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Found 13 papers, 0 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.
Learning When to Use Adaptive Adversarial Image Perturbations against Autonomous Vehicles
We propose a multi-level stochastic optimization framework that monitors an attacker's capability of generating the adversarial perturbations.
Multi-time Predictions of Wildfire Grid Map using Remote Sensing Local Data
Due to recent climate changes, we have seen more frequent and severe wildfires in the United States.
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.
Learning Wildfire Model from Incomplete State Observations
As wildfires are expected to become more frequent and severe, improved prediction models are vital to mitigating risk and allocating resources.
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.
Accelerated Almost-Sure Convergence Rates for Nonconvex Stochastic Gradient Descent using Stochastic Learning Rates
Theoretical results show accelerated almost-sure convergence rates of Stochastic Gradient Descent in a nonconvex setting when using an appropriate stochastic learning rate, compared to a deterministic-learning-rate scheme.
Stochastic Learning Rate Optimization in the Stochastic Approximation and Online Learning Settings
In this work, multiplicative stochasticity is applied to the learning rate of stochastic optimization algorithms, giving rise to stochastic learning-rate schemes.
Time Coordination of Multiple UAVs over Switching Communication Networks with Digraph Topologies
This paper presents a time-coordination algorithm for multiple UAVs executing cooperative missions.
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.
Learning Image Attacks toward Vision Guided Autonomous Vehicles
While adversarial neural networks have been shown successful for static image attacks, very few approaches have been developed for attacking online image streams while taking into account the underlying physical dynamics of autonomous vehicles, their mission, and environment.
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.
SL1-Simplex: Safe Velocity Regulation of Self-Driving Vehicles in Dynamic and Unforeseen Environments
Due to the high dependence of vehicle dynamics on the driving environments, the proposed Simplex leverages the finite-time model learning to timely learn and update the vehicle model for $\mathcal{L}_{1}$ adaptive controller, when any deviation from the safety envelope or the uncertainty measurement threshold occurs in the unforeseen driving environments.
