Posts tagged Week 3
Brainstorming 2
Jul 5th
In a previous post I explained the facts that forced us to re-think our project idea. Basically, our cool idea of an iPhone tied to a skateboard to create a exertion game require too much programming time. So we searched another idea who is required to be simpler and easy to be implemented in the remaining time.
So we got us a round table (the ones in BIT cafeteria are the best!) and put our minds to work.
First step : Use the Initial Design Techniques – Brainstorming (as learned in DIS I)
Our goal: collect as many ideas of exertion game as we can
Defer judgment, no criticism, no rejection of ideas
Include all ideas, allow also the leapfrog ideas
Result:
1. Virtual basket
2. Ping-pong game to the wall
3. Squash
4. Throw a ball to a target
5. Boxing
6. Throwing paper balls to garbage – fun in offices
After some debate we agreed to pursue in implementing the 4th idea. We will try to create an exertion game which will be composed from:
- a board which will act like a hit sensitive projection screen,
- a projector to display the target on the screen
- the software behind to calculate:
- hit points,
- decide if user hit the target
- scoring and level finishing
To have a clear idea of our game we created also a small storyboard:
Changing the idea of the project
Jul 5th
In the last meeting, our tutors, Mr. Heller and Mr. Karrer, shared with us some of their experience using the sensors which made us reconsider the project idea.
The idea
Because of the new introduction in iPhone programming and the rich set of sensors of this device, our project envisioned an iPhone attached to the board in order to track the skateboard movements. The data pulled out by the iPhone is the initial acceleration (the one when the user starts riding with the board), and lateral or up-down acceleration when he does turns or jumps with the board.
First, the iPhone accelerometer won’t do the trick of getting all the information needed from the board. As it outputs acceleration, we would have to integrate once to get the velocity and twice to get the position. This gets us into a lot of approximations which aren’t suited for movements in a few meters range.
Secondly, the iPhone sensor is not design to get an industrial-scale precision and accuracy in an outdoor activity, but more for fun activities like sensing shakes or directional changes.
Thus, combined with the above observation implies the fact that our data readed from an iPhone attached to a board would not be as accurate we need (also the integration introduces approximations first to the velocity vector and again when computing position). It also it contains a lot of noise because of the environment (the skateboard goes on the rough and bumpy surfaces).
The solution
Given the facts, our team agrees with the tutors that this project would have needed too much time in order to develop some sophisticated algorithms, compensating the noise and the two integrations approximations, hardly near impossible to be done in the time span allocated for this project.
The upper side of this discussion is that our knowledge about sensors and in particular iPhone sensors has improved thanks to our tutors. Our suggestion is that for the next lab a similar discussion and sensor presentation should be held in the first laboratory meeting, in order to guide the students even faster to concrete results.
