Fail-Active Autonomy in Unknown-Unknown Situations for Deep Space Missions

This paper discusses the environment anomalies that the CARL/COLDArm system was subjected to utilizing the OceanWATERS simulator to demonstrate "fail-active" autonomy. The geotechnical task used throughout our tests is the pressure sinkage test performed at various locations to assess the surface hardness using its end effector. As the lander is performing the pressure sinkage tests, environmental anomalies are injected into the simulation, including fiducial obscuration due to shadowing and unexpected ice build-up on the COLDArm end effector. Adjustments to the controller's available safe actions and variations in causal model knowledge that informs controller actions were assessed, using both learned and expert-developed causal models. Through these tests and demonstrations in the OceanWATERS simulator, CARL uses its causal model to infer that the fail-state is triggered by an explicit cause. Based on the inference from the causal model, CARL selects from various possible actions to resolve the fail-state from several possible actions, including COLDArm pose adjustment, camera integration time change, light activation, and heater power adjustment. This allows the lander to proceed with completing its pressure sinkage tests.