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The safety filter: A unified view of safety-critical control in autonomous systems
Recent years have seen significant progress in the realm of robot autonomy, accompanied
by the expanding reach of robotic technologies. However, the emergence of new …
by the expanding reach of robotic technologies. However, the emergence of new …
Safety-critical control for autonomous systems: Control barrier functions via reduced-order models
Modern autonomous systems, such as flying, legged, and wheeled robots, are generally
characterized by high-dimensional nonlinear dynamics, which presents challenges for …
characterized by high-dimensional nonlinear dynamics, which presents challenges for …
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 …
Safe control under input limits with neural control barrier functions
We propose new methods to synthesize control barrier function (CBF) based safe controllers
that avoid input saturation, which can cause safety violations. In particular, our method is …
that avoid input saturation, which can cause safety violations. In particular, our method is …
How to train your neural control barrier function: Learning safety filters for complex input-constrained systems
Control barrier functions (CBFs) have become popular as a safety filter to guarantee the
safety of nonlinear dynamical systems for arbitrary inputs. However, it is difficult to construct …
safety of nonlinear dynamical systems for arbitrary inputs. However, it is difficult to construct …
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 …
Marc: Multipolicy and risk-aware contingency planning for autonomous driving
Generating safe and non-conservative behaviors in dense, dynamic environments remains
challenging for automated vehicles due to the stochastic nature of traffic participants' …
challenging for automated vehicles due to the stochastic nature of traffic participants' …
Runtime assurance for safety-critical systems: An introduction to safety filtering approaches for complex control systems
More than three miles above the Arizona desert, an F-16 student pilot experienced a gravity-
induced loss of consciousness, passing out while turning at nearly 9Gs (nine times the force …
induced loss of consciousness, passing out while turning at nearly 9Gs (nine times the force …
Onboard safety guarantees for racing drones: High-speed geofencing with control barrier functions
This letter details the theory and implementation behind practically ensuring safety of
remotely piloted racing drones. We demonstrate robust and practical safety guarantees on a …
remotely piloted racing drones. We demonstrate robust and practical safety guarantees on a …
Gcbf+: A neural graph control barrier function framework for distributed safe multi-agent control
Distributed, scalable, and safe control of large-scale multi-agent systems is a challenging
problem. In this paper, we design a distributed framework for safe multi-agent control in …
problem. In this paper, we design a distributed framework for safe multi-agent control in …