One of the best parts of my job is the many brilliant students I have the opportunity to mentor. Here is a (somewhat incomplete) list of the students and their projects.
NSTRF / NSTGRO (NASA Fellowship)
- Jake Levy (2023- ) - Adaptive learning for control
- Eric Chang (2022- ) - Tactile sensors
- Holly Dinkel (2020- ) - Cable segmentation and manipulation
- Julia Di (2020-2024 ) - Tactile sensing
- David Millard (2020-2023 ) - Differentiable physics simulators for machine learning
- Ian Miller (2020-2023 ) - Semantic mapping
- Andrew Bylard (2018-2019) - Motion planning based on differential geometry.
- Abhishek Cauligi (2018-2019) - Sampling-based motion planning for Astrobee.
- Keenan Albee (2018-2022 ) - Kinodynamic motion planning for Astrobee, with arm motion.
- Chris Ericksen (2018-2021) - Learning object recognition from limited data, multi-robot scheduling.
- Brian Hou (2018-2021)- Planning for non-prehensile manipulation.
2024
- Tim Rehnström - Machine learning for Astrobee mapping
2023
- Rachel Lu - Astrobee text recognition
- Luisa Mao - Astrobee localization improvements
- Morgan Sun - Astrobee object recognition
2022
- Nitzan Orr - Astrobee mapping UI
- Gialon Kasha - Astrobee planning
- Nick Linthacum - Astrobee infrastructure
- Aryan Naveen - Astrobee object perception
- Stella Zheng - Handrail approach
2021
- Ellis Ratner - Path replanning
- Gabriel Chuang - Acoustic mapping
- Gialon Kasha - Astrobee task planning
- Jason Dekarske - Astrobee time-delayed operation
- Sayanti Roy - Operator attention modeling
- Tammer Barkouki - Improving Astrobee operator understanding
2020
- Bernard-Michael Martial - Sensor fusion with satellite imagery
- Holly Dinkel - Cable Segmentation
- Kyle Newman - Automated testing for localization
- Naama Glauber - Semi-supervised training for satellite imagery
- Patrick Collins - DELTA applied to non-flood domains
- Varsha Kumar - Open source localization algorithms for Astrorbee
2019
- Deanna Flynn - Neural architecture search
- Julien Lombardo - Astrobee perching
- Keanu Nichols - Deep learning for damaged building detection and cloud detection
- Marina Moreira - Astrobee cargo transport
- Robert Campbell - Asymmetric autoencoder search
- Tevin Achong - Digital elevation maps integrated with remote sensing for deep learning
- Yunji Kim - Multi-Astrobee communication and behaviors
2018
- Ruben Garcia - Android improvements for Astrobee and much more.
- Evelyn Huang - Controlling Astrobee while grasping large objects.
- Amit Palekar - Astrobee guest science examples and face tracking.
- Ben Saeks - Astrobee arm firmware and drivers.
- Robbie Selwyn - Astrobee guest science and signal lights.
- Peter Wofford, Vivek Kumar, and Bryce Van Ross - Astrobee ZeroRobotics competition.
2017
- Marcelino Almeida - Astrobee obstacle mapping.
- Miguel Borges - Open source Vive drivers for localization ground truth (publication, software).
- Teresa Conceicao - Joint calibration of depth and visual cameras (publication).
- Max Feinberg - Mapping and localization with different cameras.
- Karen Orton - Astrobee Gazebo simulator.
- Gwang Ho Park - Astrobee signal lights.
- Jefferson Ridgeway - Automated regression testing for localization.
2016
- Marissa Dattler - Lake level monitoring
- Nolan Cate, Chelsea Ackroyd, Anton Surunis - Measuring surface water changes in Lake Tahoe (video).
- Philip Cooksey - Astrobee replanning in response to failures.
- Pyojin Kim - Localization in changing lighting conditions (publication, video).