61 citations · 69 across the 6 of their papers we have counts for
6 papers
Safe Beyond the Horizon: Efficient Sampling-based MPC with Neural Control Barrier Functions
Ji Yin, Oswin So, Eric Yang Yu +2
A common problem when using model predictive control (MPC) in practice is the satisfaction of safety specifications beyond the prediction horizon. While theoretical works have show…
Safety on the Fly: Constructing Robust Safety Filters via Policy Control Barrier Functions at Runtime
Luzia Knoedler, Oswin So, Ji Yin +5
Control Barrier Functions (CBFs) have proven to be an effective tool for performing safe control synthesis for nonlinear systems. However, guaranteeing safety in the presence of di…
Chance-Constrained Information-Theoretic Stochastic Model Predictive Control with Safety Shielding
Ji Yin, Panagiotis Tsiotras, Karl Berntorp
This paper introduces a novel nonlinear stochastic model predictive control path integral (MPPI) method, which considers chance constraints on system states. The proposed belief-sp…
Shield Model Predictive Path Integral: A Computationally Efficient Robust MPC Approach Using Control Barrier Functions
Ji Yin, Charles Dawson, Chuchu Fan +1
Model Predictive Path Integral (MPPI) control is a type of sampling-based model predictive control that simulates thousands of trajectories and uses these trajectories to synthesiz…
Risk-Aware Model Predictive Path Integral Control Using Conditional Value-at-Risk
Ji Yin, Zhiyuan Zhang, Panagiotis Tsiotras
In this paper, we present a novel Model Predictive Control method for autonomous robots subject to arbitrary forms of uncertainty. The proposed Risk-Aware Model Predictive Path Int…
Trajectory Distribution Control for Model Predictive Path Integral Control using Covariance Steering
Ji Yin, Zhiyuan Zhang, Evangelos Theodorou +1
This paper presents a novel control approach for autonomous systems operating under uncertainty. We combine Model Predictive Path Integral (MPPI) control with Covariance Steering (…