Toward Self-Evolving Lunar Robotic Autonomy Through Contract-Governed Skill Registration

Abstract

Permanent lunar habitation will require robotic systems that can maintain infrastructure, recover from local failures, and acquire new operational capabilities under limited Earth supervision. Existing planetary robots are largely fixed-function specialists, while end-to-end foundation-model policies remain difficult to validate and extend for safety-critical surface operations. We present SELENE (Self-Evolving Lunar Embodied ageNt Ecosystem), an architectural proposal for contract-governed lunar robotic autonomy centered on a shared Atomic Action Library A. The key abstraction is the Atomic Action Contract: a typed skill interface that specifies parameters, preconditions, goal predicates, execution bindings, safety envelopes, runtime reports, and validation metadata. Through this contract, a VLM-driven Cognitive Agent plans over executable skills, a multi-modal Execution Agent realizes them through optimization-based controllers, Vision–Language–Action (VLA) policies, Vision–Language–Navigation (VLN) policies, or reinforcement-learned policies, and an offline Evolutionary Agentic Framework synthesizes and registers new candidate contracts without modifying the planner or the execution interface. This paper presents an architecture-level validation of that contract mechanism. We instantiate SELENE across two heterogeneous pathways on LunarBot and its simulation counterpart, with optimization-based control supported as a third execution modality. A pre-trained VLA policy adapted from 100 teleoperated demonstrations achieves 29/30 task success (96.7 percent) in in-domain trials on the physical LunarBot. A curriculum–RL policy instantiates the traversal pathway in simulated lunar-gravity terrain. Together, these results show that the Atomic Action Contract can serve as a common registration and dispatch interface across heterogeneous control modalities. The same contract layer also defines the path toward runtime gap-triggered self-evolution, mission-grade admission, and lunar-environment validation in subsequent system-level studies.