Kepler has received the following awards and nominations. Way to go!
The 3D models have been created and rigged using MAYA. We tried to keep the cockpit model as realistic as possible. The models were integrated in UNITY and proper rules of association were enforced so that the models interact as a unit. The Unity created app receives instructions in form of JSON format which are decoded in C#.
DYNAMIC ORIENTATION CHANGING CHAIR
The chair has two modules:
Both the modules are connected by a single Arduino which receives instructions from AI BOT.
Vibration module: The bottom of the chair is rigged with 3 vibration motors which are power up while interacting in the virtual reality. During the launch sequence the three motors work synchronously to provide the maximum vibrations while during interaction they respond depending on the directional events in the virtual reality.
Orientation module: the orientation of the chair is changed during the launch sequence. The back support is pulled to provide a more up-facing view to give a feel of acceleration during a real launch.
Documentation of the Glove Gesture recognition has always be a pain for developers. There are two solution presently available for gesture recognition, image processing and through some hardware in form of glove or band. The problem with image processing is that a person always need a view of camera at his hand for getting the image. And when it comes to hardware gloves or bands, the problem with these gadgets is that they are too costly. We decided to design our own gloves to bring down the cost. The main reason of high costing of these gadgets is high cost of sensors which are used in this. Therefore we designed our own sensors. We used most trivial laws of physics that as light goes through multiple reflections its intensity reduces. We took 2m of transparent plastic pipe and cut it into pieces according to length of fingers and then were wrapped with electric tape to reduce the loss of light. Then we attached a IR emitter and receiver at two ends and observed as the pipe was bent the intensity reduces which we measured using an android. Then we used MPU6050 sensor to get the alignment of hand. And using the data from these sensors we were able to gesture as well as complete orientation of the hand. Then we used HC-05 (Bluetooth module) to send the data to mobile. Ultimately we were able to bring the cost of complete gesture recognition glove under $25. Components used: Arduino Uno HC-05 MPU6050 IR Module ESP8266
ARTIFICIAL INTELEGENT ASSISTANT
Hardware and Equipment used:
SpaceApps is a NASA incubator innovation program.