Abstract: This paper studies the data-driven adaptive iterative learning control (DDAILC) problem for nonlinear stochastic systems. First, the DDAILC framework for nonlinear stochastic systems is ...

As companies move to more AI code writing, humans may not have the necessary skills to validate and debug the AI-written code ...

Background While the incidence of hospital adverse events appeared to be declining before 2019, the COVID-19 pandemic may ...

Five years, one artist, one robot: how Maxim Gehricke made SEN, a 3D animated short film created solo from concept to final render.

AI can be added to legacy motion control systems in three phases with minimal disruption: data collection via edge gateways, non-interfering anomaly detection and supervisory control integration.

When it comes to training robots to perform agile, single-task motor skills, such as handstands or backflips, artificial intelligence methods can be very useful. But if you want to train your robot to ...

Multi-robot systems are increasingly deployed in complex, dynamic environments such as environmental monitoring, industrial automation, and search-and-rescue missions. The coordination of such systems ...

The development of advanced control strategies for prosthetic hands is essential for improving performance and user experience. Soft prosthetic wrists pose substantial control challenges due to their ...

Abstract: This paper gives a tutorial on iterative learning control nearly five decades after what is widely regarded as the first substantive paper in the literature. The focus is on algorithm ...