SCOPE: Field-of-View-Aware Path Planning in Unknown 3D Environments via Safety-Volume Certification
arXiv:2608.04420v1 Announce Type: new 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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[Submitted on 5 Aug 2026]
Title:SCOPE: Field-of-View-Aware Path Planning in Unknown 3D Environments via Safety-Volume Certification
View a PDF of the paper titled SCOPE: Field-of-View-Aware Path Planning in Unknown 3D Environments via Safety-Volume Certification, by Junbin Yuan and 4 other authors
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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.
Comments: Project website: this https URL
Subjects:
Robotics (cs.RO)
Cite as: arXiv:2608.04420 [cs.RO]
(or arXiv:2608.04420v1 [cs.RO] for this version)
https://doi.org/10.48550/arXiv.2608.04420
arXiv-issued DOI via DataCite (pending registration)
Submission history
From: Junbin Yuan [view email] [v1] Wed, 5 Aug 2026 04:01:38 UTC (12,433 KB)
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