Whether building instrumentation for industrial robots, implementing control systems for unmanned aerial or undersea vehicles vehicles, or extending your legacy robotics platforms with new sensors and AI/ML models, Signaloid's hardware modules implementing our UxHw technology help you get to solution designs quicker. Get to your final implementations for sensor-driven robotics systems quicker and with fewer engineering and design costs by taking advantage of Signaloid's UxHw's enablement of key robot-supporting techniques ranging from hardware-assisted Bayesian inference to hardware accelerated Gaussian Process prediction. And achieve all of these facilities using hot-swappable hardware modules that take advantage of the ubiquity of both hardware (microSD and full-sized SD slots) and software for SD mass storage devices in robotics platforms.
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Solutions
Choose between different capability levels of Signaloid’s UxHw technology to integrate into your robotics hardware platforms. Choose between different form factors that all take advantage of existing mass storage device interfaces, enabling easy integration in your robot firmware or operating system (e.g., ROS, FreeRTOS, or Linux).
Example Performance Validation
Achieve 2x to over 300x speedups in your uncertainty quantification compared with existing C, C++, and FORTRAN models computing Monte Carlo simulations. Interested instead in adopting data-driven AI/ML models to replace your hand-crafted C/C++/FORTRAN code? Use the AI/ML runtime systems which run on the Signaloid cloud compute engine to get automated uncertainty quantification for the output of your AI/ML model predictions. See not just error bars but the full distribution of model output uncertainty.
Technology Explainers
Signaloid's technology provides deterministic uncertainty tracking methods by utilising efficient arithmetic on probability distributions while integrating with existing edge hardware. These technology explainer articles provide further details on how this technology benefits embedded robotics and manufacturing applications, from the underlying mathematics to the engineering implementations.
