Sarcos Technology and Robotics announced the award of an expanded contract from the Air Force Research Laboratory (AFRL) for continued development of artificial intelligence (AI)-driven methods and techniques that autonomously control a Heterogeneous Sensing Network (HSN).
As part of the AFRL contract, Sarcos is developing a collaborative sensing solution that enables its Department of Defense (DoD) partners to quickly, accurately, and safely identify, track, and classify time-critical objects using autonomous, heterogeneous sensor networks and AI to improve the operations, safety, data collection, and communication of autonomous platforms, such as Unmanned Aircraft Systems (UASs) and Unmanned Aerial Vehicles (UAVs).
The methods developed will harness the power of a myriad of sensor data to create more robust data sets that enable accurate autonomous operations in dynamic and unstructured environments, such as subsea operations and solar panel installations over diverse terrain, and the application for air force systems. The approach models how humans detect and adapt to their surroundings – using the multiple senses of sight, sound, and feel – to make real-time decisions and adjustments to operate effectively in real-world environments.
AI-Focused Business Unit
Software as a service (SaaS) and AI applications for robotics systems are emerging as expected growth drivers for Sarcos. As a result of the demand for autonomous solutions and building on the work derived from multiple, multi-million dollar, multi-year, AI-focused DoD contracts, Sarcos is also announcing the formation of a new Advanced Technologies division to be led by Dr. Garagić, Sarcos’ chief technology officer.
The Advanced Technologies division will work to progress the development and productization of Sarcos’ AI and machine learning (ML) software platform for generalizable autonomy. The AI and ML software platform will focus on enabling robots to learn from experience using a success-based learning approach. The AI and ML platform will be designed to be usable across a variety of autonomous systems, including factory robots and drones. Additionally, the division will continue to pioneer new algorithms, models, and techniques to unlock new possibilities in the field of robotics, with a focus on initiatives aimed at pushing the boundaries of AI capabilities for robotics operating in dynamic, unstructured environments which pose unique challenges due to their complex and unpredictable nature.
