Governed Capability Evolution for Embodied Agents: Safe Upgrade, Compatibility Checking, and Runtime Rollback for Embodied Capability Modules

arXiv cs.RO / 4/10/2026

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Key Points

  • The paper addresses a systems gap for embodied agents: how to safely deploy evolved executable capability modules without violating policies, breaking execution assumptions, or losing recovery guarantees.
  • It proposes a lifecycle-aware “governed capability evolution” framework that treats each new capability version as a governed deployment candidate, using staged runtime steps like candidate validation, sandbox evaluation, shadow deployment, gated activation, online monitoring, and rollback.
  • The framework defines four upgrade compatibility checks—interface, policy, behavioral, and recovery—to prevent unsafe or incompatible activations.
  • Experiments across 6 upgrade rounds and 15 random seeds show that naive upgrades reach 72.9% task success but allow unsafe activations to rise to 60%, while governed upgrades keep task success similar (67.4%) and achieve zero unsafe activations throughout (Wilcoxon p=0.003).
  • Shadow deployment uncovers about 40% of regressions missed by sandbox evaluation alone, and rollback successfully handles 79.8% of post-activation drift cases.

Abstract

Embodied agents are increasingly expected to improve over time by updating their executable capabilities rather than rewriting the agent itself. Prior work has separately studied modular capability packaging, capability evolution, and runtime governance. However, a key systems problem remains underexplored: once an embodied capability module evolves into a new version, how can the hosting system deploy it safely without breaking policy constraints, execution assumptions, or recovery guarantees? We formulate governed capability evolution as a first-class systems problem for embodied agents. We propose a lifecycle-aware upgrade framework in which every new capability version is treated as a governed deployment candidate rather than an immediately executable replacement. The framework introduces four upgrade compatibility checks -- interface, policy, behavioral, and recovery -- and organizes them into a staged runtime pipeline comprising candidate validation, sandbox evaluation, shadow deployment, gated activation, online monitoring, and rollback. We evaluate over 6 rounds of capability upgrade with 15 random seeds. Naive upgrade achieves 72.9% task success but drives unsafe activation to 60% by the final round; governed upgrade retains comparable success (67.4%) while maintaining zero unsafe activations across all rounds (Wilcoxon p=0.003). Shadow deployment reveals 40% of regressions invisible to sandbox evaluation alone, and rollback succeeds in 79.8% of post-activation drift scenarios.