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Found 11 papers, 0 papers with code
Shortest Trajectory of a Dubins Vehicle with a Controllable Laser
We formulate a novel planar motion planning problem for a Dubins-Laser system that consists of a Dubins vehicle with an attached controllable laser.
Matrix Concentration Inequalities for Sensor Selection
Since our selection of sensors is randomly chosen, the estimation error covariance of the Kalman filter is also a stochastic quantity.
FlipDyn with Control: Resource Takeover Games with Dynamics
We present the FlipDyn, a dynamic game in which two opponents (a defender and an adversary) choose strategies to optimally takeover a resource that involves a dynamical system.
A Multi-Fidelity Bayesian Approach to Safe Controller Design
Safely controlling unknown dynamical systems is one of the biggest challenges in the field of control.
A Concentration-Based Approach for Optimizing the Estimation Performance in Stochastic Sensor Selection
As a consequence, we derive concentration inequalities to bound the estimation error covariance of the Kalman filter in the semi-definite sense.
Perimeter Defense using a Turret with Finite Range and Service Times
Specifically, in the offline version, we establish that in general parameter regimes, this problem is equivalent to solving a Travelling Repairperson Problem with Time Windows (TRP-TW).
Cooperative Evasion by Translating Targets with Variable Speeds
We also characterize a fundamental limit on the total time taken by the pursuer to capture all evaders when the number of evaders is large.
Competitive Perimeter Defense on a Line
We consider a perimeter defense problem in which a single vehicle seeks to defend a compact region from intruders in a one-dimensional environment parameterized by the perimeter size and the intruder-to-vehicle speed ratio.
Probabilistic Performance Bounds for Randomized Sensor Selection in Kalman Filtering
We consider the problem of randomly choosing the sensors of a linear time-invariant dynamical system subject to process and measurement noise.
Automated Adversary Emulation for Cyber-Physical Systems via Reinforcement Learning
Adversary emulation is an offensive exercise that provides a comprehensive assessment of a system's resilience against cyber attacks.
Sequential Randomized Matrix Factorization for Gaussian Processes: Efficient Predictions and Hyper-parameter Optimization
First, we formalize an approach to compute the inverse of the kernel matrix using randomized matrix factorization algorithms in a streaming scenario, i. e., data is generated incrementally over time.
