16 citations · 48 across the 11 of their papers we have counts for
6 papers · 1 filter
On the Use of the Observability Gramian for Partially Observed Robotic Path Planning Problems
Mohammadhussein Rafieisakhaei, Suman Chakravorty, P. R. Kumar
Optimizing measures of the observability Gramian as a surrogate for the estimation performance may provide irrelevant or misleading trajectories for planning under observation unce…
A Near-Optimal Separation Principle for Nonlinear Stochastic Systems Arising in Robotic Path Planning and Control
Mohammadhussein Rafieisakhaei, Suman Chakravorty, P. R. Kumar
We consider nonlinear stochastic systems that arise in path planning and control of mobile robots. As is typical of almost all nonlinear stochastic systems, the optimally solving p…
Near-Optimal Belief Space Planning via T-LQG
Mohammadhussein Rafieisakhaei, Suman Chakravorty, P. R. Kumar
We consider the problem of planning under observation and motion uncertainty for nonlinear robotics systems. Determining the optimal solution to this problem, generally formulated…
Belief Space Planning Simplified: Trajectory-Optimized LQG (T-LQG) (Extended Report)
Mohammadhussein Rafieisakhaei, Suman Chakravorty, P. R. Kumar
Planning under motion and observation uncertainties requires solution of a stochastic control problem in the space of feedback policies. In this paper, we reduce the general (n^2+n…
Non-Gaussian SLAP: Simultaneous Localization and Planning Under Non-Gaussian Uncertainty in Static and Dynamic Environments
Mohammadhussein Rafieisakhaei, Suman Chakravorty, P. R. Kumar
Simultaneous Localization and Planning (SLAP) under process and measurement uncertainties is a challenge. It involves solving a stochastic control problem modeled as a Partially Ob…
Feedback Motion Planning Under Non-Gaussian Uncertainty and Non-Convex State Constraints
Mohammadhussein Rafieisakhaei, Amirhossein Tamjidi, Suman Chakravorty +1
Planning under process and measurement uncertainties is a challenging problem. In its most general form it can be modeled as a Partially Observed Markov Decision Process (POMDP) pr…