Environmental Monitoring Microsensor Array (EMMA) for Free Flying Robots

Makel Engineering, Inc. proposes to develop a highly compact Environmental Microsensor Array (EMMA) as a payload for free flying Intra-Vehicular Activity (IVA) robots, such as NASArsquo;s Astrobee, supporting the Integrated System for Autonomous and Adaptive Caretaking (ISAAC) project. EMMA will include machine learning to translate and interpret onboard sensor data (e.g., chemicals, temperature, humidity, pressure, etc.) within the context of planetary facilities. Planned human exploration beyond Earth orbit will rely on an orbiting facility near the Moon,nbsp;called Gateway,nbsp;with intermittent human occupation, requiring robust autonomous inspection and diagnostics tools. EMMArsquo;s sensors and machine learning algorithms will establish nominal background conditions throughout the vehicle, to identify anomalies and trigger further action. The use of machine learning tools will enable EMMA to recognize changes in patterns and decide if additional investigation is granted, e.g., if hot spot detected indicating a potential fire, use chemical sensors to classify material type and further isolate the source of fire, enabling corrective action (e.g., selectively shutting down affected systems.).nbsp;Phase I identified Gateway use cases and defined EMMArsquo;s relevant requirements. EMMA was deployed onboard COTS autonomous floor cleaning robots navigating rooms for data collection and deployed towards simulated fault conditions. Phase I machine learning algorithm was deployed and demonstrated with the data collected by EMMA.nbsp;Phase II will mature the technology taking from lab demonstration to a series of flyable prototypes which will be delivered to NASA for testing in ongoing microgravity experiments and integration with Astrobee at NASA ground-based testbeds at ARC and JSC during the program. The machine learning algorithms will be migrated to the embedded processors, resulting in a standalone prototype system.