6 papers
Model Predictive Path Integral Control as a Quantum Query Problem
Goutam Das, Takashi Tanaka
Model predictive path integral control computes its update from cost-weighted trajectory samples and may require many classical rollouts in rare-event or high-accuracy regimes. We…
Bound-Optimized Task Choice for Path Integral Control
Rylie Anderson, Goutam Das, Takashi Tanaka
Path Integral (PI) control is a powerful sampling-based method for stochastic optimal control, but it requires a restrictive coupling between the noise covariance and the control c…
Path Integral Control for Partially Observed Systems with Controlled Sensing
Goutam Das, Takashi Tanaka
Path integral control in Gaussian belief space requires a structural matching condition between the observation-driven diffusion of the belief mean and the actuation authority, whi…
Path Integral Control in Gaussian Belief Space for Partially Observed Systems
Goutam Das, Takashi Tanaka
This paper extends path integral control (PIC) to partially observed systems by formulating the problem in Gaussian belief space. PIC relies on the diffusion being proportional to…
Variational Encrypted Model Predictive Control
Jihoon Suh, Yeongjun Jang, Junsoo Kim +1
We develop a variational encrypted model predictive control (VEMPC) protocol whose online execution relies only on encrypted polynomial operations. The proposed approach reformulat…
Inverse Learning-Based Output Feedback Control of Nonlinear Systems with Verifiable Guarantees
Yeongjun Jang, Hamin Chang, Heein Park +3
In this paper, we present a data-driven output feedback controller for nonlinear systems that achieves practical output regulation, using noise-free input/output measurement data.…