Neurotechnology, a provider of deep learning-based solutions, robotics and high-precision biometric identification technologies, has announced the release of the SentiBotics Navigation Software Development Kit. Designed for researchers and engineers working on autonomous robot navigation, SentiBotics Navigation SDK provides the tools for the development of pathway learning, including object recognition and obstacle detection, in robotics systems.The system derives navigational parameters through initial user-driven input, developing a framework of data that then becomes the environment for subsequent autonomous operation. The software also allows for autonomous recharging capability once the functional environmental features are identified.SentiBotics Navigation SDK can be purchased as either a complete package, a ready-to-run robotics system that includes Neurotechnology's mobile reference platform prototype, or as a software-only option for integration into existing robotics hardware. A free 30-day trial of the SDK is available for use in a Gazebo robotics simulator.”SentiBotics Navigation SDK provides deep neural network based robot navigation software ready for integration into customers' robotic systems,” said Dr. Povilas Daniusis, Neurotechnology team lead for robotics. “The SDK provides robust functionality for robotics engineers as well as academic and educational institutions. The robotics algorithm implementations are designed for robots operating in real indoor environments. They can also be used to compose more complex autonomous behavior.”The Navigation SDK improves on the previously released SentiBotics Development Kit 2.0 and offers some important practical advantages when compared to other available autonomous navigation systems.It relies on a single webcam and two low cost ultrasonic range finders for input and allows autonomous navigation over long distances (hundreds of meters or more). The new SDK also enables navigation system training, and further adaptation to visual changes in the environment may be enhanced through additional user input, altering the system by additional data collection in changed areas or problematic locations.
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