Difference between revisions of "PRE2017 3 Group 17"

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(→‎Approach & Milestones: Updated the Milestones)
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=== Approach & Milestones ===
=== Approach & Milestones ===
# Have concrete idea.
# Have concrete idea.
# Have a basic model (single floor, all obstacles at same height).
# Have a basic model. This model will show the basic interface and will not be interactive and only features one drone.
# Have a advanced model (multiple floors, all obstacles at same height).
# Add interactivity to the simulation to test the dynamic components.
# Take obstacle height into account.
# Add walking humans.
# Detect and avoid other agents (other drones / humans).
# Upgrade the simulation to multiple drones.
# Upgrade the model to use one way locks or other optimizations.

=== Deliverables ===
=== Deliverables ===

Revision as of 11:11, 12 March 2018

Members of group 17
Eric Arts1004076
Menno Hofsté0996144
René Nijhuis0912331
Erik Takke1000575
David Tuin1013331

Construction drones

Project Details

Problem Statement / Subject explanation

In building projects it happens quite often that objects are too large to be carried by man and have to be brought to their desired spot by crane. However, often the construction has advanced to the point that cranes can no longer reach said spot, creating a problem. This problem is usually solved by using all different types of transportation to get the object to its spot. These different types of transport, and especially transitioning from one to another, takes a lot of time. To reduce this, it would be desirable to have a single means of transport that can carry the object to its final resting place fast in one, smooth go.

One means that comes to mind are drones. Despite currently not being able to carry much weight, technology is catching up and has started to develop stronger drones. All that is left is to manoeuvre the drone, lifting the object, through the building. Even though it would be possible to have the drone be steered by a human, it would be faster, safer and cheaper to have the drones to it by themselves. Therefore we want to develop a piece of software that can guide the drone(s) through the building and have them deliver the object themselves. It is the aim to have the drones evade obstacles (walls and scaffolding), navigate between floors (flying through elevator shafts or stairwell) and detect humans and stop or evade them, depending on what is safer. All to have the drone reach its destination.

To reach this goal, a proper problem statement has been constructed: How to move large objects through buildings that are under construction, using drones.

This subject uses ideas and resources from the robotics field (drones) and also accommodates all USE parts: The solution would be interesting for enterprises. Additionally, the drones can lead to hazardous situations for users and bystanders (society), adding an ethical touch to it.


As can be read in #Problem Statement / Subject explanation, it is our goal to create software that can guide object carrying drones through a multi-floor construction site. To reach this goal, several objectives can be set to clearly see the progress that is made over the weeks.

Find path

The system will be equipped with a rough layout of what the construction zone looks like. Based on this rough layout, the system has to be able to find a path that will bring the drone from its starting point to its destination. As the path does not just have to be a 2D but rather a 3D route, this will be quite the challenge to create.

Evade objects and agents

However, just like in every construction zone, obstacles (such as scaffolding) will be moved constantly, making for a dynamic environment. Therefore it will be necessary for the algorithm to adjust its path on the fly, evade objects/obstacles and still find a path to its destination. Additionally, if the idea were to catch on, it would be possible form multiple drones to simultaneously bring objects to different destinations. To prevent the drones from flying into each other, they will have to be able to detect and evade each other. The same can be said for humans: construction workers could potentially be walking all over the place. To prevent them from getting hit and be injured, the drones will have to be able to detect them and stop/evade them.


In this paragraph a typical USE-case will be described. The setting is a construction site. This hypothetical case is based on feedback we got from the interviews we did with construction workers. During the first interview it became apperant that construction workers rarely lose their tools, for instance their hammer. The man mentioned that the project would, however, be useful for bringing supplies, for example a silicone kit. The current most popular solution, as reflected by the interview, is to do some other work until you have your next coffee break. In the next couple of lines the point of view from a construction workers will be pictured.

Imagine you are a construction worker, doing what construction workers do. You are at the 11th floor of the Atlas building with all your hammers, power tools and silicone kit. The task at hand is using your silicone kit to fill holes between two mounted objects. However, after an hour of using said silicone kit, it starts te become empty.

Now, you have a couple of options:

  • Somebody needs to drop a few cans on the elevator
  • You do something else in the time between now and your next break
  • You use the new app

Since there is only one elevator, occupying it with only a couple of cans of silicone kit is not desired. So for the sake of argument, you choose to use the app.

In the app you can see the inventory of the construction site storage, neatly organised. From here you select the silicone kit, the app says it is available through drone delivery. You choose an appropriate time you want it delivered, in this case ASAP. By the time you are done with your current kit, the drone with the next kit is already arrived and you can swiftly continue your work, while the drone goes back to its place in the storage. This way you avoided having to search for other work you have to do between now and your next break. Also, you can continue your workflow leading to no loss of efficiency at all.

The usecases are based on short interviews with some construction workers at the Atlas building. The complete interviews can be found in PRE2017 3 Group 17 - Interviews.


  • The drones move in unison.

Users and what do they require?

  • Construction companies
    • The drones will have to be able to have sufficient lifting power.
    • The drones will have to operate by themselves
    • The drones will have to be able to detect and avoid all living agents.
    • The system has to adhere to safety regulations.


To make sure the simulation can give a proper insight on whether the program works there are some requirements which is must be able to do:

  • Drones detect everything the simlation does not directly pass information to the program
  • The are people walking around the drones have to deal with
  • Walls and floors can be added or removed so the pathing has to change
  • No-fly zones can be added dynamically for example if there are people working somewhere
  • Drones are not perfect
    • Speed is variable and
    • Detection might take some time
    • They can fail

Approach & Milestones

  1. Have concrete idea.
  2. Have a basic model. This model will show the basic interface and will not be interactive and only features one drone.
  3. Add interactivity to the simulation to test the dynamic components.
  4. Add walking humans.
  5. Upgrade the simulation to multiple drones.
  6. Upgrade the model to use one way locks or other optimizations.


The goal is to create software to have the drones fly by themselves. In the end we will deliver two things. First of all, an algorithm that finds a path through the building that is under construction and can adjust its path in dynamic situations. It is our goal to create this software as realistically as possible, preferable to the point that it could be used in a real life situation. Second, to show what we have accomplished, certain example situtations will be created. For these situations, the algorithm output will be explained. This should give a clear view of what the developed software is capable of.

Who does what?

Monday 5th of March 2018:

  • David Tuin: Working on the model
  • Menno Hofste: Thinking of USE cases, and updating Wiki.
  • Rene Nijhuis: Updating SOTA with information required by our project.
  • Erik Takke: Creating interview and interviewing construction workers.
  • Eric Arts: Creating interview and interviewing construction workers.

Thursday 8th of March 2018:

  • David Tuin: Working on the model
  • Menno Hofste: Creating test cases
  • Rene Nijhuis: Writing input parser
  • Erik Takke: Creating CSV files from test cases to be parsed
  • Eric Arts: Creating test cases and creating CSV files

Monday 12th of March 2018:


State of the Art

To keep this wiki clutter free, the page PRE2017 3 Group 17 - State of the Art has been created, containing several articles that support the attainability of this project.


Coaching Questions Group 17