
  12. Drone-based land-cover mapping using a fuzzy unordered rule induction algorithm integrated into object-based image analysis (2016)
  13. Crowd Analysis Using Computer Vision Techniques (2010)
  14. Drones In Domestic Settings Spark Debates About Privacy Often Equipped With Cameras Law enforcement uses the machines to find missing persons as well as crooks
  15. Unmanned aerial systems: Consideration of the use of force for law enforcement applications (2013)
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