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docs: some minor editing

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docs/en/bennie.md
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@@ -6,7 +6,7 @@ My project is a drone that can scan a store shelf and determine if the represent
Several apps have been released to fight this such as Clobotics, however they all require an employee to go around manually and take snapshots. I wanted to build a system where a shop owner could simply place the drone at a starting point, click a button and have their inventory done automatically within minutes.
Since all inventory in a shop is usually on the shelves and I wanted to not have the drone rely on GPS I fitted the Clover’s pi camera in front for object detection and navigation. Rather than using map-based navigation since one can’t expect a shop owner to place markers perfectly on the ground, opencv2 has a built in ArUco marker detection method that identifies and draws a bounding box around all markers in frame. So once the drone takes off from the starting position, it identifies where the marker is in frame and uses the Clover’s `navigate()` method to center the marker and its area to place the Clover approximately 1 metre from it.
Since all inventory in a shop is usually on the shelves and I wanted to not have the drone rely on GPS I fitted the Clover’s Pi camera in front for object detection and navigation. Rather than using map-based navigation since one can’t expect a shop owner to place markers perfectly on the ground, opencv2 has a built in ArUco marker detection method that identifies and draws a bounding box around all markers in frame. So once the drone takes off from the starting position, it identifies where the marker is in frame and uses the Clover’s `navigate()` method to center the marker and its area to place the Clover approximately 1 metre from it.
What’s expected is that the shop owner places markers at every different brand’s section in ascending order down an aisle. The drone has a specific marker ID it’s looking for and once it’s centered itself on the nearest marker, it determines its ID and moves either left or right depending if the identified marker is lower or higher than the target. This way the Clover moves down an aisle stopping at each marker until it reaches the target.

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docs/en/blue_jay_eindhoven.md
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@@ -8,15 +8,15 @@ We at Blue Jay Eindhoven are a student team of the Eindhoven University of Techn
We are participating in the Copterhack 2021, because COEX has a lot of knowledge about making a drone. With the help of COEX's expertise, we would be able to develop our drone further. However, the project with which we started the Copterhack turned out to be not that successful. We therefore also didn't get to have a more in depth discussion with COEX. The fact that we are not an open source company, added to this. We couldn't just share everything and when that one project failed, we first had to look at what we are going to share next. Because of these events, the collaboration part hasn't really lifted off.
The information that you are going to find in this project summery is therefore not that specific developed for the clover drone. It can however certainly be used to customize the clover drone. In addition, it can also give a first overview for beginners on how to design a path planning algorithm and how the design process of a drone looks like.
The information that you are going to find in this project summary is therefore not that specific developed for the Clover drone. It can however certainly be used to customize the Clover drone. In addition, it can also give a first overview for beginners on how to design a path planning algorithm and how the design process of a drone looks like.
We are still planning on doing some research on the clover drone itself. This will mainly be on the stability and movability of the our drone. But we are going to start with investigating it on the Clover drone. So there might be a nice further collaboration on this. In addition, we are also trying to implement the codes for the Clover drone onto our drones. By doing this, we will also be able to provide some feedback on it and develop it further.
We are still planning on doing some research on the Clover drone itself. This will mainly be on the stability and movability of the our drone. But we are going to start with investigating it on the Clover drone. So there might be a nice further collaboration on this. In addition, we are also trying to implement the codes for the Clover drone onto our drones. By doing this, we will also be able to provide some feedback on it and develop it further.
Now we will give you a short summary of our results on the Path Planning Algorithm and the Hardware Research that we have done. For the full reports, you can go to this google drive: https://drive.google.com/drive/folders/1vfWjWD5Qx38mDta0PvMFvAv6jC-mxF7U?usp=sharing.
## Path Planning Algorithm
It is investigated what the most optimal path planning algorithm is for the clover drone. This is done since it was noted that this is not done in the base version of the drone. The path planning algorithm makes it possible that the drone flies autonomous in a much better way than without the algorithm.
It is investigated what the most optimal path planning algorithm is for the Clover drone. This is done since it was noted that this is not done in the base version of the drone. The path planning algorithm makes it possible that the drone flies autonomous in a much better way than without the algorithm.
In the documentation, we have set up a plan to put this path planning algorithm to work on your drone. This is a low level algorithm, so everyone should be able to implement it. The algorithm does however need some sort of map from which it can get information on the possible paths. So that part, you still have to implement yourselves.
@@ -24,14 +24,14 @@ In the documentation, we have set up a plan to put this path planning algorithm
The report describes the internship project carried out at Blue Jay. As we focus on indoor drone application, we wishes to minimize the produced noise to improve user experiences. On the other hand, we also wish to improve the flying efficiency for benefiting flying time. As result, the project is about making the drone more efficient with less noise emitted during the operation. For producing design to approach the problem, design methodology has been applied. In the end the ducted fan design has been chosen through studied theory and experimenting. However, there are two additional requirements, an increase in amounts of sensors and an increase in propeller numbers to increase safety. These additional requirements result the drone has less flying time due to the increase in weight. However, the selected design still improved the efficiency of selected propeller.
This hardware part is more of a general research that can be applied to all drones, including the clover drone. If a group of high school or university students would like to do their own research on the clover drone, they can use the research for ideas. They can for instance perform a project in which they design their own 3D printed ducted fans to use on the clover drone. The research in the report would then be a good first read on how to design such a thing and what the performance results could be.
This hardware part is more of a general research that can be applied to all drones, including the Clover drone. If a group of high school or university students would like to do their own research on the Clover drone, they can use the research for ideas. They can for instance perform a project in which they design their own 3D printed ducted fans to use on the Clover drone. The research in the report would then be a good first read on how to design such a thing and what the performance results could be.
In addition, the kind of propellers that are used on the clover drone can also be adjusted. Maybe a group wants get a little smaller or larger propellers or even a different shape. The research done can then also help as a guide to decide what kind would be best for that specific use with respect to size and shape.
In addition, the kind of propellers that are used on the Clover drone can also be adjusted. Maybe a group wants get a little smaller or larger propellers or even a different shape. The research done can then also help as a guide to decide what kind would be best for that specific use with respect to size and shape.
It is also useful when one wants to use the code that the clover drone uses, but also wants to develop their own drone. The hardware research can then be used as a guide on how you can do this. It states all kind of factors that should be taken into account and in what way you can do this.
It is also useful when one wants to use the code that the Clover drone uses, but also wants to develop their own drone. The hardware research can then be used as a guide on how you can do this. It states all kind of factors that should be taken into account and in what way you can do this.
## Full Project Information
To see what our project at Blue Jay is all about, you can watch the following video of our interim event: [https://www.youtube.com/watch?v=E\_8TTQN92pU&t=0s](https://www.youtube.com/watch?v=E_8TTQN92pU&t=0s). We state our user case, explain what we have achieved so far and what the plans are for the future.
If you have questions or ideas, feel free to ask! You can contact us at [info@bluejayeindhoven.nl](info@bluejayeindhoven.nl).
If you have questions or ideas, feel free to ask! You can contact us at [info@bluejayeindhoven.nl](mailto:info@bluejayeindhoven.nl).

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docs/en/dromap.md
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@@ -28,7 +28,7 @@ A questionnaire was conducted for this project to study the need for an indoor m
* The positioning system calculates the odometry data based on the laser scanner poses. This might misestimate the drone’s position with respect to the surroundings.
* The LiDAR readings could be infinite if the distance between the LiDAR and the surrounding walls exceeds the LiDAR range.
* The communication between the Raspberry Pi and the pc relies heavily on Wi-Fi. Therefore, any loss in the Wi-Fi signal would terminate the communication between the drone and PC.
* The communication between the Raspberry Pi and the PC relies heavily on Wi-Fi. Therefore, any loss in the Wi-Fi signal would terminate the communication between the drone and PC.
#### Non-technical Challenges
@@ -55,7 +55,7 @@ Furthermore, since the project employs multiple concepts related to indoor robot
## Proposed solution
DroMap project consists mainly of two major components: the drone and the drone add-on. The drone is responsible for the physical movement of the entire system. The drone add-ons consist of necessary sensors for mapping, path planning, and mounting equipment such as Raspberry Pi 4, RPLiDAR A1M8, Sonar, and range finder. The raspberry pi collects the data from the sensors. While the data is being collected by the raspberry pi, the Hector SLAM will process these data in real-time to formulate 2-dimensional maps. After that, the map will be sent wirelessly to a remote PC and visualized through RVIZ software tool.
DroMap project consists mainly of two major components: the drone and the drone add-on. The drone is responsible for the physical movement of the entire system. The drone add-ons consist of necessary sensors for mapping, path planning, and mounting equipment such as Raspberry Pi 4, RPLiDAR A1M8, Sonar, and range finder. The Raspberry Pi collects the data from the sensors. While the data is being collected by the Raspberry Pi, the Hector SLAM will process these data in real-time to formulate 2-dimensional maps. After that, the map will be sent wirelessly to a remote PC and visualized through RVIZ software tool.
![](../assets/dromap/HLA.jpg)
@@ -193,7 +193,7 @@ The following video demonstrates an autonomous maze exploration with Hector SLAM
### The physical hardware
This section illustrates the progress done regarding the hardware components. The first step done was to establish a Wi-Fi communication between the raspberry pi and the remote PC. The second step was to install the hector SLAM and robot Localization packages in the raspberry pi to visualize the maps remotely.
This section illustrates the progress done regarding the hardware components. The first step done was to establish a Wi-Fi communication between the Raspberry Pi and the remote PC. The second step was to install the hector SLAM and robot Localization packages in the Raspberry Pi to visualize the maps remotely.
#### Initial Setup
@@ -201,7 +201,7 @@ The drone is assembled and configured correctly to accomplish the autonomous map
<img src="../assets/dromap/3.jpeg" width=400 class="center zoom">
To set up the drone ready for mapping, the raspberry pi image created by COEX was installed on the micro-SD card. COEX raspberry pi image, COEX pixracer image and COEX virtual machine were selected as they contain all the necessary tools and packages to work efficiently with clover platform. The installed platform is based on Raspbian operating system and ROS. After flashing the image on the SD, the next step is to connect clover to Wi-Fi.
To set up the drone ready for mapping, the raspberry pi image created by COEX was installed on the micro-SD card. COEX Raspberry Pi image, COEX pixracer image and COEX virtual machine were selected as they contain all the necessary tools and packages to work efficiently with clover platform. The installed platform is based on Raspbian operating system and ROS. After flashing the image on the SD, the next step is to connect clover to Wi-Fi.
#### Network Setup