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SURF: Announcements of Opportunity

Below are Announcements of Opportunity posted by Caltech faculty and JPL technical staff for the SURF program. Additional AOs for the Amgen Scholars program can be found here.

Specific GROWTH projects being offerred for summer 2018 can be found here.

Each AO indicates whether or not it is open to non-Caltech students. If an AO is NOT open to non-Caltech students, please DO NOT contact the mentor.

Announcements of Opportunity are posted as they are received. Please check back regularly for new AO submissions! Remember: This is just one way that you can go about identifying a suitable project and/or mentor.

Announcements for external summer programs are listed here.

Students pursuing opportunities at JPL must be
U.S. citizens or U.S. permanent residents.

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Project:  Data Analysis and Tool Development for Mars 2020 Lander Vision System
Disciplines:  Computer Science, Electrical Engineering, Mechanical Engineering
Mentor:  Nikolas Trawny, (JPL), Nikolas.Trawny@jpl.nasa.gov, Phone: (818) 393-8685
Background:  Human and robotic planetary lander missions require accurate surface relative position knowledge to land near science targets or next to pre-deployed assets. These accurate position estimates can be obtained in real-time by matching sensor data collected during descent to an on-board map. The Lander Vision System (LVS) being developed for the Mars 2020 mission generates landmark matches in descent imagery and combines these with inertial data to estimate vehicle position, velocity and attitude. The Mars 2020 EDL system will use this position estimate to repurpose its existing powered descent divert to avoid 100m scale hazards identified in the landing ellipse map prior to landing. This enables the selection of landing sites that have scientifically interesting terrain relief and were not selectable in the original implementation of MSL EDL.

LVS will undergo a rigorous testing and validation campaign, using simulations, laboratory testbeds, and a helicopter fieldtest. The dataproducts generated from these tests will be evaluated and analyzed to verify that LVS meets its performance and robustness requirements. A variety of analysis tools will need to be developed for this purpose, ranging from data parsers to visualization routines to statistical analysis routines.
Description:  This project aims at developing, extending, testing, and using new and existing data analysis tools to aid the validation and verification (V&V) efforts of the Lander Vision System, in very close interaction with the LVS team. Tasks include but are not limited to:

- Familiarization with LVS Concept of Operation, output products, and V&V plan.
- Development of data parsers for output products
- Development of data parsers and potential postprocessing of ground truth data
- Development of visualization routines to plot key quantities of individual and aggregate simulations (e.g., navigation state, uncertainties, feature matches, errors, performance metrics)
- Development of tools to compute key statistics (mean, median, std, max, 99%-ile) for quantities of interest, e.g. navigation state errors
- Development of automated scripts that can perform postprocessing and plot generation for large sets of simulations and test data sets
- Execute V&V test procedures to generate test data
- Analyze test data using the postprocessing tools
- Train LVS team in analysis tool usage

References:  A. E. Johnson, Y. Cheng, J. Montgomery, N. Trawny, B. E. Tweddle, and J. Zheng. Design and Analysis of Map Relative Localization for Access to Hazardous Landing Sites on Mars. In Proc. AIAA Guidance, Navigation, and Control Conference, San Diego, CA, Jan. 21, 2016.
 
https://www.jpl.nasa.gov/news/news.php?feature=4514
Student Requirements:  - Strong Python skills required, including NumPy, SciPy, and matplotlib.
- Familiarity with C desired
- Background in navigation, estimation, image processing, statistics useful
Location / Safety:  Project building and/or room locations: . Student will need special safety training: No.
Programs:  This AO can be done under the following programs:

  Program    Available To
       SURF    both Caltech and non-Caltech students 

Click on a program name for program info and application requirements.


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