Description: The Event-Based Sensing and Navigation Technologies (EBSNT) project aims to develop, integrate, and test a perception and planning avionics suite and associated on-board software in response to NASA’s Subtopic “H6.22 Deep Neural Net and Neuromorphic Processors for In-Space Autonomy and Cognition” within the scope of “Neuromorphic Software for Cognition and Learning for Space Missions.” EBSNT forms the foundation of a Relative Pose Determination and Control Subsystem (RPDCS) integrated on board a Servicer Space Vehicle (SSV) that performs Rendezvous, Proximity Operations, and Docking (RPOD) with a Client SV (CSV). The RPDCS uses a hybrid architecture of event-based sensors, interconnected Spiking Neural Networks (SNNs) and traditional sensors, actuators, and von Neumann computers that enables the SSV to autonomously i) determine the relative pose and pose rate, i.e., relative translation and rotation velocities, between the SSV and a goal feature on the CSV; ii) plan a relative trajectory that places the SSV at a commanded relative pose with respect to the specified feature of the CSV; iii) perform translation and attitude maneuvers to acquire and maintain the commanded relative pose; and iv) monitor the health status of the SSV and take appropriate action to ensure mission safety in case of SSV component and subsystem failure.

Benefits: On-orbit Service, Assembly, and Manufacture missions and multi-spacecraft human and robotic solar system exploration mission.

Derived technologies are applicable to aerial drone swarming and convoying with applications ranging from intelligence collection to urban air mobility to package delivery.