N
Nikolas Trawny
Researcher at California Institute of Technology
Publications - 59
Citations - 1634
Nikolas Trawny is an academic researcher from California Institute of Technology. The author has contributed to research in topics: Mars Exploration Program & Terrain. The author has an hindex of 20, co-authored 51 publications receiving 1400 citations. Previous affiliations of Nikolas Trawny include University of Stuttgart & Jet Propulsion Laboratory.
Papers
More filters
Journal ArticleDOI
Vision-Aided Inertial Navigation for Spacecraft Entry, Descent, and Landing
Anastasios I. Mourikis,Nikolas Trawny,Stergios I. Roumeliotis,Andrew E. Johnson,Adnan Ansar,Larry Matthies +5 more
TL;DR: The vision-aided inertial navigation algorithm (VISINAV) algorithm that enables precision planetary landing and validation results from a sounding-rocket test flight vastly improve current state of the art for terminal descent navigation without visual updates, and meet the requirements of future planetary exploration missions.
Journal ArticleDOI
Vision-aided inertial navigation for pin-point landing using observations of mapped landmarks
Nikolas Trawny,Anastasios I. Mourikis,Stergios I. Roumeliotis,Andrew E. Johnson,James F. Montgomery +4 more
TL;DR: An extended Kalman filter algorithm for estimating the pose and velocity of a spacecraft during entry, descent, and landing is described, which demonstrates the applicability of the algorithm on real‐world data and analyzes the dependence of its accuracy on several system design parameters.
Journal ArticleDOI
Autonomous Stair Climbing for Tracked Vehicles
TL;DR: The proposed method achieves robust performance under real-world conditions, without assuming prior knowledge of the stair geometry, the dynamics of the vehicle's interaction with the stair surface, or lighting conditions.
Journal ArticleDOI
Observability-based consistent EKF estimators for multi-robot cooperative localization
TL;DR: This paper analytically shows that the standard EKF-based CL always has an observable subspace of higher dimension than that of the actual nonlinear CL system, and proposes two novel observability-constrained (OC)-EKF estimators that are instances of this paradigm.
Proceedings ArticleDOI
Cooperative multi-robot localization under communication constraints
TL;DR: This paper addresses the problem of cooperative localization (CL) under severe communication constraints by presenting minimum mean square error (MMSE) and maximum a posteriori (MAP) estimators that can process measurements quantized with as little as one bit per measurement.