Hongmin Wu

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Hongmin Wu (16)
Yisheng Guan (7)
Xuefeng Zhou (6)
Juan Carlos Rojas (5)
Zhihao Xu (5)
Shuangda Duan (4)
Wu Yan (3)
Hongbin Lin (2)
Shuai Li (2)
Shuangqi Luo (2)
Zhaoyang Liao (2)
Chen Xu (1)
Hong Zhang (1)
Huajian Deng (1)
Jiancong Huang (1)
Longxin Chen (1)
Songbin Zhou (1)
Taobo Cheng (1)
Xiaoxiao Li (1)
Yisen Liu (1)

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Journal of Intelligent and Robotic Systems (2)
Neurocomputing (2)
Computers and Electronics in Agriculture (1)
Procedia Computer Science (1)
Robotics and Computer-Integrated Manufacturing (1)

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2017 IEEE-RAS 17th International Conference on Humanoid Robotics (Humanoids) (2)
2018 IEEE International Conference on Robotics and Biomimetics (ROBIO) (2)
2016 IEEE International Conference on Robotics and Biomimetics (ROBIO) (1)
2018 27th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN) (1)
Intelligent Robotics and Applications (1)
Intelligent Robotics and Applications (1)
Intelligent Robotics and Applications (1)

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IEEE Press (6)
Elsevier Science Publishers B. V. (4)
Springer-Verlag (3)
Kluwer Academic Publishers (2)
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research-article
Uncertainty-aware error modeling and hierarchical redundancy optimization for robotic surface machining
- Zhao-Yang Liao
  Institute of Intelligent Manufacturing, Guangdong Academy of Sciences, Guangdong Key Laboratory of Modern Control Technology, Guangzhou, 510070, China
  ,
- Qing-Hui Wang
  The School of Mechanical and Automotive Engineering, South China University of Technology, Guangzhou, 510641, China
  ,
- Zhi-Hao Xu
  Institute of Intelligent Manufacturing, Guangdong Academy of Sciences, Guangdong Key Laboratory of Modern Control Technology, Guangzhou, 510070, China
  ,
- Hong-Min Wu
  Institute of Intelligent Manufacturing, Guangdong Academy of Sciences, Guangdong Key Laboratory of Modern Control Technology, Guangzhou, 510070, China
  ,
- Bing Li
  The School of Mechanical Engineering and Automation, Harbin Institute of Technology, Shenzhen, 518055, China
  ,
- Xue-Feng Zhou
  Institute of Intelligent Manufacturing, Guangdong Academy of Sciences, Guangdong Key Laboratory of Modern Control Technology, Guangzhou, 510070, China
Robotics and Computer-Integrated Manufacturing, Volume 87, Issue C•Jun 2024 • https://doi.org/10.1016/j.rcim.2023.102713
Abstract
Industrial robots are commonly utilized in in-situ machining, but their inherent limitations in stiffness and positioning accuracy can pose challenges in achieving precise freeform surface milling. Previous research primarily focused on robot ...
Highlights

Proposing a novel method for evaluating surface profile errors in robotic milling that addresses robot error uncertainties. It combines geometric error prediction models (kinematic and stiffness-based) with Gaussian process regression to ...
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research-article
Learning Stable Nonlinear Dynamics and Interactive Force-Aware Variable Impedance Control for Robotic Contact Tasks
- Hongmin Wu
  Institute of Intelligent Manufacturing, Guangdong Academy of Sciences, Guangdong Key Laboratory of Modern Control Technology, Guangzhou, China
  Pazhou Lab, Guangzhou, China
  ,
- Xueqian Zhai
  Institute of Intelligent Manufacturing, Guangdong Academy of Sciences, Guangdong Key Laboratory of Modern Control Technology, Guangzhou, China
  Wuyi University, Jiangmen, China
  ,
- Xinyu Wu
  Shenzhen Institute of Advanced TechnologyChinese Academy of Sciences, Shenzhen, China
  ,
- Shichao Gu
  Institute of Intelligent Manufacturing, Guangdong Academy of Sciences, Guangdong Key Laboratory of Modern Control Technology, Guangzhou, China
  ,
- Zhaoyang Liao
  Institute of Intelligent Manufacturing, Guangdong Academy of Sciences, Guangdong Key Laboratory of Modern Control Technology, Guangzhou, China
  ,
- Zhihao Xu
  Institute of Intelligent Manufacturing, Guangdong Academy of Sciences, Guangdong Key Laboratory of Modern Control Technology, Guangzhou, China
  ,
- Jia Pan
  The University of Hong Kong, Hong Kong, China
  ,
- Xuefeng Zhou
  Institute of Intelligent Manufacturing, Guangdong Academy of Sciences, Guangdong Key Laboratory of Modern Control Technology, Guangzhou, China
  Pazhou Lab, Guangzhou, China
Procedia Computer Science, Volume 226, Issue C•2023, pp 127-133 • https://doi.org/10.1016/j.procs.2023.10.646
Abstract
This paper presents a novel approach for efficient robot programming in tasks such as polishing and grinding, which addresses the challenges of stability and adaptability in robot motion and control. The approach involves learning movement skills ...
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Positioning Error Modelling and Compensation Method for Robot Machining Based on RVM
- Jinzhu Wu
  https://ror.org/059djzq42Wuyi University, Jiangmen, China
  https://ror.org/01g9hkj35Institute of Intelligent Manufacturing, Guangdong Academy of Sciences, Guangdong Key Laboratory of Modern Control Technology, 510070, Guangzhou, China
  ,
- Zhaoyang Liao
  https://ror.org/01g9hkj35Institute of Intelligent Manufacturing, Guangdong Academy of Sciences, Guangdong Key Laboratory of Modern Control Technology, 510070, Guangzhou, China
  ,
- Hongmin Wu
  https://ror.org/01g9hkj35Institute of Intelligent Manufacturing, Guangdong Academy of Sciences, Guangdong Key Laboratory of Modern Control Technology, 510070, Guangzhou, China
  ,
- Li Jiang
  https://ror.org/059djzq42Wuyi University, Jiangmen, China
  ,
- Kezheng Sun
  https://ror.org/01g9hkj35Institute of Intelligent Manufacturing, Guangdong Academy of Sciences, Guangdong Key Laboratory of Modern Control Technology, 510070, Guangzhou, China
Intelligent Robotics and Applications•July 2023, pp 383-394• https://doi.org/10.1007/978-981-99-6480-2_32
Abstract
The low absolute positioning accuracy of industrial robots leads to low machining accuracy, seriously hindering the development and application of robots in the field of high-precision machining. To solve this problem, this article proposes a ...
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Joint optimization of autoencoder and Self-Supervised Classifier: Anomaly detection of strawberries using hyperspectral imaging
- Yisen Liu
  Institute of Intelligent Manufacturing, Guangdong Academy of Sciences, Building 13, Xianliezhong Road No. 100, Yuexiu District, Guangzhou 510070, Guangdong, China
  ,
- Songbin Zhou
  Institute of Intelligent Manufacturing, Guangdong Academy of Sciences, Building 13, Xianliezhong Road No. 100, Yuexiu District, Guangzhou 510070, Guangdong, China
  ,
- Hongmin Wu
  Institute of Intelligent Manufacturing, Guangdong Academy of Sciences, Building 13, Xianliezhong Road No. 100, Yuexiu District, Guangzhou 510070, Guangdong, China
  ,
- Wei Han
  Institute of Intelligent Manufacturing, Guangdong Academy of Sciences, Building 13, Xianliezhong Road No. 100, Yuexiu District, Guangzhou 510070, Guangdong, China
  ,
- Chang Li
  Institute of Intelligent Manufacturing, Guangdong Academy of Sciences, Building 13, Xianliezhong Road No. 100, Yuexiu District, Guangzhou 510070, Guangdong, China
  ,
- Hong Chen
  Institute of Intelligent Manufacturing, Guangdong Academy of Sciences, Building 13, Xianliezhong Road No. 100, Yuexiu District, Guangzhou 510070, Guangdong, China
Computers and Electronics in Agriculture, Volume 198, Issue C•Jul 2022 • https://doi.org/10.1016/j.compag.2022.107007
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Detecting strawberry anomalies using hyperspectral imaging.
Constructing models by joint optimization of autoencoder and self-supervised learning.
Simulating spectra with various objects to build effective self-supervised ...
Abstract
Developing unsupervised anomaly detection methods for hyperspectral data is of great importance for its applications in quality and safety control. As a frequently-used anomaly detection method, the autoencoder might suffer from the ...
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research-article
Dynamic neural networks based adaptive optimal impedance control for redundant manipulators under physical constraints
- Zhihao Xu
  Institute of Intelligent Manufacturing, Guangdong Academy of Sciences, Guangdong Key Laboratory of Modern Control Technology, Guangzhou, China
  Pazhou Lab, Guangzhou, China
  ,
- Xiaoxiao Li
  Institute of Intelligent Manufacturing, Guangdong Academy of Sciences, Guangdong Key Laboratory of Modern Control Technology, Guangzhou, China
  ,
- Shuai Li
  School of Engineering, Swansea University, Swansea, United Kingdom
  ,
- Hongmin Wu
  Institute of Intelligent Manufacturing, Guangdong Academy of Sciences, Guangdong Key Laboratory of Modern Control Technology, Guangzhou, China
  Pazhou Lab, Guangzhou, China
  ,
- Xuefeng Zhou
  Institute of Intelligent Manufacturing, Guangdong Academy of Sciences, Guangdong Key Laboratory of Modern Control Technology, Guangzhou, China
Neurocomputing, Volume 471, Issue C•Jan 2022, pp 149-160 • https://doi.org/10.1016/j.neucom.2021.11.025
Abstract
This paper presents a dynamic neural network based adaptive impedance control method for redundant robots under multiple physical constraints. In order to provide optimal contact performance without an accurate environment model, an adaptive ...
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research-article
Multimodal Prediction-Based Robot Abnormal Movement Identification Under Variable Time-length Experiences
- Hongmin Wu
  Institute of Intelligent Manufacturing, Guangdong Academy of Sciences, and Guangdong Key Laboratory of Modern Control Technology, Guangzhou, China
  ,
- Wu Yan
  Institute of Intelligent Manufacturing, Guangdong Academy of Sciences, and Guangdong Key Laboratory of Modern Control Technology, Guangzhou, China
  ,
- Zhihao Xu
  Institute of Intelligent Manufacturing, Guangdong Academy of Sciences, and Guangdong Key Laboratory of Modern Control Technology, Guangzhou, China
  Foshan Tri-Co Intelligent Robot Technology Co., Ltd, Foshan, China
  ,
- Shuai Li
  School of Engineering, Swansea University, Swansea, United Kingdom
  ,
- Taobo Cheng
  Institute of Intelligent Manufacturing, Guangdong Academy of Sciences, and Guangdong Key Laboratory of Modern Control Technology, Guangzhou, China
  ,
- Xuefeng Zhou
  Institute of Intelligent Manufacturing, Guangdong Academy of Sciences, and Guangdong Key Laboratory of Modern Control Technology, Guangzhou, China
Journal of Intelligent and Robotic Systems, Volume 104, Issue 1•Jan 2022 • https://doi.org/10.1007/s10846-021-01496-x
Abstract
Robots will eventually make part of our daily lives, helping us at home, taking care of the elderly, and collaborating at work. In such Human-Robot Collaboration (HRC) scenarios, achieving abnormal movement identification can effectively deal with ...
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Learning robot anomaly recovery skills from multiple time-driven demonstrations
- Hongmin Wu
  Institute of Intelligent Manufacturing, Guangdong Academy of Sciences, Guangdong Key Laboratory of Modern Control Technology, China
  Pazhou Lab, Guangzhou 510330, China
  ,
- Wu Yan
  Institute of Intelligent Manufacturing, Guangdong Academy of Sciences, Guangdong Key Laboratory of Modern Control Technology, China
  ,
- Zhihao Xu
  Institute of Intelligent Manufacturing, Guangdong Academy of Sciences, Guangdong Key Laboratory of Modern Control Technology, China
  Pazhou Lab, Guangzhou 510330, China
  ,
- Shuai Li
  School of Engineering, Swansea University, Swansea, United Kingdom
  ,
- Xuefeng Zhou
  Institute of Intelligent Manufacturing, Guangdong Academy of Sciences, Guangdong Key Laboratory of Modern Control Technology, China
Neurocomputing, Volume 464, Issue C•Nov 2021, pp 522-532 • https://doi.org/10.1016/j.neucom.2021.08.036
Abstract
Robots are prone to making anomalies when performing manipulation tasks in unstructured environments, it is often desirable to rapidly adapt the robotic behavior to avoid environmental changes by learning from experts’ demonstrations. We propose ...
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Real Time Volume Measurement of Logistics Cartons Through 3D Point Cloud Segmentation
- Wu Yan
  Guangdong Key Laboratory of Modern Control Technology, Institute of Intelligent Manufacturing, Guangdong Academy of Sciences, Guangzhou, China
  ,
- Chen Xu
  Guangdong Key Laboratory of Modern Control Technology, Institute of Intelligent Manufacturing, Guangdong Academy of Sciences, Guangzhou, China
  ,
- Hongmin Wu
  Guangdong Key Laboratory of Modern Control Technology, Institute of Intelligent Manufacturing, Guangdong Academy of Sciences, Guangzhou, China
  ,
- Shuai Li
  School of Engineering, Swansea University, Swansea, UK
  Foshan Tri-Co Intelligent Robot Technology Co., Ltd., Foshan, China
  ,
- Xuefeng Zhou
  Guangdong Key Laboratory of Modern Control Technology, Institute of Intelligent Manufacturing, Guangdong Academy of Sciences, Guangzhou, China
Intelligent Robotics and Applications•October 2021, pp 324-335• https://doi.org/10.1007/978-3-030-89134-3_30
Abstract
Vision-based measurement has been studied extensively in recent decades for its potential applications in robotics. However, there still remain challenges when we aim at a fast and robust detecting system even in the presence of damaged cartons. ...
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Endowing Robots with Longer-term Autonomy by Recovering from External Disturbances in Manipulation Through Grounded Anomaly Classification and Recovery Policies
- Shuangqi Luo
  University of Maryland, College Park, MD, USA
  ,
- Hongmin Wu
  Guangdong Institute of Intelligent Manufacturing, Guangzhou, People’s Republic of China
  ,
- Shuangda Duan
  University of Waterloo (Foshan) Innovation Center, Foshan, People’s Republic of China
  ,
- Yijiong Lin
  University of Bristol, Bristol, UK
  ,
- Juan Rojas
  School of Mechanical and Automation Engineering, Chinese University of Hong Kong, Hong Kong, People’s Republic of China
Journal of Intelligent and Robotic Systems, Volume 101, Issue 3•Mar 2021 • https://doi.org/10.1007/s10846-021-01312-6
Abstract
Robots are poised to interact with humans in unstructured environments. Despite increasingly robust control algorithms, failure modes arise whenever the underlying dynamics are poorly modeled, especially in unstructured environments. We contribute ...
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Variational Augmented the Heuristic Funnel-Transitions Model for Dexterous Robot Manipulation
- Jiancong Huang
  BIRL, Guangdong University of Technology, Guangzhou, Guangdong, People’s Republic of China
  IIM, Guangdong Academy of Sciences, Guangzhou, Guangdong, People’s Republic of China
  ,
- Yijiong Lin
  BIRL, Guangdong University of Technology, Guangzhou, Guangdong, People’s Republic of China
  ,
- Hongmin Wu
  IIM, Guangdong Academy of Sciences, Guangzhou, Guangdong, People’s Republic of China
  ,
- Yisheng Guan
  BIRL, Guangdong University of Technology, Guangzhou, Guangdong, People’s Republic of China
Intelligent Robotics and Applications•November 2020, pp 149-160• https://doi.org/10.1007/978-3-030-66645-3_13
Abstract
Learning from demonstrations is a heuristic technique that can only obtain the intentional dynamics of robot manipulation, which may fail to the task with unexpected anomalies. In this paper, we present a method for enhancing the diversity of ...
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Multimodal Sparse Representation for Anomaly Classification in A Robot Introspection System
- Hongmin Wu
  Biomimetic and Intelligent Robotics Lab (BIRL), Guangdong University of Technology, Guangzhou, 510006, China
  ,
- Dong Liu
  Biomimetic and Intelligent Robotics Lab (BIRL), Guangdong University of Technology, Guangzhou, 510006, China
  ,
- Shuangda Duan
  Biomimetic and Intelligent Robotics Lab (BIRL), Guangdong University of Technology, Guangzhou, 510006, China
  ,
- Yisheng Guan
  Biomimetic and Intelligent Robotics Lab (BIRL), Guangdong University of Technology, Guangzhou, 510006, China
  ,
- Juan Rojas
  Biomimetic and Intelligent Robotics Lab (BIRL), Guangdong University of Technology, Guangzhou, 510006, China
2018 IEEE International Conference on Robotics and Biomimetics (ROBIO)•December 2018, pp 1594-1600• https://doi.org/10.1109/ROBIO.2018.8665206
Robot introspection is expected to greatly aid longer-term autonomy of autonomous systems. By equipping robots with skills that allow them to assess the quality of their sensory data, robots can detect and classify anomalies and recover from them. However,...
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Integration of Visual Information and Robot Offline Programming System for Improving Automatic Deburring Process
- Zengliang Lai
  Biomimetic and Intelligent Robotics Lab (BIRL), Guangdong University of Technology, Guangzhou, 510006, China
  ,
- Rentao Xiong
  Biomimetic and Intelligent Robotics Lab (BIRL), Guangdong University of Technology, Guangzhou, 510006, China
  ,
- Hongmin Wu
  Biomimetic and Intelligent Robotics Lab (BIRL), Guangdong University of Technology, Guangzhou, 510006, China
  ,
- Yisheng Guan
  Biomimetic and Intelligent Robotics Lab (BIRL), Guangdong University of Technology, Guangzhou, 510006, China
2018 IEEE International Conference on Robotics and Biomimetics (ROBIO)•December 2018, pp 1132-1137• https://doi.org/10.1109/ROBIO.2018.8665148
The automatic deburring process of casting parts has been commonly investigated by industrial robot manipulators in recent decade. Majority of solutions are dependent on human teaching or robot Off-Line Programming system (OLP), which assume that ...
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Recovering from External Disturbances in Online Manipulation through State-Dependent Revertive Recovery Policies
- Hongmin Wu
  School of Electromechanical Engineering in Guangdong University of Technology in Guangzhou, China
  ,
- Shuangqi Luo
  School of Electromechanical Engineering in Guangdong University of Technology in Guangzhou, China
  ,
- Hongbin Lin
  School of Electromechanical Engineering in Guangdong University of Technology in Guangzhou, China
  ,
- Shuangda Duan
  School of Electromechanical Engineering in Guangdong University of Technology in Guangzhou, China
  ,
- Yisheng Guan
  School of Electromechanical Engineering in Guangdong University of Technology in Guangzhou, China
  ,
- Juan Rojas
  School of Electromechanical Engineering in Guangdong University of Technology in Guangzhou, China
2018 27th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN)•August 2018, pp 166-173• https://doi.org/10.1109/ROMAN.2018.8525771
Robots are increasingly entering uncertain and unstructured environments. Within these, robots are bound to face unexpected external disturbances like accidental human or tool collisions. Robots must develop the capacity to respond to unexpected events. ...
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Robot introspection with Bayesian nonparametric vector autoregressive hidden Markov models
2017 IEEE-RAS 17th International Conference on Humanoid Robotics (Humanoids)•November 2017, pp 882-888• https://doi.org/10.1109/HUMANOIDS.2017.8246976
Robot introspection, as opposed to anomaly detection typical in process monitoring, helps a robot understand what it is doing at all times. A robot should be able to identify its actions not only when failure or novelty occurs, but also as it executes any ...
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Learning human-robot collaboration insights through the integration of muscle activity in interaction motion models
- Longxin Chen
  School of Electromechanical Engineering in Guangdong University of Technology in Guangzhou, China
  ,
- Hongmin Wu
  School of Electromechanical Engineering in Guangdong University of Technology in Guangzhou, China
  ,
- Shuangda Duan
  School of Electromechanical Engineering in Guangdong University of Technology in Guangzhou, China
  ,
- Yisheng Guan
  School of Electromechanical Engineering in Guangdong University of Technology in Guangzhou, China
  ,
- Juan Rojas
  School of Electromechanical Engineering in Guangdong University of Technology in Guangzhou, China
2017 IEEE-RAS 17th International Conference on Humanoid Robotics (Humanoids)•November 2017, pp 491-496• https://doi.org/10.1109/HUMANOIDS.2017.8246917
Recent progress in human-robot collaboration (HRC) makes fast and fluid interactions possible. Methods like Interaction Probabilistic Movement Primitives (ProMPs) model human motion trajectories through motion capture systems. However, such presentation ...
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Sequence-modification based collision-free motion planning of multiple robots workcell
- Hongmin Wu
  School of Mechanical and Electrical Engineering, Guangdong University of Technology, Guangzhou, China, 510006
  ,
- Huajian Deng
  School of Mechanical and Electrical Engineering, Guangdong University of Technology, Guangzhou, China, 510006
  ,
- Longxin Chen
  School of Mechanical and Electrical Engineering, Guangdong University of Technology, Guangzhou, China, 510006
  ,
- Yisheng Guan
  School of Mechanical and Electrical Engineering, Guangdong University of Technology, Guangzhou, China, 510006
  ,
- Hong Zhang
  School of Mechanical and Electrical Engineering, Guangdong University of Technology, Guangzhou, China, 510006
2016 IEEE International Conference on Robotics and Biomimetics (ROBIO)•December 2016, pp 1135-1140• https://doi.org/10.1109/ROBIO.2016.7866478
This work is inspired by the problem of planning multiple robots in a shared workspace. The goal is to find out a sequence order for coordinating the paths of robots so as to avoid collisions among them and deadlocks, that is, situations where each robot ...
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How ACM Author-Izer Works

Authors may post ACM Author-Izer links in their own bibliographies maintained on their website and their own institution’s repository. The links take visitors to your page directly to the definitive version of individual articles inside the ACM Digital Library to download these articles for free.

The Service can be applied to all the articles you have ever published with ACM.

Depending on your previous activities within the ACM DL, you may need to take up to three steps to use ACM Author-Izer.

For authors who do not have a free ACM Web Account:

Go to the ACM DL http://dl.acm.org/ and click SIGN UP. Once your account is established, proceed to next step.

For authors who have an ACM web account, but have not edited their ACM Author Profile page:

Sign in to your ACM web account and go to your Author Profile page. Click "Add personal information" and add photograph, homepage address, etc. Click ADD AUTHOR INFORMATION to submit change. Once you receive email notification that your changes were accepted, you may utilize ACM Author-izer.

For authors who have an account and have already edited their Profile Page:

Sign in to your ACM web account, go to your Author Profile page in the Digital Library, look for the ACM Author-izer link below each ACM published article, and begin the authorization process. If you have published many ACM articles, you may find a batch Authorization process useful. It is labeled: "Export as: ACM Author-Izer Service"

ACM Author-Izer also provides code snippets for authors to display download and citation statistics for each “authorized” article on their personal pages. Downloads from these pages are captured in official ACM statistics, improving the accuracy of usage and impact measurements. Consistently linking to the definitive version of ACM articles should reduce user confusion over article versioning.

Note: You still retain the right to post your author-prepared preprint versions on your home pages and in your institutional repositories with DOI pointers to the definitive version permanently maintained in the ACM Digital Library. But any download of your preprint versions will not be counted in ACM usage statistics. If you use these AUTHOR-IZER links instead, usage by visitors to your page will be recorded in the ACM Digital Library and displayed on your page.

FAQ

Q. What is ACM Author-Izer?
A. ACM Author-Izer is a unique, link-based, self-archiving service that enables ACM authors to generate and post links on either their home page or institutional repository for visitors to download the definitive version of their articles for free.
Q. What articles are eligible for ACM Author-Izer?
A. ACM Author-Izer can be applied to all the articles authors have ever published with ACM. It is also available to authors who will have articles published in ACM publications in the future.

Q. Are there any restrictions on authors to use this service?
A. No. An author does not need to subscribe to the ACM Digital Library nor even be a member of ACM.

Q. What are the requirements to use this service?
A. To access ACM Author-Izer, authors need to have a free ACM web account, must have an ACM Author Profile page in the Digital Library, and must take ownership of their Author Profile page.

Q. What is an ACM Author Profile Page?
A. The Author Profile Page initially collects all the professional information known about authors from the publications record as known by the ACM Digital Library. The Author Profile Page supplies a quick snapshot of an author's contribution to the field and some rudimentary measures of influence upon it. Over time, the contents of the Author Profile page may expand at the direction of the community. Please visit the ACM Author Profile documentation page for more background information on these pages.

Q. How do I find my Author Profile page and take ownership?
A. You will need to take the following steps:
- Create a free ACM Web Account
- Sign-In to the ACM Digital Library
- Find your Author Profile Page by searching the ACM Digital Library for your name
- Find the result you authored (where your author name is a clickable link)
- Click on your name to go to the Author Profile Page
- Click the "Add Personal Information" link on the Author Profile Page
- Wait for ACM review and approval; generally less than 24 hours

Q. Why does my photo not appear?
A. Make sure that the image you submit is in .jpg or .gif format and that the file name does not contain special characters

Q. What if I cannot find the Add Personal Information function on my author page?
A. The ACM account linked to your profile page is different than the one you are logged into. Please logout and login to the account associated with your Author Profile Page.

Q. What happens if an author changes the location of his bibliography or moves to a new institution?
A. Should authors change institutions or sites, they can utilize ACM Author-Izer to disable old links and re-authorize new links for free downloads from a new location.

Q. What happens if an author provides a URL that redirects to the author’s personal bibliography page?
A. The service will not provide a free download from the ACM Digital Library. Instead the person who uses that link will simply go to the Citation Page for that article in the ACM Digital Library where the article may be accessed under the usual subscription rules.

However, if the author provides the target page URL, any link that redirects to that target page will enable a free download from the Service.

Q. What happens if the author’s bibliography lives on a page with several aliases?
A. Only one alias will work, whichever one is registered as the page containing the author’s bibliography. ACM has no technical solution to this problem at this time.

Q. Why should authors use ACM Author-Izer?
A. ACM Author-Izer lets visitors to authors’ personal home pages download articles for no charge from the ACM Digital Library. It allows authors to dynamically display real-time download and citation statistics for each “authorized” article on their personal site.

Q. Does ACM Author-Izer provide benefits for authors?
A. Downloads of definitive articles via Author-Izer links on the authors’ personal web page are captured in official ACM statistics to more accurately reflect usage and impact measurements.

Authors who do not use ACM Author-Izer links will not have downloads from their local, personal bibliographies counted. They do, however, retain the existing right to post author-prepared preprint versions on their home pages or institutional repositories with DOI pointers to the definitive version permanently maintained in the ACM Digital Library.

Q. How does ACM Author-Izer benefit the computing community?
A. ACM Author-Izer expands the visibility and dissemination of the definitive version of ACM articles. It is based on ACM’s strong belief that the computing community should have the widest possible access to the definitive versions of scholarly literature. By linking authors’ personal bibliography with the ACM Digital Library, user confusion over article versioning should be reduced over time.

In making ACM Author-Izer a free service to both authors and visitors to their websites, ACM is emphasizing its continuing commitment to the interests of its authors and to the computing community in ways that are consistent with its existing subscription-based access model.

Q. How do authors access ACM Author-Izer?
A. See How to Use

Q. Why can’t I find my most recent publication in my ACM Author Profile Page?
A. There is a time delay between publication and the process which associates that publication with an Author Profile Page. Right now, that process usually takes 4-8 weeks.

Q. How does ACM Author-Izer expand ACM’s “Green Path” Access Policies?
A. ACM Author-Izer extends the rights and permissions that authors retain even after copyright transfer to ACM, which has been among the “greenest” publishers. ACM enables its author community to retain a wide range of rights related to copyright and reuse of materials. They include:
- Posting rights that ensure free access to their work outside the ACM Digital Library and print publications
- Rights to reuse any portion of their work in new works that they may create
- Copyright to artistic images in ACM’s graphics-oriented publications that authors may want to exploit in commercial contexts
- All patent rights, which remain with the original owner

Hongmin Wu

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Uncertainty-aware error modeling and hierarchical redundancy optimization for robotic surface machining

Learning Stable Nonlinear Dynamics and Interactive Force-Aware Variable Impedance Control for Robotic Contact Tasks

Positioning Error Modelling and Compensation Method for Robot Machining Based on RVM

Joint optimization of autoencoder and Self-Supervised Classifier: Anomaly detection of strawberries using hyperspectral imaging

Dynamic neural networks based adaptive optimal impedance control for redundant manipulators under physical constraints

Multimodal Prediction-Based Robot Abnormal Movement Identification Under Variable Time-length Experiences

Learning robot anomaly recovery skills from multiple time-driven demonstrations

Real Time Volume Measurement of Logistics Cartons Through 3D Point Cloud Segmentation

Endowing Robots with Longer-term Autonomy by Recovering from External Disturbances in Manipulation Through Grounded Anomaly Classification and Recovery Policies

Variational Augmented the Heuristic Funnel-Transitions Model for Dexterous Robot Manipulation

Multimodal Sparse Representation for Anomaly Classification in A Robot Introspection System

Integration of Visual Information and Robot Offline Programming System for Improving Automatic Deburring Process

Recovering from External Disturbances in Online Manipulation through State-Dependent Revertive Recovery Policies

Robot introspection with Bayesian nonparametric vector autoregressive hidden Markov models

Learning human-robot collaboration insights through the integration of muscle activity in interaction motion models

Sequence-modification based collision-free motion planning of multiple robots workcell