Constraint Manifold Exploration for Efficient Continuous Coverage Estimation

Fuente: arXiv
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Main Authors: Wilbrandt, Robert, Dillmann, Rüdiger
Format: Preprint
Published: 2026
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author Wilbrandt, Robert
Dillmann, Rüdiger
author_facet Wilbrandt, Robert
Dillmann, Rüdiger
contents Many automated manufacturing processes rely on industrial robot arms to move process-specific tools along workpiece surfaces. In applications like grinding, sanding, spray painting, or inspection, they need to cover a workpiece fully while keeping their tools perpendicular to its surface. While there are approaches to generate trajectories for these applications, there are no sufficient methods for analyzing the feasibility of full surface coverage. This work proposes a sampling-based approach for continuous coverage estimation that explores reachable surface regions in the configuration space. We define an extended ambient configuration space that allows for the representation of tool position and orientation constraints. A continuation-based approach is used to explore it using two different sampling strategies. A thorough evaluation across different kinematics and environments analyzes their runtime and efficiency. This validates our ability to accurately and efficiently calculate surface coverage for complex surfaces in complicated environments.
format Preprint
id arxiv_https___arxiv_org_abs_2602_06749
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Constraint Manifold Exploration for Efficient Continuous Coverage Estimation
Wilbrandt, Robert
Dillmann, Rüdiger
Robotics
Many automated manufacturing processes rely on industrial robot arms to move process-specific tools along workpiece surfaces. In applications like grinding, sanding, spray painting, or inspection, they need to cover a workpiece fully while keeping their tools perpendicular to its surface. While there are approaches to generate trajectories for these applications, there are no sufficient methods for analyzing the feasibility of full surface coverage. This work proposes a sampling-based approach for continuous coverage estimation that explores reachable surface regions in the configuration space. We define an extended ambient configuration space that allows for the representation of tool position and orientation constraints. A continuation-based approach is used to explore it using two different sampling strategies. A thorough evaluation across different kinematics and environments analyzes their runtime and efficiency. This validates our ability to accurately and efficiently calculate surface coverage for complex surfaces in complicated environments.
title Constraint Manifold Exploration for Efficient Continuous Coverage Estimation
topic Robotics
url https://arxiv.org/abs/2602.06749