1 citations · 1 across the 15 of their papers we have counts for
7 papers · 1 filter
Sampling-Aware Control Barrier Functions for Safety-Critical and Finite-Time Constrained Control
Shuo Liu, Wei Xiao, Calin A. Belta
In safety-critical control systems, ensuring both safety and feasibility under sampled-data implementations is crucial for practical deployment. Existing Control Barrier Function (…
A Predictive and Sampled-Data Barrier Method for Safe and Efficient Quadrotor Control
Ming Gao, Zhanglin Shangguan, Shuo Liu +3
This paper proposes a cascaded control framework for quadrotor trajectory tracking with formal safety guarantees. First, we design a controller consisting of an outer-loop position…
Learning Safety for Obstacle Avoidance via Control Barrier Functions
Shuo Liu, Zhe Huang, Calin A. Belta
Obstacle avoidance is central to safe navigation, especially for robots with arbitrary and nonconvex geometries operating in cluttered environments. Existing Control Barrier Functi…
Control Barrier Functions via Minkowski Operations for Safe Navigation among Polytopic Sets
Yi-Hsuan Chen, Shuo Liu, Wei Xiao +2
Safely navigating around obstacles while respecting the dynamics, control, and geometry of the underlying system is a key challenge in robotics. Control Barrier Functions (CBFs) ge…
Auxiliary-Variable Adaptive Control Barrier Functions
Shuo Liu, Wei Xiao, Calin A. Belta
This paper addresses the challenge of ensuring safety and feasibility in control systems using Control Barrier Functions (CBFs). Existing CBF-based Quadratic Programs (CBF-QPs) oft…
Safety-Critical Control with Guaranteed Lipschitz Continuity via Filtered Control Barrier Functions
Shuo Liu, Wei Xiao, Calin A. Belta
In safety-critical control systems, ensuring both system safety and smooth control input is essential for practical deployment. Existing Control Barrier Function (CBF) frameworks,…
Risk-Aware Adaptive Control Barrier Functions for Safe Control of Nonlinear Systems under Stochastic Uncertainty
Shuo Liu, Calin A. Belta
This paper addresses the challenge of ensuring safety in stochastic control systems with high-relative-degree constraints, while maintaining feasibility and mitigating conservatism…