MEDER 2026

Author Instruction

Accepted full papers of registered participants will be published in the Scopus indexed book of the Springer Series Mechanisms and Machine Science, with the title: “Advances in Mechanism Design for Robots – MEDER 2026”.

The official language of the Symposium for publications and all oral presentations will be English.

Please use Springer's official paper template, in Latex or MS Word, available through the following links:

LaTex2e template

MS Word template

It will provide an example of a Springer chapter with minimal style requirements and instructions for Sections, Equations, Figures, Tables, and References.

The paper must be at least 6 pages and must not exceed 8 pages.  Color figures are welcomed.

Only papers with at least one author as a registered participant will be included in the proceedings. Authors of accepted papers must be registered before the early registration deadline.

Accommodation

Uberlandia provides accommodation in several hotels of different categories. Early reservation is recommended by directly contacting the Organising Committee Secretariat. A list of hotels will be soon on the site of the conference available.

General Chairs:

Rogério Sales Gonçalves (Brazil)

Marco Ceccarelli (Italy)

Organized by

Federal University of Uberlandia

Faculty of Mechanical Engineering

Scientific Committee

Marco Ceccarelli (Univ. of Rome Tor Vergata, Italy, Chair)

Ding Xilun (Beihang Univ., China)

Mario Acevedo (Univ. Panamericana, Mexico)

Shaoping Bai (Aalborg Univ., Denmark)

Yukio Takeda (Tokyo Inst Tech., Japan)

Alba Perez (Tech. Univ. Barcelona, Spain)

Yan Jin (Belfast Univ., UK)

Erwin-Chr. Lovasz (Poli. Univ. Timisoara, Romania)

Said Zeghloul (Poitiers Univ., France)

Chedli Bouzgarrou (SIGMA Clermont, France)

Victor Petuya (Univ. of Basque Country, Spain)

Alexey Fomin (IMASH RAN, Russia)

Kenji Hashimoto (Waseda University, Japan)

Gao Huang (Beijing Tech. Univ., China)

Matteo Russo (Univ. of Rome Tor Vergata, Italy)

Rogério Sales Gonçalves (UFU, Brazil)

Technical Sponsors

IFToMM

IFToMM Brazil

TC for Robotics and Mechatronics

TC Linkages and Mechanical Controls

TC for Computational Kinematics

Keynotes

Speaker: Sunil K. Agrawal, Ph.D., Professor                                      

Department of Mechanical Engineering                                                                      

Department of Rehabilitation and Regenerative Medicine    

Columbia University, New York, USA.

Title: Rehabilitation Robotics: Improving Everyday Human Functions

Abstract: Neural disorders, old age, and traumatic brain injury limit activities of daily living. Robotics can be used in novel ways to characterize human neuromuscular responses and retrain human functions. Columbia University Robotics and Rehabilitation (ROAR) Laboratory designs innovative mechanisms/robotics with these goals and performs scientific studies to improve human functions such as standing, walking, stairclimbing, trunk control, head turning, and others. Human experiments have targeted individuals with stroke, cerebral palsy, Parkinson’s disease, spinal cord injury, ALS, and elderly subjects. The talk will provide an overview of these robotic technologies and scientific studies performed with them to demonstrate strong potential of rehabilitation robotics to improve human functions and quality of life of people.

Biography: Sunil Agrawal received a Ph.D. degree in Mechanical Engineering from Stanford University in 1990. He is currently a Professor and Director of Robotics and Rehabilitation (ROAR) Laboratory at Columbia University, located both in engineering and medical campuses of the university. Dr. Agrawal has published more than 500 journal and conference papers, 20 U.S. patents, and 4 books. He is a Fellow of the ASME and AIMBE. His honors include a NSF Presidential Faculty Fellowship from the White House in 1994, a Bessel Prize from Germany in 2003, and a Humboldt US Senior Scientist Award in 2007. He is a recipient of 2016 Machine Design Award from ASME for “seminal contributions to design of robotic exoskeletons for gait training of stroke patients” and 2016 Mechanisms and Robotics Award from the ASME for “cumulative contributions and being an international leading figure in mechanical design and robotics”. He is a 2023 recipient of a Paintal Chair from Indian National Science Academy. He was a Plenary Speaker at the 2024 IEEE International Conference in Robotics and Automation in Yokohama.  He has successfully directed 40+ PhD student theses and has received Best Paper awards in ASME and IEEE sponsored robotics conferences. He is the founding Editor-in-Chief of the journal “Wearable Technologies” published by Cambridge University Press. He organized the IEEE BioRob 2020 conference in New York City and served as its conference chair.

Speaker: Dr. Juan Carlos A. Jáuregui Correa

Universidad Autónoma de Querétaro

Mexico

Title: Predicting Failures in Robotic Mechanisms through Artificial Intelligence

Abstract: The growing complexity of robotic systems demands reliable methods to ensure continuous operation. This keynote explores how Artificial Intelligence (AI) can predict mechanical failures in robot mechanisms by combining dynamic modeling, vibration data, and learning algorithms. Using physics-informed neural networks and experimental validation, Dr. Jáuregui demonstrates how degradation patterns can be detected early and how the remaining useful life of components can be estimated with high accuracy. The lecture presents practical applications where AI-based diagnostics outperform traditional approaches, emphasizing their potential to transform predictive maintenance and enhance the reliability of robotic systems in industrial environments.

Biography: Dr. Juan Carlos A. Jáuregui Correa is a Professor and Researcher at the Faculty of Engineering, Autonomous University of Querétaro, Mexico. His work focuses on vibration analysis, machine dynamics, and predictive maintenance supported by AI and computational modeling. He has led numerous academic and industrial projects, authored multiple scientific publications, and holds patents in dynamic testing and intelligent monitoring of rotating machinery. His research aims to bridge the gap between mechanical engineering and data-driven reliability in advanced mechatronic systems.

Speaker: Tarcisio A. Hess-Coelho

University of Sao Paulo (USP)

Brazil

Title: Modular modelling and control of parallel mechanisms

Abstract: During the last two decades, parallel robots have become more ubiquitous, employed in a great variety of sectors, from food to aerospace industries. In fact, they are much more efficient than their serial counterparts in terms of performing fast motions and consuming less energy. However, due to their mechanical complexity, they present a highly complex non-linear dynamics, which makes the modelling and control tasks difficult. A Modular Modeling Methodology (MMM) can be employed to formulate the dynamic equations for closed-loop redundant and non-redundant mechanisms of any topology that can operate in 2D- or even in 3D-spaces. Such methodology has been successfully applied to many multi-body systems, namely, parallel robots, exoskeletons and manipulators. With respect to the process for the model generation, the MMM allows the analyst to build the dynamic model from an approach in three tiers, namely, the tier of the links (bodies), the tier of the kinematic chains and the tier of the mechanism. Regarding the control of non-redundant parallel mechanisms, here two laws of hybrid control are shown, implemented in the joint and task spaces, in order to improve their dynamic behavior when performing fast motions. Additionally, for parallel mechanisms with actuation redundancy, an alternative motion control is presented, characterized by simplicity and effectiveness related to the implementation and accuracy, respectively. Regarding the motion planning, some indices are proposed in order to select the appropriate non-redundant actuation modes that can achieve comparable performances with respect to the redundant one. Experimental results evidenced a good correlation between those indices and the path tracking error.

Biography: TARCISIO A. HESS-COELHO received the Mechanical engineer (1987), the M.Sc. (1990) and the Ph.D. degrees in Mechanical Engineering (1997), all from the University of Sao Paulo, with postdoctoral studies at Stanford University (2001-2002), under the supervision of Bernard Roth. He is currently associate professor at the University of Sao Paulo. He has been Chair of Member Organization (MO) Brazil of the International Federation for the promotion of theory of mechanisms and machines (IFTomMM) since June 2018, in addition to being a member of the Robotics and Multibody dynamics technical committees of this federation. He is the author of two books, more than 70 articles, and one patent. He has experience in the field of Mechatronics Engineering, with an emphasis on Synthesis and Optimization Methods Applied to Mechanical Design, working mainly on the following topics: parallel mechanisms, robotics, bioengineering, automotive engineering and machine tools.