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X-ALT-DESC;FMTTYPE=text/html:<p>###<a href="https://teams.microsoft.com/meet/29710180079583?p=B2N7xZ2wjOZSjuDRsu">Toward Trusted Autonomous Space Guidance: Meta-Reinforcement Learning, Certification, and Adaptive Lunar Landing</a></p>
 <p>####Presented by Dr. Roberto Furfaro, University of Arizona</p>
 <p>####Thursday, October 1, 2026 @ 2:00 PM - 3:00 PM (EDT)</p>
 <hr />
 <p>Future space missions will require guidance systems that can operate autonomously while remaining robust to uncertainty, disturbances, modeling errors, and off-nominal conditions. Reinforcement learning (RL) and meta-reinforcement learning (meta-RL) offer promising approaches for developing such capabilities, with meta-RL providing the additional ability to adapt guidance behavior as vehicle dynamics or environmental conditions change. Recent results have demonstrated improved generalization across uncertainties and actuator and sensor failures.</p>
 <p>This webinar will present recent developments in learning-enabled space guidance, focusing on three complementary areas. First, applications of RL and meta-RL to planetary landing, rendezvous, proximity operations, and interception will be reviewed. Second, approaches for the verification and certification of black-box learned guidance policies will be discussed, including the use of Sparse Identification of Nonlinear Dynamical Systems (SINDy) to derive interpretable models that support analysis and validation. Finally, recent work on adaptive lunar powered-descent guidance will be presented, where meta-RL dynamically schedules the guidance gains and time-to-go of an analytical fractional-polynomial guidance law while retaining computational efficiency, physical constraints, and interpretability.</p>
 <p>Together, these efforts illustrate complementary pathways toward adaptive, robust, and certifiable autonomous space guidance.</p>
 <p>####Instructions####</p>
 <ol>
 <li>
 <a href="https://nescacademy.nasa.gov/calendar/0aaf21bb2aa341399cddd8b1d766f8951d"><strong>Add this to your calendar</strong></a> for a convenient reminder 15 minutes prior to the event.</li>
 <li>
 <a href="https://teams.microsoft.com/meet/29710180079583?p=B2N7xZ2wjOZSjuDRsu"><strong>Watch Live</strong></a>. We encourage you to use this link before the event to test your ability to tune in.</li>
 </ol>
 <p>This webcast will be recorded and made available at the following link (post-event, within 24 hours) - <a href="https://nescacademy.nasa.gov/video/0aaf21bb2aa341399cddd8b1d766f8951d"><strong>Watch Recording</strong></a></p>
 <p>####Support####</p>
 <p>Should you experience any difficulties, please email the <a href="mailto:larc-dl-support-nescacademy@mail.nasa.gov">NESC Academy team</a>.</p>
URL;VALUE=URI: 
SUMMARY;LANGUAGE=en-us:Toward Trusted Autonomous Space Guidance: Meta-Reinforcement Learning, Certification, and Adaptive Lunar Landing
DTSTART;TZID="America/New_York":20261001T180000Z
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