Selected Papers from the 10th International Conference on Automation, Control and Robotics Engineering (CACRE 2025)

A special issue of Machines (ISSN 2075-1702). This special issue belongs to the section "Automation and Control Systems".

Deadline for manuscript submissions: 31 January 2026 | Viewed by 734

Special Issue Editor


E-Mail Website
Guest Editor
Department of Mechanical Engineering, The Hong Kong Polytechnic University, Hong Kong, China
Interests: synthesis and optimization of parallel and hybrid mechanisms; generalized parallel mechanisms research; reconfigurable robots; micro/nano manipulation and mems devices (e.g., sensors); rescue robots; smart biomedical instruments (e.g., exoskeleton robots and rehabilitation robotics); AI/robotics/autonomous systems; aerial and underwater robotics and artificial intelligence for robotics
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The 2025 10th International Conference on Automation, Control and Robotics Engineering (CACRE 2025) will be held at Wuxi, China, from July 16 to 19, 2025 (https://www.cacre.org/index.html).

The CACRE series of conferences have been successfully held for 9 years since 2016, attracting scholars and students from all over the world. The CACRE 2025 conference will provide a wonderful forum for you to update your knowledge base and explore the innovations in automation, control, and robotics engineering.

This Special Issue will consider contributions from the conference CACRE 2025. Papers should fulfill the requirements at [Preprints and Conference Papers] (https://www.mdpi.com/journal/machines/instructions). The topics of this Special Issue include, but are not limited to, the following:

  • Robotics science and engineering;
  • Control science and engineering;
  • Automation science and engineering;
  • Vision science and engineering.

Prof. Dr. Dan Zhang
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Machines is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • modeling and identification
  • robot control
  • mobile robotics
  • perception systems
  • micro robots and micro-manipulation
  • visual serving
  • search, rescue, and field robotics
  • robot sensing and data fusion
  • localization, navigation, and mapping
  • dexterous manipulation
  • medical robots and bio-robotics
  • space and underwater robots
  • tele-robotics
  • mechanism design and applications
  • adaptive control
  • robust control
  • process control
  • co-operative control
  • identification and estimation
  • nonlinear systems
  • intelligent systems
  • precision motion control
  • control applications
  • control engineering education
  • human–robot interactions
  • process automation
  • intelligent automation
  • factory modeling and simulation
  • home, laboratory, and service automation
  • planning, scheduling, and coordination
  • nano-scale automation and assembly
  • instrumentation systems

Benefits of Publishing in a Special Issue

  • Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • Reprint: MDPI Books provides the opportunity to republish successful Special Issues in book format, both online and in print.

Further information on MDPI's Special Issue policies can be found here.

Published Papers (1 paper)

Order results
Result details
Select all
Export citation of selected articles as:

Research

17 pages, 3783 KB  
Article
A Dual-Task Improved Transformer Framework for Decoding Lower Limb Sit-to-Stand Movement from sEMG and IMU Data
by Xiaoyun Wang, Changhe Zhang, Zidong Yu, Yuan Liu and Chao Deng
Machines 2025, 13(10), 953; https://doi.org/10.3390/machines13100953 - 16 Oct 2025
Viewed by 228
Abstract
Recent advances in exoskeleton-assisted rehabilitation have highlighted the significance of lower limb movement intention recognition through deep learning. However, discrete motion phase classification and continuous real-time joint kinematics estimation are typically handled as independent tasks, leading to temporal misalignment or delayed assistance during [...] Read more.
Recent advances in exoskeleton-assisted rehabilitation have highlighted the significance of lower limb movement intention recognition through deep learning. However, discrete motion phase classification and continuous real-time joint kinematics estimation are typically handled as independent tasks, leading to temporal misalignment or delayed assistance during dynamic movements. To address this issue, this study presents iTransformer-DTL, a dual-task learning framework with an improved Transformer designed to identify end-to-end locomotion modes and predict joint trajectories during sit-to-stand transitions. Employing a learnable query mechanism and a non-autoregressive decoding approach, the proposed iTransformer-DTL can produce the complete output sequence at once, without relying on any previously generated elements. The proposed framework has been tested with a dataset of lower limb movements involving seven healthy individuals and seven stroke patients. The experimental results indicate that the proposed framework achieves satisfactory performance in dual tasks. An average angle prediction Mean Absolute Error (MAE) of 3.84° and a classification accuracy of 99.42% were obtained in the healthy group, while 4.62° MAE and 99.01% accuracy were achieved in the stroke group. These results suggest that iTransformer-DTL could support adaptable rehabilitation exoskeleton controllers, enhancing human–robot interactions. Full article
Show Figures

Figure 1

Back to TopTop