3 citations · 3 across the 4 of their papers we have counts for
4 papers · 1 filter
Deep Reinforcement Learning for Scalable Multiagent Spacecraft Inspection
Kyle Dunlap, Nathaniel Hamilton, Kerianne L. Hobbs
As the number of spacecraft in orbit continues to increase, it is becoming more challenging for human operators to manage each mission. As a result, autonomous control methods are…
Run Time Assured Reinforcement Learning for Six Degree-of-Freedom Spacecraft Inspection
Kyle Dunlap, Kochise Bennett, David van Wijk +2
The trial and error approach of reinforcement learning (RL) results in high performance across many complex tasks, but it can also lead to unsafe behavior. Run time assurance (RTA)…
Run Time Assurance for Simultaneous Constraint Satisfaction During Spacecraft Attitude Maneuvering
Cassie-Kay McQuinn, Kyle Dunlap, Nathaniel Hamilton +2
A fundamental capability for On-orbit Servicing, Assembly, and Manufacturing (OSAM) is inspection of the vehicle to be serviced, or the structure being assembled. This research ass…
A Universal Framework for Generalized Run Time Assurance with JAX Automatic Differentiation
Umberto Ravaioli, Kyle Dunlap, Kerianne Hobbs
With the rise of increasingly complex autonomous systems powered by black box AI models, there is a growing need for Run Time Assurance (RTA) systems that provide online safety fil…