Advances in the Theory of Control Barrier Functions: Addressing practical challenges in safe control synthesis for autonomous and robotic systems
This tutorial paper presents recent work of the authors that extends the theory of Control
Barrier Functions (CBFs) to address practical challenges in the synthesis of safe controllers …
Barrier Functions (CBFs) to address practical challenges in the synthesis of safe controllers …
Data-driven safety filters: Hamilton-jacobi reachability, control barrier functions, and predictive methods for uncertain systems
Today's control engineering problems exhibit an unprecedented complexity, with examples
including the reliable integration of renewable energy sources into power grids, safe …
including the reliable integration of renewable energy sources into power grids, safe …
Dynamic control barrier function-based model predictive control to safety-critical obstacle-avoidance of mobile robot
This paper presents an efficient and safe method to avoid static and dynamic obstacles
based on LiDAR. First, point cloud is used to generate a real-time local grid map for obstacle …
based on LiDAR. First, point cloud is used to generate a real-time local grid map for obstacle …
Safety-critical control and planning for obstacle avoidance between polytopes with control barrier functions
A Thirugnanam, J Zeng… - … Conference on Robotics …, 2022 - ieeexplore.ieee.org
Obstacle avoidance between polytopes is a chal-lenging topic for optimal control and
optimization-based tra-jectory planning problems. Existing work either solves this problem …
optimization-based tra-jectory planning problems. Existing work either solves this problem …
Autonomous racing with multiple vehicles using a parallelized optimization with safety guarantee using control barrier functions
This paper presents a novel planning and control strategy for competing with multiple
vehicles in a car racing scenario. The proposed racing strategy switches between two …
vehicles in a car racing scenario. The proposed racing strategy switches between two …
Iterative convex optimization for model predictive control with discrete-time high-order control barrier functions
Safety is one of the fundamental challenges in control theory. Recently, multi-step optimal
control problems for discrete-time dynamical systems were formulated to enforce stability …
control problems for discrete-time dynamical systems were formulated to enforce stability …
Walking in narrow spaces: Safety-critical locomotion control for quadrupedal robots with duality-based optimization
This paper presents a safety-critical locomotion control framework for quadrupedal robots.
Our goal is to enable quadrupedal robots to safely navigate in cluttered environments. To …
Our goal is to enable quadrupedal robots to safely navigate in cluttered environments. To …
Mega-dagger: Imitation learning with multiple imperfect experts
Imitation learning has been widely applied to various autonomous systems thanks to recent
development in interactive algorithms that address covariate shift and compounding errors …
development in interactive algorithms that address covariate shift and compounding errors …
Incorporating control barrier functions in distributed model predictive control for multi-robot coordinated control
Multirobot motion planning and control has been investigated for decades and is still an
active research area due to the growing demand for both performance optimality and safety …
active research area due to the growing demand for both performance optimality and safety …
Safety-critical ergodic exploration in cluttered environments via control barrier functions
In this paper, we address the problem of safe trajectory planning for autonomous search and
exploration in constrained, cluttered environments. Guaranteeing safe (collision-free) …
exploration in constrained, cluttered environments. Guaranteeing safe (collision-free) …