BEGIN:VCALENDAR VERSION:2.0 PRODID:-//wp-events-plugin.com//6.6.4.4//EN TZID:Asia/Jerusalem X-WR-TIMEZONE:Asia/Jerusalem BEGIN:VEVENT UID:0-1643@aerospace.technion.ac.il DTSTART;TZID=Asia/Jerusalem:20260318T133000 DTEND;TZID=Asia/Jerusalem:20260318T143000 DTSTAMP:20260318T081838Z URL:https://aerospace.technion.ac.il/events/optimal-estimation-aware-motio n-a-control-centric-optimization-framework/ SUMMARY:Optimal Estimation-Aware Motion: A Control-Centric Optimization Fra mework DESCRIPTION:Lecturer:Liraz Mudrik\n Faculty:Mechanical and Aerospace Engine ering Department\n Institute:Naval Postgraduate School\n Location:\n Zoom: https://technion.zoom.us/j/94050711666\n Abstract: This talk focuses on t he intersection of trajectory generation with estimation theory\, specific ally addressing the challenges of operating in uncertain or adversarial en vironments\, such as GPS-denied scenarios. In such scenarios\, trajectorie s must be aware of the estimation process and actively maximize informatio n gain. However\, coupling estimation metrics with high-fidelity nonlinear dynamics creates complex\, nonconvex optimal control problems that challe nge standard computational techniques\, such as the popular pseudospectral methods. Generating sensor-based trajectories naturally requires uniform time spacing\, which introduces well-known limitations such as the Runge p henomenon and the impossibility theorem. This talk outlines a unified rese arch architecture that bridges the gap between high-level mission goals an d efficient computational methods with theoretical guarantees.\n\nFirst\, to enable efficient planning in complex domains\, we introduce the mixed B ernstein-Fourier approximants. This representation is specifically designe d to encode the complex periodic behaviors inherent to missions such as ob server trajectory design and mine countermeasures\, significantly reducing the dimensionality of the search space without sacrificing accuracy.\n\nS econd\, we present a control-centric optimization framework that fundament ally reinterprets optimization algorithms as continuous-time dynamical sys tems. This approach provides a general theory for synthesizing solvers wit h tunable convergence profiles\, ranging from asymptotic to fixed and pres cribed-time. By leveraging results from Lyapunov stability theory\, this f ramework allows embedding constraints\, ensuring strictly feasible traject ories. This establishes a theoretical foundation for scalable autonomy\, d emonstrated through constrained optimization\, minimax problems\, and gene ralized Nash equilibrium seeking. These results pave the way for future re search in robust\, scalable aerospace autonomy where real-time performance and safety guarantees are paramount.\n\nDr. Liraz Mudrik is currently a P ostdoctoral Fellow in the Department of Mechanical and Aerospace Engineeri ng at the Naval Postgraduate School. He received his Ph.D. in Aerospace En gineering (direct track) from the Technion–Israel Institute of Technolog y in 2023\, where he also earned his B.Sc. (cum laude).\n\n \;\n\nPlea se be advised that all seminars scheduled for the near future\, and until further notice\, will be held online only via Zoom. This transition allows us to maintain our academic calendar and ensure the safety and participat ion of our community regardless of location. We are committed to ensuring these virtual sessions are delivered promptly and effectively. We apprecia te your continued flexibility and look forward to seeing you in our virtua l seminars.\n\n \;\n Details: \n CATEGORIES:Seminars,סמינרים END:VEVENT BEGIN:VTIMEZONE TZID:Asia/Jerusalem X-LIC-LOCATION:Asia/Jerusalem BEGIN:STANDARD DTSTART:20251026T010000 TZOFFSETFROM:+0300 TZOFFSETTO:+0200 TZNAME:IST END:STANDARD END:VTIMEZONE END:VCALENDAR