From the 2 of 62 linked papers with an AI index.
3 citations · 3 across the 16 of their papers we have counts for
7 papers · 1 filter
Trajectory-Regularized Stochastic Optimal Control via KL Divergence
Mintae Kim, Koushil Sreenath
We introduce trajectory-regularized stochastic optimal control (TRSOC), which augments standard stochastic optimal control (SOC) with a Kullback--Leibler (KL) divergence between co…
A Forward Reachability Perspective on Control Barrier Functions and Discount Factors in Reachability Analysis
Jason J. Choi, Donggun Lee, Boyang Li +4
Control invariant sets are crucial for various methods that aim to design safe control policies for systems whose state constraints must be satisfied over an indefinite time horizo…
Learning-Enabled Iterative Convex Optimization for Safety-Critical Model Predictive Control
Shuo Liu, Zhe Huang, Jun Zeng +2
Safety remains a central challenge in control of dynamical systems, particularly when the boundaries of unsafe sets are complex (e.g., nonconvex, nonsmooth) or unknown. This paper…
When are safety filters safe? On minimum phase conditions of control barrier functions
Jason J. Choi, Claire J. Tomlin, Shankar Sastry +1
In emerging control applications involving multiple and complex tasks, safety filters are gaining prominence as a modular approach to enforcing safety constraints. Among various me…
Data-Driven Hamiltonian for Direct Construction of Safe Set from Trajectory Data
Jason J. Choi, Christopher A. Strong, Koushil Sreenath +2
In continuous-time optimal control, evaluating the Hamiltonian requires solving a constrained optimization problem using the system's dynamics model. Hamilton-Jacobi reachability a…
Dynamic Incentive Selection for Hierarchical Convex Model Predictive Control
Akshay Thirugnanam, Koushil Sreenath
In this paper, we discuss incentive design for hierarchical model predictive control (MPC) systems viewed as Stackelberg games. We consider a hierarchical MPC formulation where, gi…