IEEE Transactions on Automation Science and Engineering

Aims & Scope

The IEEE Transactions on Automation Science and Engineering (T-ASE) publishes fundamental papers on Automation, emphasizing scientific results that advance efficiency, quality, productivity, and reliability.

T-ASE encourages interdisciplinary approaches from computer science, control systems, electrical engineering, mathematics, mechanical engineering, operations research, and other fields.

T-ASE welcomes results relevant to industries such as agriculture, biotechnology, healthcare, home automation, maintenance, manufacturing, pharmaceuticals, retail, security, service, supply chains, and transportation.

T-ASE addresses a research community willing to integrate knowledge across disciplines and industries.

For this purpose, each paper includes a Note to Practitioners that summarizes how its results can be applied or how they might be extended to apply in practice.

View Aims & Scope

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Metrics & Ranking

Impact Factor

Year	Value
2025	6.4

Journal Rank

Year	Value
2024	1562

Journal Citation Indicator

Year	Value
2024	6835

SJR (SCImago Journal Rank)

Year	Value
2024	1.918

Quartile

Year	Value
2024	Q1

h-index

Year	Value
2024	122

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Abstracting & Indexing

Journal is indexed in leading academic databases, ensuring global visibility and accessibility of our peer-reviewed research.

• Scopus
• Google Scholar
• Web of Science

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Subjects & Keywords

Journal’s research areas, covering key disciplines and specialized sub-topics in Engineering, designed to support cutting-edge academic discovery.

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Most Cited Articles

The Most Cited Articles section features the journal's most impactful research, based on citation counts. These articles have been referenced frequently by other researchers, indicating their significant contribution to their respective fields.

• Carbon Footprint and the Management of Supply Chains: Insights From Simple Models

  Citation: 989

  Authors: Saif, Yanzhi, Mark

• A Survey of Research on Cloud Robotics and Automation

  Citation: 651

  Authors: Ben, Sachin, Pieter, Ken

• Modeling and Control of Piezo-Actuated Nanopositioning Stages: A Survey

  Citation: 544

  Authors: Guo-Ying, Li-Min, Chun-Yi, Han, Sergej

• Neural RRT*: Learning-Based Optimal Path Planning

  Citation: 413

  Authors: Jiankun, Wenzheng, Chenming, Chaoqun, Max Q.-H.

• Bouc–Wen Modeling and Inverse Multiplicative Structure to Compensate Hysteresis Nonlinearity in Piezoelectric Actuators

  Citation: 401

  Authors: Micky

• Automated Crack Detection on Concrete Bridges

  Citation: 386

  Authors: Prateek, Kristin J., Nenad, Basily B., Hung M., Ronny Salim, Hooman

• Semidefinite Programming Approaches for Sensor Network Localization With Noisy Distance Measurements

  Citation: 354

  Authors: P., T.-C., K.-C., Y., T.-C.

• Theory and Experiment on Formation-Containment Control of Multiple Multirotor Unmanned Aerial Vehicle Systems

  Citation: 342

  Authors: Xiwang, Yongzhao, Yan, Zhang, Yisheng

• Safety in human-robot collaborative manufacturing environments: Metrics and control

  Citation: 336

  Authors: Andrea Maria, Nicola Maria, Paolo, Hao, Bjorn

• Analysis and Observations From the First Amazon Picking Challenge

  Citation: 312

  Authors: Nikolaus, Kostas E., Dmitry, Oliver, Albert, Kris, Kei, Alberto, Joseph M., Peter R.

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