Registration strategy of point clouds based on region-specific projections and virtual structures for robot-based inspection systems

Bauer, Philipp; Heckler, Lars; Worack, Mario; Magaña, Alejandro; Reinhart, Gunther

doi:10.1016/j.measurement.2021.109963

Cited by 9 publications

(2 citation statements)

References 37 publications

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“…However, we consider the steps proposed within this subsection more traceable, modular, and extendable to consider further constraints, multisensor systems, or even transferable to similar problems. For example, a variation of the algorithm could be applied to maximize or guarantee the registration space between two different viewpoints, which represents a fundamental challenge within many vision applications [62].…”

Section: Discussionmentioning

confidence: 99%

Viewpoint Generation Using Feature-Based Constrained Spaces for Robot Vision Systems

et al. 2023

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The efficient computation of viewpoints while considering various system and process constraints is a common challenge that any robot vision system is confronted with when trying to execute a vision task. Although fundamental research has provided solid and sound solutions for tackling this problem, a holistic framework that poses its formal description, considers the heterogeneity of robot vision systems, and offers an integrated solution remains unaddressed. Hence, this publication outlines the generation of viewpoints as a geometrical problem and introduces a generalized theoretical framework based on Feature-Based Constrained Spaces (C-spaces) as the backbone for solving it. A C-space can be understood as the topological space that a viewpoint constraint spans, where the sensor can be positioned for acquiring a feature while fulfilling the constraint. The present study demonstrates that many viewpoint constraints can be efficiently formulated as C-spaces, providing geometric, deterministic, and closed solutions. The introduced C-spaces are characterized based on generic domain and viewpoint constraints models to ease the transferability of the present framework to different applications and robot vision systems. The effectiveness and efficiency of the concepts introduced are verified on a simulation-based scenario and validated on a real robot vision system comprising two different sensors.

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Section: Discussionmentioning

confidence: 99%

Viewpoint Generation Using Feature-Based Constrained Spaces for Robot Vision Systems

et al. 2023

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“…However, in the context of applications demanding multiple viewpoints, we observed that the potential of

remains to be further exploited for considering further constraints. On the one hand, based on our ongoing research and preliminary results, we still see the potential for explicitly characterizing registration constraints for maximizing and ensuring the overlapping area between adjacent measurements [ 46 ]. On the other hand, we can also imagine that

s could be used for considering further robot constraints such as sensor lighting parameters, robot collisions, cycle times, and energy-efficiency constraints.…”

Section: Discussionmentioning

confidence: 99%

Viewpoint Planning for Range Sensors Using Feature Cluster Constrained Spaces for Robot Vision Systems

Magaña,

Vlaeyen,

Haitjema

et al. 2023

Sensors

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The efficient computation of viewpoints for solving vision tasks comprising multi-features (regions of interest) represents a common challenge that any robot vision system (RVS) using range sensors faces. The characterization of valid and robust viewpoints is even more complex within real applications that require the consideration of various system constraints and model uncertainties. Hence, to address some of the challenges, our previous work outlined the computation of valid viewpoints as a geometrical problem and proposed feature-based constrained spaces (C-spaces) to tackle this problem efficiently for acquiring one feature. The present paper extends the concept of C-spaces to consider multi-feature problems using feature cluster constrained spaces (GC-spaces). A GC-space represents a closed-form, geometrical solution that provides an infinite set of valid viewpoints for acquiring a cluster of features satisfying diverse viewpoint constraints. Furthermore, the current study outlines a generic viewpoint planning strategy based on GC-spaces for solving vision tasks comprising multi-feature scenarios effectively and efficiently. The applicability of the proposed framework is validated on two different industrial vision systems used for dimensional metrology tasks.

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Research on robot regrinding trajectory planning and surface characteristics of damaged blades

Zhipeng,

Zhiqiang,

Yuchao

et al. 2023

Int J Adv Manuf Technol

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Registration strategy of point clouds based on region-specific projections and virtual structures for robot-based inspection systems

Cited by 9 publications

References 37 publications

Viewpoint Generation Using Feature-Based Constrained Spaces for Robot Vision Systems

Viewpoint Generation Using Feature-Based Constrained Spaces for Robot Vision Systems

Viewpoint Planning for Range Sensors Using Feature Cluster Constrained Spaces for Robot Vision Systems

Research on robot regrinding trajectory planning and surface characteristics of damaged blades

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