One Problem, One Solution: Unifying Robot Design and Cell Layout Optimization

The task-specific optimization of robotic systems has since the inception of the field been divided into the optimization of the robot and the optimization of the layout of its workstations. In this letter, we argue that these two problems are interdependent and should be treated as such. To this end, we present a unified problem formulation that enables for the simultaneous optimization of both the robot kinematics and the workstation layout. We demonstrate the effectiveness of our approach by jointly optimizing a robotic milling system. To compare our approach to the state of the art, we optimize the robot’s kinematics and layout separately. The results show that our approach outperforms the state of the art and that simultaneous optimization leads to up to eight times better solutions.

Authors

Institutions

Publication Details

Published
2024-10-14
DOI
https://doi.org/10.1109/iros58592.2024.10801417
Citations
5
Primary Topic
Advanced Manufacturing and Logistics Optimization
Type
article
Field-Weighted Citation Impact
1.74

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

One Problem, One Solution: Unifying Robot Design and Cell Layout Optimization

Alexander Puchta, Jürgen Fleischer, Jan Baumgärtner
5 citations
Advanced Manufacturing and Logistics Optimization
1.74
article

One Problem, One Solution: Unifying Robot Design and Cell Layout Optimization

Alexander Puchta, Jürgen Fleischer, Jan Baumgärtner
article en
5 citations

Abstract

The task-specific optimization of robotic systems has since the inception of the field been divided into the optimization of the robot and the optimization of the layout of its workstations. In this letter, we argue that these two problems are interdependent and should be treated as such. To this end, we present a unified problem formulation that enables for the simultaneous optimization of both the robot kinematics and the workstation layout. We demonstrate the effectiveness of our approach by jointly optimizing a robotic milling system. To compare our approach to the state of the art, we optimize the robot’s kinematics and layout separately. The results show that our approach outperforms the state of the art and that simultaneous optimization leads to up to eight times better solutions.

Karlsruhe Institute of Technology (DE)
Deutsche Forschungsgemeinschaft
Openalex Percentile: Top 13%
Advanced Manufacturing and Logistics Optimization
1.74
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.