A Coordinated Dual-Arm Framework for Delicate Snap-Fit Assemblies

• URL: http://arxiv.org/abs/2511.18153v1
• Date: Sat, 22 Nov 2025 18:50:35 GMT
• Title: A Coordinated Dual-Arm Framework for Delicate Snap-Fit Assemblies
• Abstract summary: Delicate snap-fit assemblies demand timely engagement detection and rapid force attenuation to prevent overshoot-induced component damage or assembly failure.<n>We introduce SnapNet, a lightweight neural network that detects snap-fit engagement from joint-velocity transients in real-time.<n>We present a dynamical-systems-based dual-arm coordination framework that integrates SnapNet driven detection with an event-triggered impedance modulation.
• Score: 1.5537556667860262
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Delicate snap-fit assemblies, such as inserting a lens into an eye-wear frame or during electronics assembly, demand timely engagement detection and rapid force attenuation to prevent overshoot-induced component damage or assembly failure. We address these challenges with two key contributions. First, we introduce SnapNet, a lightweight neural network that detects snap-fit engagement from joint-velocity transients in real-time, showing that reliable detection can be achieved using proprioceptive signals without external sensors. Second, we present a dynamical-systems-based dual-arm coordination framework that integrates SnapNet driven detection with an event-triggered impedance modulation, enabling accurate alignment and compliant insertion during delicate snap-fit assemblies. Experiments across diverse geometries on a heterogeneous bimanual platform demonstrate high detection accuracy (over 96% recall) and up to a 30% reduction in peak impact forces compared to standard impedance control.

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