Systems Engineering

Researchers from the University of Science and Technology of China have unveiled a groundbreaking study on how trout optimize their swimming efficiency, offering valuable insights for biomechanics, fluid dynamics, and engineering. The team, led by Ta

Researchers from KU Leuven, including Sander De Witte, Jeroen Taets, Andras Retzler, Guillaume Crevecoeur, and Tom Lefebvre, have developed a novel approach to optimize robotic systems using human preferences. Their work, titled “How to Capture Human

Researchers from the University of Freiburg and the University of Messina have unveiled a breakthrough in soft robotics that could redefine the capabilities of these flexible machines. The team, led by Eduardo Sergio Oliveros-Mata and Giovanni Finocc

The GigaWorld Team, a collaborative group of researchers from various institutions, has introduced GigaWorld-0, a groundbreaking framework designed to empower embodied AI through world models. This innovative approach aims to create a scalable, data-

Researchers from the University of Minnesota and the University of Science and Technology of China have developed a hybrid reinforcement learning (RL) framework that bridges the gap between simulation and real-world applications in the 3D bin packing

Researchers from the University of São Paulo, Brazil, have developed a machine-learning solution to improve fault location accuracy in onshore wind farm collector networks. The team, led by A. J. Alves Junior and including M. J. B. B. Davi, R. A. S.

Researchers at the Technische Universität Dresden have introduced a novel approach to designing robust control systems without the need for detailed process modeling. This development, led by Michael Ruderman, addresses a common challenge in practica

Researchers Haoyu Wang, Andrea Alfonsi, Roberto Ponciroli, and Richard Vilim have introduced a novel data-driven approach to selecting state variables for dynamical systems, offering a significant advancement in the field of Digital Twins and control

Researchers Franklin Cardenoso and Wouter Caarls have introduced a groundbreaking framework designed to streamline the process of creating effective reward functions in reinforcement learning (RL). Their work, titled “LEARN-Opt (LLM-based Evaluator a

Researchers from the Max Planck Institute for Intelligent Systems and ETH Zurich have made a significant stride in the field of robotics with the development of SPEAR-1, a new robotic foundation model that promises to revolutionize the way robots und