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20132025
most citedIncentive Compatibility in Stochastic Dynamic Systems

17 citations · 73 across the 15 of their papers we have counts for

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5 papers · 1 filter

cs.RO2018★ 14 cited

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…

cs.RO2017★ 5 cited

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…

cs.RO2017★ 2 cited

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…

cs.RO2016★ 4 cited

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…

cs.RO2016★ 6 cited

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…