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Machines
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Selected Papers from the 8th International Symposium on Multibody Systems...
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Selected Papers from the 8th International Symposium on Multibody Systems and Mechatronics

A special issue of Machines (ISSN 2075-1702). This special issue belongs to the section "Robotics, Mechatronics and Intelligent Machines".

Deadline for manuscript submissions: closed (31 December 2025) | Viewed by 2213

Special Issue Editors

Dr. Mario Acevedo

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Guest Editor
Facultad de Ingeniería, Universidad Panamericana, Álvaro del Portillo 49, Zapopan 45010, México
Interests: multibody dynamics; experimental robotics and mechatronics; AI in multibody/mechatronic systems; optimization in multibody systems
Dr. Leonardo Valdivia

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Guest Editor
Facultad de Ingeniería, Universidad Panamericana, Álvaro del Portillo 49, Zapopan 45010, México
Interests: applied engineering; IoT; sensors
Prof. Dr. Hiram Ponce

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Guest Editor
Facultad de Ingeniería, Universidad Panamericana, Mexico City 03920, Mexico
Interests: Machine learning; robotics; intelligent systems for healthcare
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Ramiro Velázquez

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Guest Editor
School of Engineering, Josemaría Escrivá de Balaguer 101, Universidad Panamericana, Aguascalientes 20296, Mexico
Interests: assistive technology; mechatronic systems; sensors and actuators; wearables; haptics
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

We are pleased to introduce this Special Issue, which is dedicated to the latest advancements and interdisciplinary contributions in multibody system dynamics and mechatronics. This collection of articles showcases cutting-edge research and novel methodologies, emphasizing fundamental theories and practical applications across various domains. The rapid evolution of computational tools, experimental techniques, and analytical methods has significantly influenced these fields, fostering deeper integration with other disciplines and expanding their impact on modern engineering and science.
Multibody system dynamics serves as a cornerstone for understanding and predicting the behavior of complex mechanical systems, providing invaluable insights into the kinematics and dynamics of machines and mechanisms. The innovation potential becomes limitless when combined with mechatronics, a field that synergizes mechanical engineering, electronics, control theory, and computational intelligence. This Special Issue explores these synergies and their applications in robotics, vehicle dynamics, biomechanics, mechanical design, artificial intelligence, and optimization.

The featured articles span a diverse range of topics, including, but not limited to, the following:

  • Kinematics and dynamics of machines and mechanisms: novel approaches to motion analysis, flexible multibody systems, and real-time simulations.
  • Control theory and mechatronics: advances in adaptive, robust, and intelligent control strategies for complex electromechanical systems.
  • Optimization and mechanical design: methods for enhancing system performance, reducing energy consumption, and improving reliability.
  • Artificial intelligence and robotics: machine learning-driven modeling, autonomous systems, and intelligent motion planning.
  • Vehicles and biomechanics: applications in automotive engineering, human movement analysis, and bio-inspired robotic systems.

The contributions presented here stem from the collaborative efforts of researchers and practitioners worldwide, reflecting the field's multidisciplinary nature. We hope this Special Issue will be a valuable resource for academics, engineers, and professionals, inspiring future innovations and fostering cross-disciplinary collaborations.

Dr. Mario Acevedo
Dr. Leonardo Valdivia
Prof. Dr. Hiram Ponce
Prof. Dr. Ramiro Velázquez
Guest Editors

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 250 words) can be sent to the Editorial Office for assessment.

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

  • multibody system dynamics
  • kinematics
  • vehicle dynamics
  • biomechanics
  • robotics
  • mechatronics

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

Published Papers (3 papers)

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Research

17 pages, 2172 KB  
Article
Combining Augmented Reality Guidance and Virtual Constraints for Skilled Epidural Needle Placement
by Daniel Haro-Mendoza, Marcos Lopez-Magaña, Luis Jimenez-Angeles and Victor J. Gonzalez-Villela
Machines 2026, 14(4), 446; https://doi.org/10.3390/machines14040446 - 17 Apr 2026
Viewed by 440
Abstract
Accurate needle insertion during epidural anesthesia is challenging due to strong dependence on clinician experience and the limited integration of guidance modalities that simultaneously provide visual feedback and physical motion constraints. Current approaches, including ultrasound guidance and augmented reality visualization, mainly offer passive [...] Read more.
Accurate needle insertion during epidural anesthesia is challenging due to strong dependence on clinician experience and the limited integration of guidance modalities that simultaneously provide visual feedback and physical motion constraints. Current approaches, including ultrasound guidance and augmented reality visualization, mainly offer passive assistance and do not actively regulate insertion trajectory and depth, which may lead to variability in accuracy and increased risk of complications. This work presents a multimodal human–machine assistance system that combines augmented reality guidance with virtual fixtures to support lumbar epidural needle placement. A Tuohy needle is coupled to a haptic device interacting with a patient-specific L3–L4 lumbar phantom fabricated using 3D printing and ballistic gel. A model-based force profile reproduces the mechanical response of anatomical layers during insertion. Three experimental conditions are evaluated: freehand execution, augmented reality guidance with trajectory and depth visualization, and cooperative guidance using virtual fixtures defined by a cylindrical corridor and a depth-limiting plane. Results show a progressive reduction in mean depth error from 6.82 ± 3.46 mm (freehand) to 4.96 ± 2.41 mm (augmented reality) and 2.21 ± 1.73 mm (virtual fixtures). These findings indicate that the integration of visual and haptic guidance significantly enhances insertion precision and control. The proposed approach highlights the potential of multimodal human–machine cooperation for safer training and assisted interventions. Full article
(This article belongs to the Special Issue Selected Papers from the 8th International Symposium on Multibody Systems and Mechatronics)
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18 pages, 8749 KB  
Article
Biomechanical and Signal-Based Characterization of Karate Lateral Kicks Using Videogrammetry Analysis
by Luis Antonio Aguilar-Pérez, Jorge Luis Rojas-Arce, Luis Jímenez-Ángeles, Carlos Alberto Espinoza-Garces, Adolfo Ángel Casarez-Duran and Christopher René Torres-SanMiguel
Machines 2026, 14(3), 339; https://doi.org/10.3390/machines14030339 - 17 Mar 2026
Viewed by 692
Abstract
Martial arts have evolved from self-defense practices into structured competitive sports that demand high levels of neuromotor control, where improper execution remains a major source of injury. This study evaluates lower-limb control during the execution of the karate lateral kick using videogrammetry biomechanical [...] Read more.
Martial arts have evolved from self-defense practices into structured competitive sports that demand high levels of neuromotor control, where improper execution remains a major source of injury. This study evaluates lower-limb control during the execution of the karate lateral kick using videogrammetry biomechanical analysis. Three participants were recorded during regular training sessions and selected according to their level of expertise. Each participant performed lateral kicks at three predefined distances (close, comfortable, and long), selected based on common training practice and individual biomechanical considerations. Videogrammetry data were generated using Kinovea version 0.9.5 software to extract sagittal ankle trajectories. Statistical analyses were carried out in MATLAB version 2025b using spatial coordinates to obtain kinematic data on the practitioner’s performance. The results revealed skill-dependent differences in movement control, characterized by temporal evolution of kinematic variables and their corresponding time–frequency representations. Novice practitioners exhibited limited control during the raising and recovery phases, despite reaching the target. In contrast, expert practitioners demonstrated consistent posture, controlled acceleration during impact, and stable limb trajectories during descent. These observations provide a foundation for data-driven classification of kick execution quality and outline potential applications in supervised learning, real-time feedback systems, and injury risk reduction during karate training. Full article
(This article belongs to the Special Issue Selected Papers from the 8th International Symposium on Multibody Systems and Mechatronics)
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25 pages, 3675 KB  
Article
Natural Motion Design for Energy-Efficient Pick-and-Place Scenarios
by Juan Pablo Mora, Carlos F. Rodriguez and Burkhard Corves
Machines 2026, 14(3), 330; https://doi.org/10.3390/machines14030330 - 14 Mar 2026
Viewed by 394
Abstract
Reducing the energy consumption of industrial robots performing pick-and-place tasks is required to increase profitability while reducing carbon footprint. Natural motion stands out as a mixed-energy-reduction strategy, especially useful for cyclical tasks. An optimization approach is proposed for calculating the elastic parameters, namely [...] Read more.
Reducing the energy consumption of industrial robots performing pick-and-place tasks is required to increase profitability while reducing carbon footprint. Natural motion stands out as a mixed-energy-reduction strategy, especially useful for cyclical tasks. An optimization approach is proposed for calculating the elastic parameters, namely the stiffness and equilibrium position, of constant-stiffness springs parallel to the actuators of parallel robots. Three typical trajectory-dependent methods for calculating these parameters are presented: free-vibration response, optimized, and predefined trajectory. As the set of springs and the task specification are strongly coupled, deviations from the nominal task would require replacing or removing the springs. Therefore, two adjustment strategies, one based on trajectory optimization and the other on equilibrium position update, are proposed to further exploit the natural motion. All optimization problems are solved and compared in a case study of a five-bar linkage performing a nominal pick-and-place task. Then, a palletizing pick-and-place scenario is introduced to perform the proposed trajectory and equilibrium adjustments. It is shown that using nominal springs reduces energy consumption near the nominal task, and implementing the proposed adjustments reduces energy over a wider region. Full article
(This article belongs to the Special Issue Selected Papers from the 8th International Symposium on Multibody Systems and Mechatronics)
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