27th February 2017 – San Francisco, CA: Occipital, Inc. and Inuitive Ltd. announce their collaboration to bring to market a complete hardware and software solution that brings highly efficient room-scale sensing and SLAM (simultaneous localization and mapping) to next generation mixed reality, augmented reality and virtual reality (MR/AR/VR) headsets and robotics.

NU3000The joint offering enables manufacturers of AR/VR/MR headsets and home & industrial robots to easily integrate efficient, low-latency 3D sensing and SLAM into their next generation of products. The solution merges Occipital’s Structure Core embeddable depth sensor with Inuitive’s NU3000 depth processing chip.

For the past year, Occipital and Inuitive have worked together to tightly integrate Structure Core and NU3000 to achieve levels of performance that minimize host system loads while delivering an exceptional user experience. The combined Structure Core and NU3000 offers high performance with low power consumption.

The market-leading solution is able to sense depths from 30cm to greater than 5m with an accuracy as high as ±0.17% RMS at 1m (using fit-to-plane). The integrated solution reduces CPU load to be equivalent to <25% of a recent dual-core ARM CPU during 6-DoF tracking.

System latency (from camera to fully-tracked pose) is just 10ms. Even with this high performance, the power consumption for depth + visible is between 1.3W and 2.0W, depending on the configuration selected.

Along with Structure Core, Occipital also offers Bridge Engine, an advanced MR software engine and development platform. Available on multiple platforms, Bridge Engine allows manufacturers to accelerate development of market-ready devices with advanced position-tracked VR and mixed reality capabilities.

The combination of Structure Core and NU3000 is designed for use in the new generation of home & industrial robots as well as headsets. In particular, Structure Core’s dual infrared cameras can be used for stereo depth sensing when ambient sunlight would otherwise blind robotic navigation systems that rely on time-of-flight or structured light depth sensors.

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