Quanergy Systems Inc., a provider of LiDAR sensors and smart sensing solutions, has acquired OTUS People Tracker software from Raytheon BBN Technologies. The software complements Quanergy’s existing software portfolio and, when used with Quanergy’s LiDAR sensors, creates an integrated hardware and software solution for advanced people detection and tracking applications within the security and autonomous driving markets.
“The acquisition of Raytheon BBN’s OTUS People Tracker software is a significant milestone in Quanergy’s strategy and long term road map for LiDAR integration into larger transportation and automation platforms,” says Louay Eldada, Quanergy CEO. “Raytheon BBN is a recognized leader in the space, with the most advanced solution, and Quanergy is now further positioned to expand its footprint and accelerate its ability to deliver new levels of product performance.”
OTUS uses sophisticated human perception algorithms to identify and track people for safety and security in crowded environments at ranges exceeding 100 meters when used with Quanergy LiDAR sensors. The system features segmentation techniques identifying humans, background extraction, object clustering, sophisticated merge and split algorithms, persistent tracking algorithms, and other features supporting robust crowd control.
Support for multiple zones of interest is included, allowing users fine control over active monitoring. The combined solution has advantages over camera systems including the ability to work in any weather or lighting conditions with fewer false alarms, along with the reduction of equipment and labor costs.
About Quanergy Systems
Quanergy Systems Inc. was founded in 2012 and builds on decades of experience of its team in the areas of optics, photonics, optoelectronics, artificial intelligence software and control systems. Headquartered in Sunnyvale, Calif., in the heart of Silicon Valley, Quanergy offers the LiDAR sensors and software for real-time capture and processing of 3D mapping data and object detection, tracking, and classification. In transportation, the data is utilized to greatly improve the accuracy and reliability of on-board driver safety systems and enhance them with perception, scenario analysis and decision making capability for active control, as well as enable autonomous driving in the future.