NASA is forging ahead with its mission to explore the potential for life on other planets through advanced robotic technology. The agency is focusing on “ocean worlds” such as Jupiter’s moon Europa and Saturn’s moon Enceladus, which are prime candidates for exploration due to the presence of liquid water. These efforts are part of a broader initiative to find signs of life and assess habitability in the solar system.

Central to NASA’s strategy is the use of autonomous robotic systems, designed to overcome the significant communication delays and harsh environments of these distant worlds. Two primary testbeds have been developed to facilitate this goal: the Ocean Worlds Lander Autonomy Testbed (OWLAT) and the Ocean Worlds Autonomy Testbed for Exploration, Research, and Simulation (OceanWATERS).

OWLAT, based at the Jet Propulsion Laboratory, simulates the operations of a spacecraft lander on an ocean world’s surface. Equipped with a six degrees-of-freedom platform and a seven DOF robotic arm, OWLAT performs tasks such as sampling and science operations. This testbed also includes cameras and sensors to replicate the challenges faced in low-gravity environments. The autonomy software interacts with OWLAT through a ROS-based interface, allowing for real-time command and telemetry feedback.

OceanWATERS, developed at NASA’s Ames Research Center, offers a dynamic simulation environment based on ROS. It provides users with the ability to model the European terrain, complete with realistic celestial and sunlight simulations. Important operations such as site surveying, trench digging, and material sampling are supported in this virtual platform, which also incorporates fault injection and power consumption analysis.

Six research teams have been pivotal to advancing these technologies under NASA’s ARROW and COLDTech programs. For instance, the University of South Carolina’s RASPBERRY SI project developed tools for diagnosing faults, while Caltech’s REASIMO project enhanced autonomy in detecting anomalies and selecting sample sites. Collectively, these efforts underscore the importance of autonomy and machine learning in addressing the unique challenges of ocean world exploration.

The shared autonomy interface between OWLAT and OceanWATERS enables cross-functional research, utilizing reinforcement learning, causal reasoning, and advanced planning. These initiatives aim to equip landers with the intelligence needed to manage unforeseen events, optimize sampling strategies, and prioritize tasks based on power availability.

NASA’s strategic investment in autonomous technologies for exploring ocean worlds marks a significant step forward in the search for extraterrestrial life. Through collaborative efforts and innovative testbed developments, the agency is poised to uncover the mysteries of these distant worlds, bringing us closer to answering fundamental questions about life beyond Earth.

Source: Science.nasa