10 citations · 18 across the 6 of their papers we have counts for
6 papers
Deep Learning Warm Starts for Trajectory Optimization on the International Space Station
Somrita Banerjee, Abhishek Cauligi, Marco Pavone
Trajectory optimization is a cornerstone of modern robot autonomy, enabling systems to compute trajectories and controls in real-time while respecting safety and physical constrain…
Diagnostic Runtime Monitoring with Martingales
Ali Hindy, Rachel Luo, Somrita Banerjee +3
Machine learning systems deployed in safety-critical robotics settings must be robust to distribution shifts. However, system designers must understand the cause of a distribution…
Contingency Planning Using Bi-level Markov Decision Processes for Space Missions
Somrita Banerjee, Edward Balaban, Mark Shirley +2
This work focuses on autonomous contingency planning for scientific missions by enabling rapid policy computation from any off-nominal point in the state space in the event of a de…
A System-Level View on Out-of-Distribution Data in Robotics
Rohan Sinha, Apoorva Sharma, Somrita Banerjee +6
When testing conditions differ from those represented in training data, so-called out-of-distribution (OOD) inputs can mar the reliability of learned components in the modern robot…
Data Lifecycle Management in Evolving Input Distributions for Learning-based Aerospace Applications
Somrita Banerjee, Apoorva Sharma, Edward Schmerling +3
As input distributions evolve over a mission lifetime, maintaining performance of learning-based models becomes challenging. This paper presents a framework to incrementally retrai…
Adaptive Meta-Learning for Identification of Rover-Terrain Dynamics
S. Banerjee, J. Harrison, P. M. Furlong +1
Rovers require knowledge of terrain to plan trajectories that maximize safety and efficiency. Terrain type classification relies on input from human operators or machine learning-b…