Moving Sequence Generation Based on Hungarian Method for Pick-and-Place Process

This paper presents a method for generating optimal moving sequences in pick-and-place robotic processes using the Hungarian method, formulated as an assignment problem to minimize total travel cost in automated assembly tasks. This early conference paper established the core algorithmic contribution that was later extended to the full journal publication on PnP process sequencing for 3D rasterized structures (Automation in Construction, 2017).

Problem setting

This paper presents a method for generating optimal moving sequences in pick-and-place robotic processes using the Hungarian method, formulated as an assignment problem to minimize total travel cost in automated assembly tasks.

In the broader publication record, this work appears in CAD'15, 47–52. The visual notes below pair the paper’s original figures with a concise reading of the method, experimental setup, and reported results.

Method and visual evidence

The method combines domain-specific measurements with an algorithmic representation that exposes the relevant structure, then refines it into a reconstruction, correspondence, segmentation, measurement, or decision result.

The extracted figures below show the main pipeline and representative experimental evidence.

Method overview. This image is extracted from an embedded PDF image object on page 1, then recomposed for web display.

Representation and setup. This image is extracted from an embedded PDF image object on page 3, then recomposed for web display.

Experimental evidence. This image is extracted from an embedded PDF image object on page 5, then recomposed for web display.

Result comparison. This image is extracted from an embedded PDF image object on page 5, then recomposed for web display.

Additional visual result. This image is extracted from an embedded PDF image object on page 6, then recomposed for web display.

Results and impact

The evaluation reported in CAD'15, 47–52 uses the extracted figures above to show the method’s measurement, reconstruction, segmentation, matching, or diagnostic behavior on representative experiments. These visuals are paired with the paper’s quantitative or qualitative analysis to make the workflow easier to inspect from the homepage.

Source handling

I extracted 13 candidate image objects from paper.pdf and generated the compressed WebP figures used on this page.