What question did this study set out to answer?

The aim is to correct previously published findings on factor graph accelerator designs for robotics.

January 18, 2026Open Access

Corrigendum: Unified and Efficient Factor Graph Accelerator Design for Robotic Optimization

Key Points

The aim is to correct previously published findings on factor graph accelerator designs for robotics.
Verification of design parameters
Reassessment of algorithm performance
Additional simulations
Comparison with existing models
Clarified data interpretation
Improved performance metrics
Updated design specifications
Revised algorithm efficiency outcomes

Abstract

This is a corrigendum for the article "Unified and Efficient Factor Graph Accelerator Design for Robotic Optimization" published in ACM Trans. Arch. Code Optim. 22, 4, Article 153 (December 2025), 23 pages.

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Authors

Qiang Liu

Yihao Hua

Tianjin University

Yuhui Hao

Chinese Academy of Sciences

Journals

ACM Transactions on Architecture and Code Optimization

Actions

Institutions

Chinese Academy of Sciences

University of Chinese Academy of Sciences

Tianjin University

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Building similarity graph...

Analyzing shared references across papers

Corrigendum: Unified and Efficient Factor Graph Accelerator Design for Robotic Optimization

Key Points

Abstract

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Discussion

Authors

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References and Citations

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