SCOPE: Field-of-View-Aware Path Planning in Unknown 3D Environments via Safety-Volume Certification

• URL: http://arxiv.org/abs/2608.04420v1
• Date: Wed, 05 Aug 2026 04:01:38 GMT
• Title: SCOPE: Field-of-View-Aware Path Planning in Unknown 3D Environments via Safety-Volume Certification
• Abstract summary: A body-mounted limited-field-of-view sensor requires the complete robot-inflated volume of an intended motion to be observed and verified free before execution.<n>We propose SCOPE (Safety Certification through Observation Planning and Execution), a planning framework that decouples optimistic goal-directed guidance from certified execution.<n>A certified preview mechanism and an observation-aware trajectory optimization backend enable smooth execution.
• Score: 4.246800075908515
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Safe navigation with a body-mounted limited-field-of-view sensor requires the complete robot-inflated volume of an intended motion to be observed and verified free before execution. We formulate this requirement as online safety-volume certification in an unknown voxel map and construct a certified graph whose vertices correspond exactly to positions with fully known-free safety volumes. Based on this representation, we propose SCOPE (Safety Certification through Observation Planning and Execution), a planning framework that decouples optimistic goal-directed guidance from certified execution. SCOPE converts the first uncertified point along an optimistic route into an explicit observation obligation, resolves it through target-centric viewpoint search, and recursively clears intermediate obligations when useful viewpoints are not yet certified-reachable. A certified preview mechanism and an observation-aware trajectory optimization backend enable smooth execution. We prove conditional complete planning: under ideal monotone sensing and exhaustive finite-domain graph search, SCOPE reaches the goal whenever a finite feasible sequence of certified sensing actions exists within its planning primitives. Across 60 randomized tasks in three unknown 3D environments, SCOPE reaches every goal while maintaining near-zero entry into non-certified inflated space. Preview reduces mean mission time by 27%, and real-robot demonstrations in two representative scenarios validate the complete system.

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