Intel had 41 patents in robotics during Q2 2024. Intel Corp’s patents in Q2 2024 focus on innovative techniques for calculating a “complexity score” and qualifying allocation score to optimize performance in navigation systems, audio processing using neural networks, traffic management for emergency vehicles, network slice management for service level objectives, and manufacturing processes using collaborative robots and cameras for PCB assembly. GlobalData’s report on Intel gives a 360-degree view of the company including its patenting strategy. Buy the report here.
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Intel had no grants in robotics as a theme in Q2 2024.
Recent Patents
Application: Entity allocation for navigated routes (Patent ID: US20240210185A1)
The patent filed by Intel Corp introduces techniques to calculate a "complexity score" (CS) and qualifying allocation score for entities like vehicles or autonomous mobile robots (AMRs) based on data collected from specific navigation segments. The CS is determined by combining vehicle-based alerts, environment-based data, and other factors with a performance score to provide a context-sensitive view of the performance score. This view is then used to allocate the most suitable entity to a subsequent route that includes the navigation segments.
The computing device described in the patent is configured to receive data from a vehicle, compute a road complexity score (RCS) for road segments based on environment-based data and drive assist alerts, and determine an allocation of entities like vehicles or drivers to a subsequent route. The RCS is calculated as a ratio of static and dynamic components, with the static component based on road type and the dynamic component based on driving conditions. The patent also covers the computation of the CS for navigation segments, involving a similar process of combining static and dynamic components based on historical alerts, camera information, and map data to determine the most suitable entity allocation for subsequent routes.
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GlobalData Patent Analytics tracks bibliographic data, legal events data, point in time patent ownerships, and backward and forward citations from global patenting offices. Textual analysis and official patent classifications are used to group patents into key thematic areas and link them to specific companies across the world’s largest industries.
