4 papers
Agentic AutoResearch forSpace Autonomy: An Auditable, LLM-Driven Research Agent for Aerospace Control Problems
Amit Jain, Richard Linares
Spacecraft guidance, navigation, and control functions are increasingly realized as learned policies distilled from expert solvers. Developing such a policy is itself a research pr…
Memory-Efficient Meta-Reinforcement Learning for Adaptive Safety-Critical Control in Adversarial Spacecraft Proximity Operations
Alejandro Posadas-Nava, Richard Linares, Minduli Wijayatunga
Autonomous spacecraft rendezvous and proximity operations (RPO) require controllers that guarantee safety under thrust constraints while minimizing fuel expenditure. Input-constrai…
Autonomous Reasoning for Spacecraft Control: A Large Language Model Framework with Group Relative Policy Optimization
Amit Jain, Richard Linares
This paper presents a learning-based guidance-and-control approach that couples a reasoning-enabled Large Language Model (LLM) with Group Relative Policy Optimization (GRPO). A two…
Tiny Recursive Control: Iterative Reasoning for Efficient Optimal Control
Amit Jain, Richard Linares
Neural network controllers increasingly demand millions of parameters, and language model approaches push into the billions. For embedded aerospace systems with strict power and la…