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Shreyansh Daftry

Address:

4800 Oak Grove Drive
M/S 198-219
Pasadena, CA 91101

Phone:

626.840.4160

Member of:

347J - Perception Systems

Shreyansh Daftry

Robotics Technologist

Biography

Shreyansh Daftry is a Technologist in the Computer Vision group in the Autonomous Systems division (34x) at JPL. As a researcher in the field of Artificial Intelligence, he is interested in pushing the boundaries of technology with innovations in Computer Vision, Machine Learning and Autonomous Robotics. His lifelong ambition is to promote both the exploration of space and improvement of sustainable living on Earth.

Prior to joining JPL, Shreyansh received his M.S. degree in Robotics from Carnegie Mellon University, USA. His studies were focused on robust perception and navigation for small unmanned aerial vehicles. He has worked as a software developer and research intern for several organizations including Astrobotic Inc., where he developed technology for multi-robot exploration of lunar caves as part of the Google Lunar X prize.

Shreyansh has also served on the Mission support team for NASAs human research program: Hawaii Space Exploration Analog and Simulation Mission 4.

Education

M.S. in Robotics, Carnegie Mellon University (2014-2016)
B.S. in Electronics and Communication Engineering, MIT Manipal (2009-2013)

Professional Experience

Robotics Technologist, Jet Propulsion Lab, USA (2016-present)
Mission Support Team, NASAs HI-SEAS Mission 4 (2016)
Graduate Research Assistant, Carnegie Mellon University, USA (2014-2016)
Research Associate, TU Graz, Austria (2013-2014)
Summer Research Scholar, Astrobotic Inc. (2012)
Research Intern, IIT Kanpur, India (2011)

Research Interests

Safe and Precise Autonomous Landing of Planetary Helicopters/Landers
Vision-based Localization, State-estimation, Mapping and Navigation
Semantic Scene Understanding and Terrain Classification
Machine Learning, Reinforcement Learning and Multi-agent Systems
Human-Robot Interactions
Systems Engineering

Publications

2020
  1. T. Pham, W. Seto, S. Daftry, A. Brinkman, J. Mayo, C. Padgett, E. Kulczycki, R. Detry, "Rover Localization for Tube Pickup: Dataset, Methods and Validation for Mars Sample Return Planning," IEEE Aerospace Conference, Big Sky, MT, USA, 05 February 2020.
  2. M. Ono, B. Rothrock, K. Otsu, Y. Iwashita, A. Didier, T. Islam, V. Sun, C. Laporte, K. Stack, S. Higa, J. Sawoniewicz, S. Daftry, C. Mattmann, V. Timmaraju, S. Sahnoune, O. Lamarre, D. Qiu, S. Ghosh, S. Nomura, H. Sarabu, S. Suehr, L. Folsom, G. Hedrick, H. Park, H. Roy, "MAARS: Machine Learning-Based Analytics for Rover Systems," IEEE Aerospace Conference, Big Sky, MT, USA, 05 February 2020.
  3. A. Schutte, J. Delaune, E. Sklyanskiy, R. Hewitt, S. Daftry, M. Quadrelli, L. Matthies, "Integrated Simulation and State Estimation for Precision Landing on Titan," IEEE Aerospace Conference, Big Sky, MT, USA, 05 February 2020.
  4. L. Matthies, S. Daftry, B. Rothrock, A. Davis, R. Hewitt, E. Sklyanskiy, J. Delaune, A. Schutte, M. Quadrelli, M. Malaska, "Terrain Relative Navigation for Guided Descent on Titan," IEEE Aerospace Conference, Big Sky, MT, USA, 05 February 2020.
2019
  1. S. Daftry, M. Das, J. Delaune, C. Sorice, R. Hewitt, S. Reddy, D. Lytle, E. Gu and L. Matthies, "Robust Vision-based Autonomous Navigation, Mapping and Landing for MAVs at Night," International Symposium on Experimental Robotics (ISER), Buenos Aires, Argentina, 06 August 2019.
  2. L. H. Matthies, B. Rothrock, S. Daftry, A. B. Davis and M. Malaska, "Map Matching During Descent for Terrain Relative Navigation on Titan," International Planetary Probe Workshop (IPPW), Oxford, United Kingdom, 06 August 2019.
2018
  1. S. Daftry, D. Dey, H. Sandhawalia, S. Zeng, J. A. Bagnell, M. Hebert, "Semi-Dense Visual Odometry for Monocular Navigation in Cluttered Environment," IEEE International Conference on Robotics and Automation (ICRA) Workshop, Seattle, USA, 03 October 2018.
  2. S. Daftry, S. Zeng, A. Khan, N. Melik-Barkhudarov, J. A. Bagnell, M. Hebert, "Robust Monocular Flight in Cluttered Outdoor Environments," IEEE International Conference on Intelligent Robots and Systems (IROS) Workshop, Daejeon, South Korea, 03 October 2018.
  3. S. Daftry, J. Delaune, R. Bhuta, L. Matthies, "Towards Vision-based Safe Autonomous Landing of MAVs at Night," IEEE International Conference on Robotics and Automation (ICRA) Workshop, Brisbane, Australia, 03 October 2018.
  4. S. Daftry, Y. Agrawal, L. Matthies, "Online Self-supervised Scene Segmentation for Micro Aerial Vehicles," IEEE International Conference on Robotics and Automation (ICRA) Workshop, Brisbane, Australia, 03 October 2018.
  5. S. Daftry, Y. Agrawal, L. Matthies, "Online Self-supervised Long-range Scene Segmentation for MAVs," IEEE International Conference on Intelligent Robots and Systems (IROS), Madrid, Spain, 03 October 2018.
  6. C. Ordonez, R. Alicea, B. Rothrock, K. Ladyko, J. Nash, R. Thakker, S. Daftry, M. Harper, E. Collins and L. Matthies, "Characterization and Traversal of Pliable Vegetation for Robot Navigation," International Symposium on Experimental Robotics (ISER), Buenos Aires, Argentina, 03 October 2018.
  7. S. Daftry, S. Zeng, J. A. Bagnell, M. Hebert, "Introspective Perception: Learning to Predict Failures in Vision Systems," IEEE International Conference on Intelligent Robots and Systems (IROS), Daejeon, South Korea, 15 May 2018.
  8. S. Daftry, J. A. Bagnell, M. Hebert, "Learning Transferable Policies for Monocular Reactive MAV Control," International Symposium on Experimental Robotics (ISER), Tokyo, Japan, 15 May 2018.
2017
  1. S. Daftry, "Towards Scalable Visual Navigation of Micro Aerial Vehicles," Master Thesis, Carnegie Mellon, University, USA, 07 October 2017.
  2. S. Daftry, W. L. Whittaker, "Multi Robot Sensor Fusion and 3D Modelling for Subsurface Lunar Exploration," Robotics Institute Summer Scholar, Pittsburgh, USA, 02 October 2017.
  3. S. Daftry, C. Hoppe, H. Bischof, "Multi Scale Camera Network For Accurate Structure from Motion," International Computer Vision Summer School, Sicily, Italy, 02 October 2017.
  4. V. Agarwal, S. Daftry, B. Bhattacharya, "An Innovative Approach to Pipeline Health Monitoring using Crawler Robot with PVDF based Probe," International Conference on Robotics, Pittsburgh, USA, 02 October 2017.
  5. S. Daftry, S. Dawar, "Performance Evaluation of Transform based Feature Extraction Methods for Identity Authentication System using Fingerprint Matching," International Conference on Signal Processing, Pattern Recognition and Applications, Crete, Greece, 02 October 2017.
  6. A. Hussain, H. Jones, B. Kannan, U. Wong, T. Pimentel, S. Tang, S. Daftry, S. Huber, W. L. Whittaker, "Mapping Planetary Caves with an Autonomous, Heterogeneous Robot Team," IEEE Aerospace Conference (Aero), Big Sky, USA, 02 October 2017.
  7. S. Daftry, A. Wendel, H. Bischof, "Flexible and User-Centric Camera Calibration using Planar Fiducial Markers," British Machine Vision Conference (BMVC), Bristol, UK, 02 October 2017.
  8. S. Daftry, C. Hoppe, H. Bischof, "Building with Drones: Accurate 3D Facade Reconstruction using MAVs," IEEE International Conference on Robotics and Automation (ICRA), Seattle, USA, 02 October 2017.
  9. D. Dey, K. S. Shankar, S. Zeng, R. Mehta, M. T. Agcayazi, C. Eriksen, S. Daftry, J. A. Bagnell, M. Hebert, "Vision and Learning for Deliberative Monocular Cluttered Flight," International Conference on Field and Service Robotics (FSR), Toronto, Canada, 02 October 2017.
  10. S. Daftry, "Artificial Neural Networks based Classification Technique for Iris Recognition," International Journal of Computer Applications, 57(4), 22-25, 02 October 2017.
  11. M. Rumpler, S. Daftry, A. Tscharf, R. Prettenthaler, C. Hoppe, G. Mayer, H. Bischof, "Automated End-to-End Workflow for Precise and Geo-accurate Reconstructions using Fiducial Markers," ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences, 02 October 2017.
  12. M. Rumpler, A. Tscharf, C. Mostegel, S. Daftry, C. Hoppe, R. Prettenthaler, F. Fraundorfer, G. Mayer, H. Bischof, "Evaluations on multi-scale camera networks for precise and geo-accurate reconstructions from aerial and terrestrial images with user guidance," Computer Vision and Image Understanding (CVIU), 02 October 2017.