Admittance-Based Surface Alignment for Human-in-the-Loop Robotic Visual Inspection

• URL: http://arxiv.org/abs/2606.18601v1
• Date: Wed, 17 Jun 2026 02:01:51 GMT
• Title: Admittance-Based Surface Alignment for Human-in-the-Loop Robotic Visual Inspection
• Abstract summary: This paper presents a novel real-time, closed-loop robotic orientation control pipeline for precision visual inspection.<n>We design the end-effector as a virtual sphere moving through a medium, such that the resulting physically interpretable mass--damper system generates synchronized, compliant motion.<n>We validate the framework on a 6-DOF manipulator demonstrating stable normal-tracking and a final mean orientation error of 0.4.
• Score: 7.354545339891874
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Precision visual inspection underpins quality assurance across aerospace, semiconductor, and medical manufacturing, where undetected surface anomalies on high-value parts translate directly into scrap, rework, and field failures. Robotic visual inspection requires precise alignment between the end-effector and local surface geometry in the presence of perception noise and surface irregularities. In industrial settings, a human operator is often kept in the loop via teleoperation or shared autonomy, introducing real-time adjustments that render purely offline motion planning inadequate. This motivates control architectures capable of reactive, compliant behavior under combined human and perceptual uncertainty. This paper presents a novel real-time, closed-loop robotic orientation control pipeline for precision visual inspection, with an admittance-based framework that unifies operator input and perception-driven surface alignment. We design the end-effector as a virtual sphere moving through a viscous medium, such that the resulting physically interpretable mass--damper system generates synchronized, compliant motion from orientation error and operator commands. We validate the framework on a 6-DOF manipulator demonstrating stable normal-tracking and a final mean orientation error of 0.4°.

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