2 citations · 3 across the 16 of their papers we have counts for
7 papers · 2 filters
Robust Halo Orbit Stationkeeping Under Missed Thrust Events and Maneuver Execution Errors
Shaurya Shrivastava, Kenshiro Oguri
Spacecraft stationkeeping is subject to various operational uncertainties such as missed thrust events, maneuver execution errors, and dynamics modeling errors. Missed thrust event…
Cubature-Based Statistical Moment Steering for Nonlinear, Non-Gaussian Trajectory Optimization
Daniel C. Qi, Kenshiro Oguri
This paper addresses discrete-time non-Gaussian distribution steering in deterministic nonlinear systems. Distribution steering is a problem in which a control policy is designed o…
Global Optimization Framework for Automated Low-Thrust Gravity-Assist Trajectory Design
Ryo Iijima, Kenshiro Oguri, Toshinori Kuwahara
Gravity-assist trajectory design requires searching numerous leg combinations, but applying nonlinear programming (NLP) for low-thrust trajectory optimization to all combinations i…
On the Optimality of Markovian Policies for Chance-Constrained Covariance Steering
Naoya Kumagai, Kenshiro Oguri
Many studies on finite-horizon stochastic optimal control, including covariance steering, parameterize control policies as state-history-affine. This parameterization enables a con…
Data-Efficient Non-Gaussian Semi-Nonparametric Density Estimation for Nonlinear Dynamical Systems
Aaron R. Liao, Kenshiro Oguri, Michele D. Carpenter
Accurate representation of non-Gaussian distributions of quantities of interest in nonlinear dynamical systems is critical for estimation, control, and decision-making, but can be…
Generalizing Output-Feedback Covariance Steering to Incorporate Non-Orthogonal Estimation Errors
Daniel C. Qi, Kenshiro Oguri
This paper addresses the problem of steering a state distribution over a finite horizon in discrete time with output feedback. The incorporation of output feedback introduces addit…
Square Root-Factorized Covariance Steering
Naoya Kumagai, Kenshiro Oguri
Covariance steering (CS) synthesizes a control policy which drives the state's mean and covariance matrix towards desired values. Offering tractable computation of a closed-loop po…