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In pursuing this Design Objective, four different collaboration patterns to implement the three dimensions of collaboration described above were defined
In pursuing this Design Objective, four different collaboration patterns to implement the three dimensions of collaboration described above were defined
Choosing together: in order to select an object, touch by some or all of the users interacting with the system is required (e.g., pressing a button together). This realizes the Joint-Performance dimension. <br>
# 1. Choosing together: in order to select an object, touch by some or all of the users interacting with the system is required (e.g., pressing a button together). This realizes the Joint-Performance dimension. <br>
Constraints on objects pattern: collaboration that is required because of explicit constraints on an object; for example, an object is too heavy and the children cannot drag it on their own. This realizes the Joint-Performance dimension.<br>
#2. Constraints on objects pattern: collaboration that is required because of explicit constraints on an object; for example, an object is too heavy and the children cannot drag it on their own. This realizes the Joint-Performance dimension.<br>
Different role pattern: collaboration that is required because the individuals have been assigned to play different roles; for example, a driver who needs to focus on driving while a navigator checks a map. This realizes the Sharing dimension. <br>
#3. Different role pattern: collaboration that is required because the individuals have been assigned to play different roles; for example, a driver who needs to focus on driving while a navigator checks a map. This realizes the Sharing dimension. <br>
Ownership pattern: collaboration that is required because the participants have ownership of different objects that need to be negotiated. This realizes the Mutual Planning dimension
#4. Ownership pattern: collaboration that is required because the participants have ownership of different objects that need to be negotiated. This realizes the Mutual Planning dimension


=== Nao ===
=== Nao ===

Revision as of 11:00, 13 March 2017

Using Robots to Help Autistic Children
Project Robots Everywhere

For the final course of the use learning trajectory of Robots Everywhere students work in groups to create a robot design.
Combining scientific knowledge with social knowledge and taking into accound the USE aspects, it is a perfect application to finish with.

Robots.png


List of Participants

Roxanne Boehlé Bo Drummen
Jolijn Hesen
Rachel Roumans
Sietske Wijffels
Fenna Wit

Technique on Heels


Problem Description

Autism.jpg

Our group acknowledged that therapy for autism based on robot is developing rapedly. For these therapies different kinds of robots are used and each robot has another approach.
Autistic people take a look at the world differently. They have a mysterious complex impairment in social interaction and communication.
Children with autism struggle with social skills. A robot would be a good solution, because they have infinite patience and do not judge.


Project

In this project we want to face the state of art of this sort of autism therapy specialised for children.
We want to study possibilities in helping these autistic children. We want to get a clear view of what a robot can do for autistic children by analysing existing robots and other autism research, keeping user and society in mind. And finally, we want to design a game that is suitable to help autistic children. This game should make use of a robot and help the child to develop the skill of teamwork.

Objectives

Our main objective is to make sure children with autism can smoothly integrate in society, by improving their social skills with the help of robots.

objective 1; Recognize facial expressions
objective 2; Achieve skills in teamwork
objective 3; Responding appropriately to different kinds of behaviors
  1. Turn taking
  2. Gaze behavior
  3. Show interest
objective 4; Adapt to changes in the environment

We want to focus on objective 2, and create a game that encourages teamwork

State of the Art

ZECA:

ZECA robot ("Author Archives", 2017)

ZECA stands for Zeno Engaging Children with Autism. Zeno is smaller humanoid looking robot that can display facial expressions. ZECA can either be sad, happy, scared, surprised, angry or neutral. In a study (Costa et all, 2013) it was found that adults and typically developing children could identify Zeno’s facial expressions and gestures which intent to convey emotion. So, Zeno can interact with children through nonverbal communication such as body movements and facial expressions. This speeds up diagnosis and perhaps it can even enable it to be carried out before a child can talk(Tucker, 2015).
Dr Dan Popa at the University of Texas at Arlington (Tucker, 2015): The idea is for the robot to instruct kids, give them some useful social skills and at the same time observe their reactions and calculate their reaction times. That calculation could form some kind of an autism scale.” Zeno has three modes in which it can be used (Tucker, 2015). Scripted mode of interaction. Here pre-programmed sequences of motions are performed by Zeno. Wizard of Oz mode. In this mode an operator or therapist can control the robot by tele-operations. In this mode, Zeno mirrors the motions of the instructor. In the third mode, the child can take control of the robot. However, this could be unsafe, because for both the child and the robot. So this mode is intended for entertainment only.

In another study (Torres et all, 2012), researchers were able to achieve human-robot interaction through mimicking behaviors between Zeno and humans. Zeno was given smooth motion that resembles human-like movement, taking into consideration that Zeno has a lower number of degrees of freedom compared to humans. The ability of having smooth motion contributes to the human-likeness of a robot. With the algorithms for smooth motion, Zeno was introduced to one child with ASD and his reaction was positive. The child was immediately attracted to Zeno and was tentative and responded to the instructions given through him.


In another study (Salvador et all, 2015), researches compared the ability to recognize emotion of children diagnosed with autism with those of typically developing children. They looked at the effect of incorporating gestures to the emotion recognition accuracy in both child groups. No indication of a significant impairment in the general emotion recognition of the autism group was found. However, a specific shortfall in correctly identifying fear was found for the autism group when compared to the TD children. Furthermore, it was found that gestures can significantly impact the recognition accuracy for both children with autism and typically developing children. This is either in a negative or positive way depending on the specific expression. This study concluded that the use of gestures for conveying emotional expressions through a humanoid robot is relevant in a social skill therapy setting.

NAO ("Wiki Therapist", 2017)

WikiTherapist

The WikiTherapist project aims to promote embodied interaction through interfaces that are able to develop an understanding of the intent of the natural movement of the human body. The movements are then simulated on robots as part of games. These games aim to improve the social interaction skills of children with ASD. The WikiTherapist project strives for a framework which enables the expression and interpretation of patterns of emotional movement (Costa et all, 2013).
The WikiTherapist project uses the humanoid robot NAO as an assistant in their behavioral therapies for children with autism. The NAO robot can engage with people in interactive behaviour through movement, speech, basic facial expressions and touch (Gillesen et all, 2010). So far, the NAO robot is able to recognize simple instrumental and emotional movements based on emotional primitives (Barakova et all, 2009). Furthermore, NAO is able to perform some complex movements. However, interaction scenarios with autistic patients is still in its developing stages.
The goal of the WikiTherapist project is to create a web based community of therapists and robot practitioners who co-create robot behaviors and scenarios of all types of complexity ("Wiki Therapist", 2017).
Furthermore, the WikiTherapist project strives to simplify the programming environment for therapists who will use WikiTherapist as a platform. This is realized through developing techniques to program robotic systems by demonstration of the desired behavior. This is called imitation learning. Imitation learning reduces the complexity of robot programming for therapists. Moreover, the developed imitation learning techniques can also be used as a training tool in the therapy sessions for children with ASD (Gillesen et all, 2010).


The current FACE robot, developed by Hanson Robotics (Mazzei et all,2010)





FACE

FACE stands for Facial Automation for Conveying Emotions. FACE is a humanoid robot which is able to express and convey emotions and empathy in order to help autistic children to better deal with emotional and expressive information. FACE is used in combination with a therapeutic setup comprising a sensorised shirt, video cameras, and an eye tracking hat (Mazzei et all,2010). Subsequently, FACE integrates the therapeutic adaptive information derived from sensors used on children and in the surrounding environment. This information allows FACE to harmonize its own expressions and movements with the feelings of the user, through control and data processing algorithms (Costa et all, 2013).


robot bandit (Scassellati et all, 2012)



Robot Bandit Project

The robot Bandit project aims at facilitating human robot interaction in a natural way, subsequently increasing interactions of children with autism.
A sound speaker is mounted on the robot which allows the robot to play pre-recorded vocalizations. These communicate the emotional state of the robot (e.g., happy or confused).
It was found that more verbal children showed more interest, but also had more expectations for the social capabilities of the humanoid robot(Costa et all, 2013).
Bandit has two degrees of freedom. One in the mouth and one in each to the eyebrows. This allows the robot to have limited facial emotion expression without being biologically faithful.
Bandit can also turn its head from side to side and has six degrees of freedom in each arm. This allows him to indicate “no” and do pointing and make gestures (Scassellati et all, 2012).




KASPAR

KASPAR is designed in the UK by the University of Hertfordshire’s Adaptive Systems Research Group. He has the size of a small child. Unlike robots like Zeno and Milo, Kaspar has a neutral expression so that children can interpret him how they wish. (Tucker, 2015). KASPAR is used in tactile interaction scenarios with children with autism. KASPAR responds differently(e.g. happy or sad), depending on the way he is touched. KASPAR has a realistic face with significantly little actuation: It has two degrees of freedom in the mouth (open/close and smile/frown) and three degrees of freedom in the eyes (up/down, left/right, and open/close the eyelids). According to its designers, KASPAR’s minimally expressive face reduces its complexity as a social stimulus (Scassellati et all, 2012).
With KASPAR’s ability to provide immediate feedback to a child’s touch, it provides appropriate teaching considering physical social engagement. It reinforces suitable behaviors for tactile interaction with another agent. Despite seeing no significant differences when evaluating the tactile interaction in a study, more than 90% of the times the children touched the robot gently (Costa et all, 2013)
In an exploratory study (Costa, Lehman et all, 2013) children with autism interacted with KASPAR. The study investigated robot-assisted play, here KASPAR acted as a social mediator. The study aimed to increase body awareness with tasks that taught children about the identification of human body parts. It was found that children were to have a lot of interest in touching the robot, that the children started looking to the experimenter for a longer period of time and that KASPAR could prolong the attention span of the children. An evaluation by teachers of the children participating in the experiment showed (Costa, Lehman et all, 2013), that they improved their ability to identify parts of the their body with their own hands. Additionally, some of the children that initially were not able to identify any of the body parts on themselves, showed an improvement of their knowledge.
In another recent study (Huijnen et all, 2016) researchers were looking at the potential contribution of KASPAR to the therapy and/or educational goals for children with autism. For this the researchers asked professionals and practitioners in the field to fill in online questionnaires and participate in focus groups. It was found that professionals expected KASPAR to be of added value to autism objectives like ‘communication’, ‘social/interpersonal interaction and relations’, and ‘play’, but also in objectives related to ‘emotional wellbeing’ and ‘preschool skills’. A top 10 (Table 1) was created of professionals’ expectations of potential added value for robot KASPAR for working on therapy and educational goals for children with autism.

table 1 (Scassellati et all, 2012)

Kaspar


Kismet ("Can Robots Feel Your Pain?", 2017)


Kismet

Kismet engages people in expressive social interaction. Kismet perceives a variety of natural social cues from visual and auditory channels, and delivers social signals to people through gaze direction, facial expression, body posture, and vocalizations (Breazeal, 2000). In a study (Costa et all, 2013), the creators studied how children reacted to the robot when it generated a variety of social gestures and facial expressions in response to stimuli from the child. The result consisted of an ongoing turn-taking between robot and human.

MILO

Milo is a humanoid robot that engages with children with autism through research-based lessons that teach social behaviors. Milo is meant as a social mediator for educators, therapists and parents. Milo can teach children to understand the meaning of emotions and expressions, and demonstrates appropriate social behavior and responses ("Robots4Autism", 2017). Recent research ("Robots4Autism", 2017) has shown that children working with a therapist and Milo are engaged 70-80% of the time compared to just 3-10% of the time with traditional approaches. It was found that children want to work with Milo again and again which increases their opportunities to learn and their developmental success.
Milo looks very similar to Zeno from ZECA. Milo’s expressive face is one of his most important features. Children with autism are asked to identify the emotion shown by Milo from multiple choices on an iPad. Milo’s eyes are cameras, recording feedback. The child wears a chest monitor that records changes in heart rate. This allows Milo to identify the child’s changes in emotion (Tucker, 2015). What seems to be unique about Zeno and Milo is the way that their expressiveness defies long-held robotic conventions. They could eventually have an impact far beyond the diagnosis and treatment of autism. The inventors, RoboKind, envision a broader role for their robots in educating young children.(Tucker, 2015)




Leka: Uses expressions, sound, light to interact
Zeno: Expressive face, focused on emotions
zeno

Theory

Autism

Autism spectrum disorders (ASDs) are a class of neurodevelopmental disorders defined by impairments in social functioning and communication, often accompanied by repetitive and stereotyped patterns of behaviour and interests [1]. The impairments typically occur before 3 years of age. ASD include the diagnostic categories of autism, Asperger’s syndrome and PDD-NOS. ASD is pretty common: around 1 in 150 children [1] and even more than 1% of the population of The Netherlands (approximately 190.000 people) are diagnosed with an ASD [2].

Signs and symptoms

ASD has a wide range of signs and symptoms. There a two main types of behaviours according to the National Institute of Mental Health (NIMH) [3]: restricted/repetitive behaviours and social communication/interaction behaviours. Examples of the first type of behaviours are: repeating certain behaviours or having unusual behaviours, having overly focused interest, such as with moving objects and having a lasting and intense interest in certain topics, such as numbers or details. Examples of the second type of behaviours are: getting upset by a slight change in routine, atypical language development, poor nonverbal communication skills and having facial expressions that do not match with what is being said.

Therapies

To assist people with ASD, therapies are often already started at a young age. These therapies necessarily involve a team of people. At the Brigham Young University Comprehensive Clinic, this team includes a primary and a secondary therapist, a therapy supervisor, and the child’s caregivers [4]. As stated by Marwecki et al., ASD are not curable. The main goals of therapy are to decrease the symptoms, help affected persons to accept their situation, and provide support for their families. Through behavior therapy, desired behaviors can be conditioned and develop strategies for overcoming his or her deficits. [7]

Therapies with robots

Nowadays, more and more research is done in therapies with robots to help children with ASD. Mostly, if not all of them, show positive results. Below you can read about several robots that are already tested with autistic children. Important to note is that social engagement with a robot is not a goal but rather a means for helping autistic children interact socially with other humans [4]. Although we know that involving robots in such therapies is beneficial, there are no clear conclusions yet on why these robots succeed in establishing social engagement. However, Scassellati et al. stated that there are a couple of hypothesis why robots generate prosocial behaviour in many children [5]: Perhaps the simplified social cues that robots present result in less overstimulation of the children; perhaps robots offer more predictable and reliable responses than those from a human partner with ever-changing social needs; perhaps robots trigger social responses without the learned negative associations that some children have with human-human interactions; perhaps the exaggerated prompts at robots provide are better triggers for social behaviour than the nuanced and subtle social prompts from a human partner [5].

Requirements robots

Research that was based on the three-way interaction of the child, clinician and robot found that robots that autistic children favour robots that do not look too much like real humans [6]. However, it is suggested that the children can generalize what is learnt better if the robots are more humanoid. This leads to the suggestion that it would be beneficial if robots could change appearance throughout the therapy. In a conference paper of October 2010 [6] were suggested a couple of robot specifications: the robot must be robust, easy programmable, affordable, and appealing to children with autism in order to be useful in therapy.

Collaboration definition

Scientific article Giusti, L., Zancanaro, M., Gal, E., & Weiss, P. L. T. (2011, May). Dimensions of collaboration on a tabletop interface for children with autism spectrum disorder. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (pp. 3295-3304). ACM. --In this article the authors state objectives for creating a game that improves collaboration skills for autistic children: One of them is:
Embed specific interaction mechanisms to foster and promote collaboration between children.
They defined three key factors in collaboration:
1. Joint Performance: Collaboration is the performance of an action together (e.g., moving heavy objects together).
2. Sharing: Collaboration is the sharing of personal resources to achieve a common objective.
3. Mutual Planning: Collaboration is the elaboration and performance of a joint plan; if we want to solve the problem we have to coordinate our actions and our resources.

In pursuing this Design Objective, four different collaboration patterns to implement the three dimensions of collaboration described above were defined

  1. 1. Choosing together: in order to select an object, touch by some or all of the users interacting with the system is required (e.g., pressing a button together). This realizes the Joint-Performance dimension.
  2. 2. Constraints on objects pattern: collaboration that is required because of explicit constraints on an object; for example, an object is too heavy and the children cannot drag it on their own. This realizes the Joint-Performance dimension.
  3. 3. Different role pattern: collaboration that is required because the individuals have been assigned to play different roles; for example, a driver who needs to focus on driving while a navigator checks a map. This realizes the Sharing dimension.
  4. 4. Ownership pattern: collaboration that is required because the participants have ownership of different objects that need to be negotiated. This realizes the Mutual Planning dimension

Nao

Nao is a personalizable and interactive humanoid robot that has been evolving since 2006. A French company named Aldebaran Robotics are the makers of the Nao Robot. Currently Nao is in its 5th version. It is 58 centimeter in height and it weights 4.3 kilograms. Nao is controlled by NAOqi, a Linux-based operating system. With the robot comes a software suite which includes a graphical programming tool Choregraphe.

Functions

Nao can speak up to nine different languages. He is able to detect and recognize faces. He is able to recognize speech and understand what people say and his sensors and camera are albe to sense the environment very well. Nao is mainly used for entertainment purposes. He can play songs, talk with people or show them how to do their exercises. Therefore Nao is used as a help for physiotherapists for example.

Limitations

Nao is not able to walk very fast, because he will fall down if he does this. Beside that it is quite hard for Nao to pick up objects because his hands are not too powerful and he is not able to move his fingers seperately. Since we are not experienced with programming the Nao robot, this is also a limitation for us. We will have to stick to using the Choregraphe tool and use the movements and actions from that tool. These include standing up, sitting down, walking, talking, waving and some dances and other basic movements. And it is able to read data from the sensors.

Game Concepts

Requirements

Requirements of the Game:
- Teamwork is needed to reach the goal, the participants need each other in the game
- The game is understandable for children of age seven till nine
- The goal of the game is clear

Requirements of the Robot:
- The robot is able to recognize speech of the player.
- The robot is able to recognize faces, so that it can distinguish the different players.
- The robot is able to communicate with the participants by verbal communication.

Approach

Our approach containes doing literature research to see what is out there and what not, mostly focusing on what is not.
Then, we plan to talk to specialists and/or parents with children with autism, to see what is needed or what they would look for in a robot.
If possible, we would like to integrate these needs in a game which could be programmed in a robot.

USE

User

Society

Enterprise

Week 1

Problem definition

In week 1 we got the first lecture of the course. During the lecture an overview of the course was given. Then, groups were formed and during our first meeting we brainstormed about possible robot technologies we could use as our subject. We created a mindmap with several branches of interest. After eliminating most of them, were hesitating between robots for children with autism, robots for rehabilitation purposes and a persuasive dieting robot.
We ended up choosing robots for children with autism. At the end of the meeting we scheduled another meeting for which each of us had to come prepared by looking up literature on our topic.

During the second meeting we further elaborated on the subject. Where we wanted to go and what we already knew about current technologies involving children with autism. We talked about our objectives and the approach.

Week 2

In the second week we continued with the literature study, to get a good view of the state of the art. And we searched for the answers on the following questions:
- What is autism?
- Why can robots help children with autism?
- Which social skills are important for teamwork?

Via our literature study, we wanted to find out the things that already exist and which things are missing in the research field. We found out that there are already several robots that help children to learn to recognize facial expressions or that learn children how to react on different kinds of behavior. We concluded that another important social skill that autistic children find hard to develop is teamwork and that robots could help them during the development of this social skill. So this is the social skill we will focus on.

Now we will interview specialists in this field to gather more information about the topic and finally we want to create our own game with Nao that can help autistic children to develop their teamwork skill.

Week 3

Interview with Barakova

In week 3 we held a meeting with Emilia Barakova, in which we asked some question about her research. She suggested some possibilities for our game. Thursday we will discuss her suggestions and determine which sort of game we want to develop.


File:Transcriptie.pdf

Week 4

For this week all of us came up with a game idea. We discussed those ideas, but could not make a decision yet. Then we had our first meeting with the tutors. They advised us to set up the requirements of the game and check which of the games satisfy the requirements, so we can pick one.

On Thursday we concluded that none of the games completely satisfied the requirements. And so the next task is to find a solution for each of the games so that it could work.

Week 5

Everyone came up with a solution and we discussed the new game ideas. We are still doubting about which one to choose. After the tutormeeting the tutors advised us to make a table with the game ideas and the requirements and put checkmarks in it. The game with the most checkmarks will be selected.


References

  • Barakova, E.I. & Lourens, T. (2009). Mirror neuron framework yields representations for robot interaction. Neurocomputing, 72(4-6), 895-900.
  • Breazeal, C.: Sociable machines: Expressive social exchange between humans and robots. PhD thesis, Massachusetts Institute of Technology (2000)
  • Costa, S., Soares, F., & Santos, C. (2013). Facial expressions and gestures to convey emotions with a humanoid robot. Paper presented at the , 8239 542-551. doi:10.1007/978-3-319-02675-6_54
  • Costa, S., Lehmann, H., Robins, B., Dautenhahn, K., Soares, F.: Where is your nose?-developing body awareness skills among children with autism using a humanoid robot. In: The Sixth International Conference on Advances in ComputerHuman Interactions, ACHI 2013, pp. 117–122 (2013)
  • Gillesen, J., Boere, S., & Barakova, E. (2010). wikitherapist. Paper presented at the 373-374. doi:10.1145/1962300.1962390
  • Huijnen, Claire A. G. J, Lexis, M. A. S., & de Witte, L. P. (2016). Matching robot KASPAR to autism spectrum disorder (ASD) therapy and educational goals. International Journal of Social Robotics, 8(4), 445-455. doi:10.1007/s12369-016-0369-4
  • Mazzei, D., Billeci, L., Armato, A., Lazzeri, N., Cisternino, A., Pioggia, G., Igliozzi, R., Muratori, F., Ahluwalia, A., De Rossi, D.: The face of autism. In: The 18th IEEE International Symposium on Robot and Human Interactive Communication, RO-MAN 2010, pp. 791–796 (2010)
  • Salvador, M. J., Silver, S., & Mahoor, M. H. (2015). An emotion recognition comparative study of autistic and typically-developing children using the zeno robot. Paper presented at the 6128-6133. doi:10.1109/ICRA.2015.7140059
  • Scassellati, B., Admoni, H., & Matari, M. (2012). Robots for use in autism research. Annual Review of Biomedical Engineering, 14(1), 275-294. doi:10.1146/annurev-bioeng-071811-150036
  • Tucker, E. (2015, February 01). How robots are helping children with autism. Retrieved February 22, 2017, from https://www.theguardian.com/lifeandstyle/2015/feb/01/how-robots-helping-children-with-autism
  • Torres, N., Clark, N., Ranatunga, I., & Popa, D. (2012). Implementation of interactive arm playback behaviors of social robot zeno for autism spectrum disorder therapy. Paper presented at the 1-7. doi:10.1145/2413097.2413124


Appendix

Planning


Planning

To make sure that we manage our project in the best possible way we made a planning in which we incorporated everything we wanted to do. At the end of the eight weeks of the project we want to have two deliverables a literature study and our own game.
Since the knowledge of the literature study is needed to develop a game, we decided that the literature study had to be finished by the end of week 3. This is also our first milestone.
There are a couple of reasons why we first want to do a literature study. Firstly, we want to have a good and complete overview of what is already developed and what researches have already done. Our goal is to develop a new game and not to duplicate or further develop an existing technology. Secondly, this gives us a good idea which niches we have to further investigate for our own game. This is a lot of work but should be feasible within 3 weeks.
The second part of our research will be qualitative research. More specifically: interviews with specialists. The first one to interview is Emilia Barakova. We thought it would be nice if we could speak to her as soon as possible since she has done of research about this topic as well. That is why we planned an appointment with her at the beginning of week 3. Of course we also planned in some time to prepare the interviews and to transcribe and code them. This should be finished by the end of week 5.
With the knowledge of the literature study and the interviews we can develop our own game. This last phase will consist of a design phase and a realization phase. We planned to start this phase already at the beginning of week 3, because by that time we will already have sufficient knowledge to take the first steps in our design. The design should be finished by the end of week 7. This is our second milestone. The last week will be reserved for any delays and the cleaning up of the wiki. So just the finishing touch. The third and last milestone represents the end of our project. This will of course be at the end of week 8.

Planning


Gantt chart

To make this planning as clear as possible we made a Gantt chart out of it. For this Gantt chart we divided all the work we had to do, as discussed above, in five sections. These sections are: presentations, literature study, qualitative research, implementation and finishing touch. Out of this basic planning we made a Gantt chart. This was done with Smartsheet (https://www.smartsheet.com/). The sections and its subtasks and the Gantt chart can be seen in the appendix. The grey horizontal bars represent the sections as explained earlier and the green bars below each grey one represent its subtasks. Some bars are connected with arrows. These represent a causal relationship: which task is the follow up task of another, i.e. what has to be done before a task can be started. In week 8, it can be seen that everything comes together in the last milestone: project finished! At this point in time, all the sections are finished which means that all the tasks specified are done. Note: the week of Feb 27 is made red because that is the week of the spring holydays. Since this is not an official school week we decided not to plan any deadlines in that week.

Gantt chart

Tasks

Lastly, we made records during our meeting containing the things we talked about as well as bullet points of the tasks each of us had to do for the next week. Among other things, this consisted of making the presentation, writing the first part for the wiki, get in contact with specialists and think of future planning.

  1. presentation preperation
  2. search + read articles + summarize