Fiber Alignment and Photonic Chip Test & Assembly Just Got Easier
The new algorithm and technology have the potential to drastically reduce complex fiber alignment and photonics alignment procedure times by several orders of magnitude, surpassing any other existing technique used for automated fiber optic alignment in the market.
Nanopositioning and Motion Control Solutions for the Semiconductor Industry
Recently, the convergence of photonics and electronics, known as Silicon Photonics, has marked a significant advancement in both performance and the reduction of power consumption.
Piezoelectric and Piezoresistive Effects in Robotics
Below, we'll look at piezoelectric and piezoresistive effects. Neither of those is new, but engineers are applying them in creative ways within the field of robotics or through methods that may one day improve robotics.
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Featured Product
Palladyne IQ - Unlocking new frontiers for robotic performance.
Palladyne IQ is a closed-loop autonomy software that uses artificial intelligence (AI) and machine learning (ML) technologies to provide human-like reasoning capabilities for industrial robots and collaborative robots (cobots). By enabling robots to perceive variations or changes in the real-world environment and adapt to them dynamically, Palladyne IQ helps make robots smarter today and ready to handle jobs that have historically been too complex to automate.
Robotics and Automation - Featured Company
Palladyne AI Corp.
Welcome to Palladyne AI, where we unleash the power of robotics with our revolutionary AI software platform for the physical world. In a world where robots are progressing toward human-like adaptability, seamlessly navigating dynamic environments and conquering complex tasks with unparalleled efficiency, Palladyne AI stands as the beacon of innovation toward that future reality. Through our cutting-edge artificial intelligence (AI) software platform, we are redefining the boundaries of robotics. Our goal is simple: Help companies with autonomy in their robotics operations by addressing key challenges of traditional robotic deployments.
