PRE2016 2 Groep1

PRE2016 Q2 Group 1 - Main page Koen Damen - 0893034 Stijn de Milliano - 0816573 Ralf Reinartz - 0892456 Zjeraar Scharis - 0651925 Stefan Thijssen - 0888708 Peter Visser - 0877628 Welcome Welcome to the Wiki of the first and only group of Project Robots Everywhere 2016 Quarter 2. On this page we will keep track of our progress during the project, this way everybody can see the progress we are making and we can organize the information we have gathered. Feel free to take a look around. We have divided our progress into the separate weeks we worked on the project explaining for each week what we did, what results we got and what we plan to do with those results. Included on the bottom of each week are also the notes of our meetings in order to be able to review those.

You can click the following link for more background information on the course and the project. [1] This link leads to the studieguide that was placed on oase. Week 1 The goal of the first week was to decide on a subject for our project and what we were planning to do with this. This started on Monday with the first lecture, where we got more information about the course itself. After this we started brainstorming about different possible ideas to look into. A few examples of the things we looked at were space-exploration, robotic prosthetic and automating hazardous professions like firefighting. In the end we decided on swarm technology. We did still have to specify this so after the meeting we individually looked into some different applications of swarm technology. In the second meeting (17-11) we decided on a final subject: using swarm technology to observe the environment, focused on water like harbors and rivers. Here we want to test the quality of the water by looking at Chemicals, temperature, pH and metals. We decided on making a simulation of the system which can eventually be expanded. The next step was to figure out exactly what we need to make the simulation as realistic as possible, the USE-aspects and how we are going to approach the goal we set for ourselves. Our next meeting (19-11) was focused on combining the results we made throughout the week into a presentation that was to be given the following monday. File:Presentation week1.pdf File:Notulen 17-11.pdf File:Notulen 19-11.pdf Week 2 In week 2 we were trying to do 2 major things. First off, after receiving feedback on our presentation on Monday, we made contact with multiple organisations involved with the sanitation of water. We had contact with the sea harbor police, Greenpeace, Stichting-Noordzee and Rijkswaterstaat. A lot of these organisations could not give a specific answer to what problems our system should solve, since they always first encounter the problem which they then start solving. In the end the sea harbor police said they had a lot of trouble with drifting pieces of wood, since this can obstruct or even pierce their boats. Using this we changed the concept of our design to a point where the swarm should be able to find driftwood and push it to a place where it is not a problem (along with the previously defined tasks). This will give the system a specific user. File:Notes 24-11.pdf After this was done we started defining our tasks for the rest of the project. For this an initial Gantt-chart was already made in the first halve of the week. In the second meeting this week we distributed tasks which we then made individual gantt-charts for. In the third meeting we combined these to make one final charts which is to be presented in our second presentation. In this chart can be found who does what, when and with who they will be working together. File:Notes 27-11.pdf This same Gantt-chart is placed here on the right. In this chart every group/task has a different colour for clarity. Green = everybody Orange = Stijn Yellow = Ralf Blue = Stefan & Peter Red = Koen & Zjeraar Week 3 In week 3 every group started with their individual tasks (as described by the Gantt-chart in week 2). A complete list was made of the different contaminants we would like to investigate and how to do this using different sensors and how they could be applied. For the simulating of the swarm the Matlab application 'Multi-robot simulation' is investigated to check its functions and compatibility with our project. If these results are positive this program can be used to design our system. For the environment a map was made using a picture of the harbor of Rotterdam. A software was used to convert this into a black and white map we can use for our simulation. The resolution of this map is going to be enhanced by reducing the size of the map we use. Our contact with the external companies has not yet given results, since these contacts had either no time or did not respond at all. Detection Methods A list was made of all different contaminants we could look at for our system. After this methods were found to detect each of these. Following this list, combined with feedback of the users, a final choice can be made for which detection methods to incorporate in the final design. Wood This was explained by the sea-harbor police as a problem for them. The first option that was looked into was a Gelsight sensor, this sensor can determine what material it is pressed against by comparing its surface to a database. This would however need a drone to have already found the object in the first place. Because of this it would be better to combine cameras with recognition software to find floating objects, regardless of material. Oxygen For oxygen the most practical detection method for our system would be a dissolved oxygen sensor. For the amount of oxygen which can be dissolved in water is influenced by the factors of temperature, pressure and salinity. Because of this a dissolved oxygen sensor also has a thermometer and a barometer. Salinity The salinity is the amount of salts and similar materials in water. This is directly related to its conductivity. Because of this an electric conductivity meter can be used. pH-value The pH-value of water is a good indication of water pollution. Not only do some substances have a very low or high pH-value themselves, thus altering the value of the water when added. A low pH-value also allows (heavy) metals to dissolve more easily, making them mobile. For the pH-value a pH-sensor can be used, as the name implies. Oil spills Although a lot of pollutions can be seen visually by a person, for a drone this can be more difficult. A methods that could be applied to our system for the detection of oil can be using uv-fluorescence. This is based around oil reflecting uv-light, allowing it to be detected. Metals and organic compounds Especially heavy metals like mercury or lead or very poisonous. They are considered as some of the most dangerous pollutions possible. A method to detect them could a graphene based sensor, which is also based on electric conductivity. Another method for this could be spectrofoto-analysis. For this a light or laser is filtered and shone through a sample of water. Different materials absorb some wavelengths of the colour spectrum differently. By comparing these to a 'clean' sample the concentration of other substances can be determined. This works not only for metals but also for organic compounds like chlorine or sulfur. These machines can be quiet expansive though. Simulting the Environment Creation of 3D-space In order to create a map for our simulation, we choose to render a map of the harbor into Matlab (we choose a piece of the harbor of Rotterdam called the Botlek). To do this a map of the harbor was taken and firstly edited a bit. The resolution was enhanced, smoothed out and colour-contrast was increased. Using a special script this was then translated into black-and-white picture of the map. This script gives all coordinates of water a value of 1 and the rest a value of 0. After this the resulting Matrix was doubled in size on both axis. Space Data For the basic conditions of the environment, parameters are given to the matrix created in the 3D-space. pH/Temperature/Oxygen For each of these parameters multiple matrices are made in advance. Then the simulation picks a random value of these matrices for the value of that parameter on a specific coordinate. This is done in order to create a normal distribution and deviation, which is more compliant with reality. Current/Wind speed/Waves These parameters are made in a similar fashion as previous parameters. Every coordinate is given an appropriate value (combining multiple coordinates to give a realistic image of these factors). Again each coordinate is given a slight deviation using a normal distribution and deviation value. These matrices are again saved. Day/Night-cycle To simulate this, the black content matrix (used in the creation of the 3D space) is multiplyied with an appropriate light intensity value, changing over time. This is saved as a new matrix. Swarm system Matlab was chosen to simulate the swarm. Firstly because we are familiar with the software and coding language, and we think it is capable of what we need. Secondly to ensure compatibility, since the virtual world is also made in Matlab. We found a program called MultiRobotSimulator (MRsim) which we studied to see how we could simulate a swarm. In order to create a realistic simulation of a swarm of boatbots, it is important to understand which physical characteristics of these boatbots will influence their behavior. A list with educated guesses was made for this as part of the simulation-inventory, where these are described fully, including used sources. By choosing or comparing to off-the-shelf technology, this makes sure that our assumptions are realistic, and also makes the design-process more USE-based, specifically the entrepreneurial/market dimension. As in previous weeks, the notes of our other meetings are linked to down below: File:Notes 1-12.pdf This following link is a link to our Dropbox files for this week. There all the files we worked on can be seen to clarify anything missing from the description above. week 3: [2] Week 4 This following link is a link to our Dropbox files for this week. There all the files we worked on can be seen to clarify anything missing from the description above. Week 4: [3]