Modular Kinematic Reduction of Closed-Chain Mechanisms Using Path Assembly and Defect Homotopy

2026-09-10

AI Summary

本文提出了一种路径组装闭合微分映射框架，用于解决闭链机制中的非线性闭合约束问题，并通过缺陷同伦方法恢复一致的被动坐标。

Abstract

Closed kinematic chains complicate modular modeling by coupling active and passive coordinates through nonlinear closure constraints. This paper presents a Path-Assembled Closure Differential Mapping (PACDM) framework for modular closure resolution and kinematic reduction. Each closure element compares two ordered transformation paths with common endpoints, with their mismatch expressed through the logarithm on SE(3) and the corresponding Jacobian assembled from local transformation derivatives. Multi-path modules are constructed from a minimal set of pairwise closure elements, while rank-revealing analysis selects locally independent scalar constraints. A defect homotopy recovers closure-consistent passive coordinates from approximate estimates along a feasible and regular continuation path. At regular configurations, implicit differentiation yields the local active-to-passive differential mapping, which is subsequently used in a predictor-corrector continuation procedure for prescribed motion. The framework is evaluated on a seven-degree-of-freedom heavy-duty manipulator containing two-path and three-path closed-chain modules. Comparison with Simscape Multibody yields trajectory root-mean-square errors below 8.5 x 10^-10 rad, while predictor-corrector continuation is approximately 45.8 times faster than applying defect homotopy at every trajectory sample.

Problem

• Closed-Chain Mechanisms
• Kinematic Reduction
• Nonlinear Closure Constraints

Innovation

• Path-Assembled Closure Differential Mapping (PACDM)
• defect homotopy
• closed-chain mechanisms