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UID:198@cds.iisc.ac.in
DTSTART;TZID=Asia/Kolkata:20260528T150000
DTEND;TZID=Asia/Kolkata:20260528T160000
DTSTAMP:20260522T064821Z
URL:https://cds.iisc.ac.in/events/ph-d-thesis-colloquium-102-cds-28-may-20
 26-geometry-consistent-and-integrity-aware-navigation-for-autonomous-space
 craft-under-partial-observability-and-model-uncertainty/
SUMMARY:Ph.D: Thesis Colloquium: 102 : CDS: 28\, May 2026 “Geometry-Consi
 stent and Integrity-Aware Navigation for Autonomous Spacecraft under Parti
 al Observability and Model Uncertainty”
DESCRIPTION:DEPARTMENT OF COMPUTATIONAL AND DATA SCIENCES\nPh.D. Thesis Col
 loquium\n\n\n\nSpeaker: Mr. Surya Ratna Prakash Dumpa\nS.R. Number: 06-18-
 00-11-12-20-1-18701\nTitle: “Geometry-Consistent and Integrity-Aware Nav
 igation for Autonomous Spacecraft under Partial Observability and Model Un
 certainty”\nResearch Supervisor: Prof. Soumyendu Raha\nDate &amp\; Time 
 : May 28\, 2026 (Thursday)\, 03:00 PM\nVenue : #102\, CDS Seminar Hall\n\n
 \n\nABSTRACT\nAutonomous spacecraft navigation during powered descent and 
 planetary landing operates under severe uncertainty\, partial observabilit
 y\, and strict finite-time safety requirements. During such mission phases
 \, navigation systems must reconcile nonlinear dynamics with noisy and inc
 omplete measurements while remaining robust to structural model mismatch\,
  estimator degradation\, and transient instability. Classical filtering ar
 chitectures\, including Kalman filtering and standard particle filtering\,
  primarily rely on posterior correction after state propagation and are ty
 pically analyzed using asymptotic stability notions. These approaches may 
 become inadequate in autonomy-critical regimes where local geometric incon
 sistency\, particle degeneracy\, and short-horizon perturbation growth det
 ermine mission success before asymptotic behaviour becomes relevant.\n\nTh
 is thesis develops a unified geometric and stochastic framework for integr
 ity-aware autonomous spacecraft navigation in which geometric consistency\
 , estimator integrity\, probabilistic hazard forecasting\, and finite-time
  transient stability are treated as interconnected components of the same 
 problem.\n\nFirst\, a co-state-based differential--algebraic framework is 
 developed to enforce local compatibility between system dynamics and measu
 rement geometry under partial observability. The resulting geometric co-st
 ate variable acts as an intrinsic consistency signal linking nominal propa
 gation with the measurement-consistent manifold. This signal is further us
 ed to construct stochastic regime abstractions and continuous-time hazard 
 forecasting models\, enabling probabilistic prediction of degraded operati
 ng modes through regime occupancy probabilities and mean first-passage ind
 icators.\n\nSecond\, an integrity-aware nonlinear filtering architecture\,
  termed the Geometric Projection Particle Filter (GPF)\, is introduced for
  nonlinear and non-Gaussian state estimation under persistent model uncert
 ainty. Unlike conventional bootstrap particle filters\, the proposed metho
 d projects nominal drift dynamics directly onto the measurement-consistent
  subspace during propagation\, creating a geometry-aware proposal process 
 that reduces proposal--likelihood mismatch prior to weighting. This suppre
 sses particle degeneracy\, improves effective sample size retention\, and 
 maintains bounded estimation error in regimes where standard particle filt
 ers diverge.\n\nThird\, a logarithmic-norm-based framework is developed fo
 r analyzing finite-time transient stability of nonlinear It^o stochastic s
 ystems and projected data-constrained dynamics. By extending matrix measur
 es in a Lipschitz sense\, the approach provides tractable characterization
  of perturbation growth without requiring explicit Lyapunov function const
 ruction. The analysis clarifies the distinction between mean stability and
  pathwise finite-time safety\, showing that stochastic diffusion induces n
 onzero probability of critical transient excursions even when average beha
 viour remains stable.\n\nThe proposed methods are validated using lunar la
 nder descent navigation scenarios with partial observability and persisten
 t model mismatch. Results demonstrate early hazard detection\, improved es
 timator robustness\, significant reduction in particle degeneracy\, interp
 retable probabilistic hazard forecasting\, and stronger finite-time safety
  characterization compared with classical filtering and asymptotic stabili
 ty approaches.\n\nThese results establish that autonomous navigation shoul
 d be treated not only as a state estimation problem\, but as a coupled pro
 blem of geometric consistency\, estimator integrity\, stochastic hazard ev
 olution\, and finite-time operational safety. The thesis provides theoreti
 cal foundations and practical algorithmic realizations for integrity-aware
  autonomous spacecraft navigation.\n\n\n\nALL ARE WELCOME
CATEGORIES:Events,Ph.D. Thesis Colloquium
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