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* Add our own project - m4, edit m4-index.md

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* M7 - Added TBA section for presentation video and small text changes

Co-authored-by: Marvin Kullick <mkullick@web.de>
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Sabrows and Rein3ke authored Jul 12, 2021
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Expand Up @@ -13,6 +13,12 @@ team = ["Adrian Sabrowski", "Marvin Kullick", "Konrad Ukens", "Julian Bechthold"
supervisor = "Tamara Voigt, Martin Steinicke"
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{{<section title="Our presentation">}}

(_To be revealed at the Showtime, on July 16th._)

{{</section>}}

{{<section title="Summary">}}


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Expand Up @@ -55,13 +55,13 @@ Distractions
---


Following our data collected both from industry and scientific publications, as well as field research (interviews, user testing, workshop visits), we learned that distractions pose one of the largest sources of danger when operating machines.
Following our data collected both from industry and scientific publications (see [Process](../process)), as well as field research (interviews, user testing, workshop visits), we learned that distractions pose one of the largest sources of danger when operating machines.
In consideration of the various directions we could take our project in, we decided to develop a system of distraction events that could be used while a user is performing tasks in the simulation.
Our research gave us a number of ideas from which we chose a selection based on feasibility (development complexity and time to create) and expected effectivity (potential to distract users).

- **Custom Event System**

In terms of dynamically triggering distractions at runtime, we created a system that follows the **Observer design pattern**.
In terms of dynamically triggering distractions at runtime, we created a system that follows the [Observer design pattern](https://en.wikipedia.org/wiki/Observer_pattern).
From the implementation perspective, this means that we have defined certain areas in the virtual workshop in which distractions can take place, the so-called hotspots.

Every hotspot is also a listener to any kind of incoming event.
Expand Down Expand Up @@ -123,7 +123,7 @@ One approach to calculate the positions of a chain of joints (like the human arm
Through it, given a set of rotations for joints connected by individual bones, the final position of that chain can be computed.

The problem consisted in not having access to the rotation of each joint in our player's body, but only the positions and rotations of the tracked VR headset and their two VR controllers.
Another mathematical approach to calculate joint-chain-movement, given the position of the final joint, is called **inverse kinematics (IK)**.
Another mathematical approach to calculate joint-chain-movement, given the position of the final joint, is called [inverse kinematics (IK)](https://en.wikipedia.org/wiki/Inverse_kinematics).
With the help of one of the newest and most optimized IK-solver algorithms, called [Forwards and Backwards reaching Inverse Kinematics (FABRIK)](https://www.researchgate.net/profile/Andreas-Aristidou/publication/273166356_Inverse_Kinematics_a_review_of_existing_techniques_and_introduction_of_a_new_fast_iterative_solver/links/54faeca10cf20b0d2cb8782b/Inverse-Kinematics-a-review-of-existing-techniques-and-introduction-of-a-new-fast-iterative-solver.pdf#page74),
this challenge was overcome.

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Expand Up @@ -79,12 +79,14 @@ Lastly, performance optimizations would allow for a smoother overall experience.

{{<section title="Resultant Questions and Next Steps">}}

If the project is to be continued by a dedicated team and regular communication and collaboration with workshops can be guaranteed, we consider the following questions to give guidance for an integration within apprenticeships:
In order to consolidate the first findings and to determine the most effective integration within apprenticeships, we consider the following questions to be relevant:

- Short term (e.g. single use), such as our first semester sandbox mode vs. long term use, such as our new challenge mode (and extensions thereof)? Challenge mode for single time use vs. sandbox mode for repeated use? What integration makes the most sense?
- Which setting provides the highest benefit: short term (e.g. single use), such as our first semester sandbox mode vs. long term use, such as our new challenge mode (and extensions thereof)?
Group setting as an additional extrinsic motivation factor vs. the current single player experiences?
- Extending the previous question: how could an integration in the apprenticeship educational curriculum maximize learning benefits? What would the use context look like?
- What differences with metal workers with varying experience must be considered? Can the delivery of fresh lessons for trainees be combined with a refresher for those already experienced in the workshop?

Next steps are already planned: a follow up test session at the HTW workshop to further prove or disprove our current findings. Additionally the Berliner Stadtreinigungsbetriebe (BSR) expressed their interest to try out our application.

Next steps are already planned: a follow up test session at the HTW workshop to further prove or disprove our current results. Additionally the Berliner Stadtreinigungsbetriebe (BSR) expressed their interest to try out our application.

{{</section>}}
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Expand Up @@ -80,7 +80,7 @@ Based on the data we collected, we improved on almost all new aspects of the pro
Although we were not able to observe a reliable effect on injuries, our distractions and user tasks were positively received by the trainers, confirming that we were moving in the right direction.

Our preparation for the second and final user test of our prototype counted three large topics: improvement of the previously tested features, the finalization of our user avatars, and how to adapt our user test setup to maximize data collection.
Within the three weeks we had, our distractions were finalized, additional tools to improve the user task were created and added, and we integrated two fully rigged user avatars.
Within the three weeks we had, our distractions were finalized, additional tools to improve the user task were created and added, and we integrated two fully rigged and animated user avatars.
The test we outlined included a scientifically standardised questionnaire for Avatar Embodiment investigation, questions to compare returning testers' experiences (from the first semester), and specific questions related to our new features.


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