80 citations · 100 across the 35 of their papers we have counts for
25 papers · 1 filter
Lifting Safety Through Reduced-Order Model Architectures: An Invariant Manifold Approach
Massimiliano de Sa, Aaron D. Ames
Reduced-order model architectures are often used to decompose complex safety-critical control design tasks into tractable subproblems. In this paradigm, one must ask: when does the…
Constructive Safety-Critical Control for a Class of Underactuated Systems: A Hierarchical Approach
Massimiliano de Sa, Aaron D. Ames
Underactuated systems with nontrivial geometry are abundant in practical robotic problems. However, little is known about constructive safety-critical control design in the presenc…
A Recursive CBF Framework for Safety under State Uncertainty
Rahal Nanayakkara, Aaron D. Ames, Paulo Tabuada
The practical implementation of Control Barrier Functions (CBFs) for safety-critical control is often hindered by uncertainty in the knowledge of the state. While existing robust C…
A Duality-Based Optimization Formulation of Safe Control Design with State Uncertainties
Xiao Tan, Rahal Nanayakkara, Paulo Tabuada +1
State estimation uncertainty is prevalent in real-world applications, hindering the application of safety-critical control. Existing methods address this by strengthening a Control…
Generalizations of Backup Control Barrier Functions: Expansion and Adaptation for Input-Bounded Safety-Critical Control
David E. J. van Wijk, Dohyun Lee, Ersin Das +3
Guaranteeing the safety of nonlinear systems with bounded inputs remains a key challenge in safe autonomy. Backup control barrier functions (bCBFs) provide a powerful mechanism for…
Topological Obstructions to the Existence of Control Barrier Functions
Massimiliano de Sa, Aaron D. Ames
In 1983, Brockett developed a topological necessary condition for the existence of continuous, asymptotically stabilizing control laws. Building upon recent work on necessary condi…
Input-to-State Safe Backstepping: Robust Safety-Critical Control with Unmatched Uncertainties
Max H. Cohen, Pio Ong, Aaron D. Ames
Guaranteeing safety in the presence of unmatched disturbances -- uncertainties that cannot be directly canceled by the control input -- remains a key challenge in nonlinear control…
Explicit Control Barrier Function-based Safety Filters and their Resource-Aware Computation
Pol Mestres, Shima Sadat Mousavi, Pio Ong +4
This paper studies the efficient implementation of safety filters that are designed using control barrier functions (CBFs), which minimally modify a nominal controller to render it…
From Bundles to Backstepping: Geometric Control Barrier Functions for Safety-Critical Control on Manifolds
Massimiliano de Sa, Pio Ong, Aaron D. Ames
Control barrier functions (CBFs) have a well-established theory in Euclidean spaces, yet still lack general formulations and constructive synthesis tools for systems evolving on ma…
Combinatorial Control Barrier Functions: Nested Boolean and p-choose-r Compositions of Safety Constraints
Pio Ong, Haejoon Lee, Tamas G. Molnar +2
This paper investigates the problem of composing multiple control barrier functions (CBFs) -- and matrix control barrier functions (MCBFs) -- through logical and combinatorial oper…
Matrix Control Barrier Functions
Pio Ong, Yicheng Xu, Ryan M. Bena +2
This paper generalizes the control barrier function framework by replacing scalar-valued functions with matrix-valued ones. Specifically, we develop barrier conditions for safe set…
Safety Under State Uncertainty: Robustifying Control Barrier Functions
Rahal Nanayakkara, Aaron D. Ames, Paulo Tabuada
Safety-critical control is a crucial aspect of modern systems, and Control Barrier Functions (CBFs) have gained popularity as the framework of choice for ensuring safety. However,…
Safe Navigation under State Uncertainty: Online Adaptation for Robust Control Barrier Functions
Ersin Das, Rahal Nanayakkara, Xiao Tan +4
Measurements and state estimates are often imperfect in control practice, posing challenges for safety-critical applications, where safety guarantees rely on accurate state informa…
On the Properties of Optimal-Decay Control Barrier Functions
Pio Ong, Max H. Cohen, Tamas G. Molnar +1
Control barrier functions provide a powerful means for synthesizing safety filters that ensure safety framed as forward set invariance. Key to CBFs' effectiveness is the simple ine…
Secure Safety Filter Design for Sampled-data Nonlinear Systems under Sensor Spoofing Attacks
Xiao Tan, Pio Ong, Paulo Tabuada +1
This paper presents a secure safety filter design for nonlinear systems under sensor spoofing attacks. Existing approaches primarily focus on linear systems which limits their appl…
Control Barrier Function Synthesis for Nonlinear Systems with Dual Relative Degree
Gilbert Bahati, Ryan K. Cosner, Max H. Cohen +2
Control barrier functions (CBFs) are a powerful tool for synthesizing safe control actions; however, constructing CBFs remains difficult for general nonlinear systems. In this work…
Computationally Efficient Safe Control of Linear Systems under Severe Sensor Attacks
Xiao Tan, Pio Ong, Paulo Tabuada +1
Cyber-physical systems are prone to sensor attacks that can compromise safety. A common approach to synthesizing controllers robust to sensor attacks is secure state reconstruction…
Rectified Control Barrier Functions for High-Order Safety Constraints
Pio Ong, Max H. Cohen, Tamas G. Molnar +1
This paper presents a novel approach for synthesizing control barrier functions (CBFs) from high relative degree safety constraints: Rectified CBFs (ReCBFs). We begin by discussing…
Hierarchical Event-Triggered Systems: Safe Learning of Quasi-Optimal Deadline Policies
Pio Ong, Manuel Mazo, Aaron D. Ames
We present a hierarchical architecture to improve the efficiency of event-triggered control (ETC) in reducing resource consumption. This paper considers event-triggered systems gen…
Safety of Linear Systems under Severe Sensor Attacks
Xiao Tan, Pio Ong, Paulo Tabuada +1
Cyber-physical systems can be subject to sensor attacks, e.g., sensor spoofing, leading to unsafe behaviors. This paper addresses this problem in the context of linear systems when…
Safety-Critical Control for Autonomous Systems: Control Barrier Functions via Reduced-Order Models
Max H. Cohen, Tamas G. Molnar, Aaron D. Ames
Modern autonomous systems, such as flying, legged, and wheeled robots, are generally characterized by high-dimensional nonlinear dynamics, which presents challenges for model-based…
Collision Avoidance and Geofencing for Fixed-wing Aircraft with Control Barrier Functions
Tamas G. Molnar, Suresh K. Kannan, James Cunningham +3
Safety-critical failures often have fatal consequences in aerospace control. Control systems on aircraft, therefore, must ensure the strict satisfaction of safety constraints, pref…
Generative Modeling of Residuals for Real-Time Risk-Sensitive Safety with Discrete-Time Control Barrier Functions
Ryan K. Cosner, Igor Sadalski, Jana K. Woo +2
A key source of brittleness for robotic systems is the presence of model uncertainty and external disturbances. Most existing approaches to robust control either seek to bound the…
Safety-Critical Control of Nonholonomic Vehicles in Dynamic Environments using Velocity Obstacles
Aurora Haraldsen, Martin S. Wiig, Aaron D. Ames +1
This paper considers collision avoidance for vehicles with first-order nonholonomic constraints maintaining nonzero forward speeds, moving within dynamic environments. We leverage…