Robust Peg-in-Hole Assembly under Uncertainties via Compliant and Interactive Contact-Rich Manipulation

2025-06-28

AI Summary

To address insufficient robustness in high-precision peg-in-hole assembly caused by perceptual and physical uncertainties, this paper proposes a model-free, contact-driven compliant manipulation method. We formalize uncertainty absorption and contact-guided insertion via a “manipulation funnel” mechanism operating across a multi-state space, enabling progressive localization and insertion without reliance on high-fidelity sensing. The approach integrates collision-tolerant motion planning, exploitation of environmental constraints, and iterative state convergence—systematically characterizing contact-driven robustness for the first time. It supports general-purpose assembly across scales, heterogeneous geometries, and diverse material pairings. Experimental validation on the NIST standard task board and under stringent tolerance conditions demonstrates high success rates, strong generalization capability, and significant engineering applicability.

Technology Category

• Intelligent Robots: Manipulation
• Computer Vision: Low Level & Physics-based Vision
• Planning, Routing, and Scheduling: Replanning and Plan Repair

Application Category

• Responsible Web: Machine-in-the-loop, human agency and autonomy
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs
• Semantics and Knowledge: Data modeling to support human-machine intelligence, including LLMs agents, intelligent system behavior, explanations, and user-friendly interactions

Abstract

Robust and adaptive robotic peg-in-hole assembly under tight tolerances is critical to various industrial applications. However, it remains an open challenge due to perceptual and physical uncertainties from contact-rich interactions that easily exceed the allowed clearance. In this paper, we study how to leverage contact between the peg and its matching hole to eliminate uncertainties in the assembly process under unstructured settings. By examining the role of compliance under contact constraints, we present a manipulation system that plans collision-inclusive interactions for the peg to 1) iteratively identify its task environment to localize the target hole and 2) exploit environmental contact constraints to refine insertion motions into the target hole without relying on precise perception, enabling a robust solution to peg-in-hole assembly. By conceptualizing the above process as the composition of funneling in different state spaces, we present a formal approach to constructing manipulation funnels as an uncertainty-absorbing paradigm for peg-in-hole assembly. The proposed system effectively generalizes across diverse peg-in-hole scenarios across varying scales, shapes, and materials in a learning-free manner. Extensive experiments on a NIST Assembly Task Board (ATB) and additional challenging scenarios validate its robustness in real-world applications.

Problem

• Robust peg-in-hole assembly under tight tolerances
• Eliminate uncertainties via contact-rich manipulation
• Generalize across diverse scales and shapes

Innovation

• Compliant manipulation under contact constraints
• Collision-inclusive iterative hole localization
• Learning-free generalization across diverse scenarios