Swarm robotic search aims at searching targets using a large number of collaborating
simple mobile robots, with applications to search and rescue and hazard localization. In this …

Swarm-robotic approaches to search and target localization, where target sources emit a
spatially varying signal, promise unparalleled time efficiency and robustness. With most …

Bioinspired surface riblets have been known to improve drag performance by altering the
near-wall flow structures, especially in the transitional flow regime. Unlike conventional riblet …

Decentralized swarm robotic solutions to searching for targets that emit a spatially varying
signal promise task parallelism, time efficiency, and fault tolerance. It is, however …

This paper presents a physics-aware surrogate-based approach (aka PhySBO) for
computationally efficient optimization of complex systems. This approach is founded on a …

This paper delves into the paradigm of zero-shot object detection, a fundamental challenge
in computer vision. Traditional approaches encounter limitations in recognizing novel …

The past decade of artifcial intelligence and deep learning has made tremendous progress
in highly perceptive tasks such as image recognition. Deep learning algorithms map high …

Swarm robotic system is a large number of autonomous systems working together to
accomplish collective goals. Swarm systems offer remarkable operational flexibility …

In many cases, a high fidelity or “full physics” model is either not available or, if available, is
computationally prohibitive to evaluate, especially in time-sensitive usage contexts like …

Abstract Physics-Infused Machine Learning (PIML) architectures aim at integrating machine
learning with computationally efficient (partial) physics models, leading to improved …