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Found 9 papers, 1 papers with code
Backup Plan Constrained Model Predictive Control with Guaranteed Stability
To include this new safety concept in control problems, we formulate a feasibility maximization problem aiming to maximize the feasibility of the primary and alternative missions.
Certified Robust Control under Adversarial Perturbations
Autonomous systems increasingly rely on machine learning techniques to transform high-dimensional raw inputs into predictions that are then used for decision-making and control.
Synergistic Redundancy: Towards Verifiable Safety for Autonomous Vehicles
The synergistic safety layer uses only verifiable and logically analyzable software to fulfill its tasks.
Verifiable Obstacle Detection
Perception of obstacles remains a critical safety concern for autonomous vehicles.
Path Integral Methods with Stochastic Control Barrier Functions
In this paper, we utilize Stochastic Control Barrier Functions (SCBFs) constraints to limit sample regions in the sample-based algorithm, ensuring safety in a probabilistic sense and improving sample efficiency with a stochastic differential equation.
Protective Mission against a Highly Maneuverable Rogue Drone Using Defense Margin Strategy
We introduce a new concept of defense margin to complement an existing strategy and construct a control strategy that successfully solves our problem.
Control Barrier Function Augmentation in Sampling-based Control Algorithm for Sample Efficiency
For a nonlinear stochastic path planning problem, sampling-based algorithms generate thousands of random sample trajectories to find the optimal path while guaranteeing safety by Lagrangian penalty methods.
Constrained Attack-Resilient Estimation of Stochastic Cyber-Physical Systems
In this paper, a constrained attack-resilient estimation algorithm (CARE) is developed for stochastic cyber-physical systems.
Backup Plan Constrained Model Predictive Control
To incorporate this new safety concept in control problems, we formulate a feasibility maximization problem that adopts additional (virtual) input horizons toward the alternative missions on top of the input horizon toward the primary mission.
