2 citations · 4 across the 7 of their papers we have counts for
5 papers · 1 filter
Deep learning from a control vantage point
Álvaro Rodríguez Abella, João Pedro Silvestre, Bahman Gharesifard +1
This article offers an overview of recent developments in deep learning from a control vantage point. It reviews several classes of models including feedforward and residual neural…
PESTO: Formally Correct Registration of LiDAR Point Clouds with Limited Overlap
Valen Yamamoto, Matteo Marchi, Paulo Tabuada
In this paper we tackle the problem of aligning LiDAR point clouds also known as the point cloud registration problem. We propose a new algorithm, PESTO, that exploits tetrahedra a…
Predicting Viral Evolution from a Single Early Measurement Using the Target Cell Limited Model
Rahal Nanayakkara, Paulo Tabuada
Recent advances in diagnostic techniques have enabled the accurate quantification of early-stage viral loads. A key problem of interest is translating these measurements into predi…
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…