IEEE The Institute is marking 50 years of informing members about IEEE initiatives, technical standards, and career guidance. This milestone highlights its enduring role in the engineering community.
The landscape of factory automation is evolving, making strong automation software skills indispensable. This shift means engineers need to master dashboards, data, and updates for future success in robotics and industrial control.
SS Innovations recently highlighted key surgical robot challenges and their innovative solutions. This discussion sheds light on advancements in medical robotics, particularly for emergency care in challenging environments.
KUKA is set to present its latest advancements in scalable machine tending robotics at IMTS 2026. The demonstrations will highlight how manufacturers can more easily adopt robotic automation through a service-based approach, reducing complexity for evolving production needs.
New research demonstrates that ordinary WiFi signals can be used for WiFi human identification, allowing recognition of individuals even without devices. This breakthrough has implications for various applications.
A new development showcases how millifluidics soft clocks can perform computation using liquids, opening doors for novel applications in soft robotics and beyond traditional electronics.
Genesis AI has unveiled Genesis World 1.0, a new robotics simulation platform. This innovation aims to dramatically reduce development and testing times for robotic AI systems, moving from days to minutes through large-scale virtual environments.
The 2026 Robotics Summit 2026 insights from a recent expo are now available. Discover key discussions and emerging trends in the robotics industry relevant for students.
The introduction of compact touchless position sensors marks a significant development for robotics and automation. These advanced components offer enhanced precision and durability, opening new possibilities for student projects and research in engineering fields.
A new miniature AI spectrometer chip from UC Davis is revolutionizing chemical analysis. This tiny device combines smart silicon sensors with machine learning, bringing lab-style spectral analysis to a compact, portable form factor.