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NASA Centennial Challenges

What I do?

Mars Ascent Vehicle

Creativity and originality

Our design is simple and based on the requirements of the launch.The primary concept was the fewer systems, the better. This creates a lower probability of failure. We using material's elastic strain as the mechanism to catch the sample which replace the traditional servo claw.

Uniqueness and significance

The linear slider are used it as an escalator for the AGSE. The ignition system is comprised of several parts to perform the function of safely moving the ignition wire into the motor. Our “lemonade pitcher” design of securing the sample within the rocket is a unique application of that two-cylinder mechanism.
Suitable level of challenge

The rocket team has no experience and knowledge for building a full automatic robotic system at that time. So there was a significant learning curve to overcome. All team members came as volunteers and to research, design, build and test the rocket during them personal breaks .

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What I do?

Atmospheric Aerosol Detection

Creativity and originality

We used model 212 profiler particle counter to sample the atmosphere. The goal is to sample the atmosphere from the ground to one mile in the atmosphere and back to the ground to understand the distribution of particles in the sample area. This is an original idea has never attempted a payload like this.

Uniqueness and significance
The particle counter was selected to attempt a novel approach to atmospheric sampling through in situ air collection and analysis.  The particle counter will provide data on the size of the particle in addition to the mass of the sample and giving the sample a respirable particulate qualifier.
Suitable level of challenge
The challenge is of a suitable level as the particle counter is not a plug in ready system. The system requires engineering knowledge and ingenuity to incorporate into the rocket design. Further, the dissemination of data from the findings will allow a comprehensive report to be developed.

What I do?

Landing Hazard Detection

Creativity and originality
Arduino is more powerful in connecting various sensors together. However, Raspberry Pi with powerful CPU and video decoder is much better at image processing and multi-media part. We connected this two parts by Adruberry sheild and get more than 2X power.

Uniqueness and significance
The machine learning help us to train our image dataset. Also we split the dataset into training and validation dataset. This method helps convince us the classifying capacity of our model, and indicates related the stability of our classification model when applied to predict the result in the test dataset.

Suitable level of challenge

To make sure the model classifies correctly, we need to train over 4000 images. We’ll create a feature vector of 100 dimensions for each images. Hence, totally there will be a huge matrix with 3000 x 100 dimension. To apply better algorithm for release computing pressure will be one of the main challenge of our work, especially in the data training part.

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What I get?

  

This is most important project in my undergraduate life. During these three years, I came from a rocket rookie to be a competent team leader. I drank hundreds coffees and monsters, spent countless nights working in the machine shop to improve our rocket system. These experience make me feeling hard, stress, sometimes painful, but it worth undoubtedly.
From algorithm understanding to computer simulation, from material processing to the rocket production, all of these are the treasures which this porject given to me. Especially, I am proudly work with these team members. They never let me face and fight these problem alone and never let me feeling helpless.

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