SII 2026
SII 2026

The 2026 IEEE/SICE International Symposium on System Integration (SII 2026) will be held from January 11 to 14, 2026, in the vibrant city of Cancun, Mexico

Institute of Electrical and Electronics Engineers (IEEE)IEEE Robotics and Automation Society (RAS)IEEE Industrial Electronics Society (IES)Society of Instrument and Control Engineers (SICE)SICE System Integration Division (SI)
OMRON SINIC X CorporationUnitree RoboticsHitachi, Ltd.Applied Science and Artificial Intelligence Institute (ASAII)Consejo Quintanarroense de Humanidades, Ciencias y Tecnologías (COQHCYT)Federación Mexicana de Robótica (FMR)

Countdown to #SII2026

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🏝️Keynote Sessions & Speakers

Prof. Kyu-Jin ChoDr. Rafael Murrieta-CidProf. Toshie TakahashiProf. Vicente Parra VegaProf. Katja MombaurProf. Ryo Kurazume
Prof. Kyu-Jin Cho

Prof. Kyu-Jin Cho

Professor @ Seoul National University (SNU)

South Korea

Kyu-Jin Cho is a Professor and the Director of Soft Robotics Research Center and Biorobotics Lab at Seoul National University. He received his Ph.D. in mechanical engineering from MIT and his B.S and M.S. from Seoul National University. He was a post-doctoral fellow at Harvard Microrobotics Laboratory before joining SNU in 2008. He has been exploring novel soft bio-inspired robot designs, including a water jumping robot, various shape-changing robots, and soft wearable robots for the disabled. He has received the 2014 IEEE RAS Early Academic Career Award for his fundamental contributions to soft robotics and biologically inspired robot design. He has published a Science paper on a water jumping robot and several papers in Science Robotics with novel robot designs. He has served RAS as Associate VP of Publication Activities Board, a general chair of RoboSoft 2019, and management committee chair of TMECH. Currently, he serves as VP of the RAS Technical Activities Board and General Chair of ICRA2027.

Presentation TitleSoft Wearable Robots: Creating Technology to Enhance Human Capabilities
Presentation AbstractThe innovative field of soft wearable robots, designed to seamlessly integrate into daily life with unparalleled comfort and flexibility, utilizes textile materials or soft materials to create wearable robots that are lightweight and flexible. Compared to exoskeletons that use rigid frames to transmit the actuation force to the body part, soft wearable robots transmit the forces using tendons, straps, or a composite of rigid and soft material. Naturally, they tend to have fewer constraints in terms of degrees of freedom and have the potential to become a part of everyday life. These robots will provide significant benefits in healthcare, aiding rehabilitation and enhancing the quality of life for individuals with disabilities and the elderly. We will discuss the design principles, functionality, and applications of soft wearable robots, and address current challenges and future prospects.
Keywords🤖 soft robotics🦾 wearable robots🦿 assistive technology
Dr. Rafael Murrieta-Cid

Dr. Rafael Murrieta-Cid

Senior Research Scientist @ Centro de Investigación en Matemáticas (CIMAT)

Mexico

Rafael Murrieta-Cid is a Senior Research Scientist (Investigador Titular D) at the Centro de Investigación en Matemáticas (CIMAT) in Guanajuato, Mexico. He received his B.S. in Physics Engineering from the Monterrey Institute of Technology and Higher Education, Mexico, and his Ph.D. in vision-based robot navigation from the Institut National Polytechnique, Toulouse, France. He conducted his doctoral research with the Robotics Group at LAAS-CNRS in Toulouse. He has held postdoctoral positions at Stanford University and the University of Illinois at Urbana-Champaign (UIUC), and has completed two sabbaticals, one at UIUC and another at INRIA Université Côte d'Azur. His research interests include robotics, robot motion planning, and control theory. Dr. Murrieta-Cid is a member of Mexico's National System of Researchers, rank 3, and a member of the Mexican Academy of Sciences. He currently serves as an Editor for the IEEE Transactions on Robotics.

Presentation TitleVisual-RRT*: Generating Asymptotically Optimal Trajectories with Vision-based Controllers
Presentation AbstractIn this talk, we present a new approach to robot motion planning that anticipates the use of vision-based feedback control during task execution. The proposal is based on the RRT*, which is an asymptotically optimal sampling-based algorithm resulting in a tree that encodes trajectories. The planning method, by construction, guarantees the planned trajectories to be executable in closed-loop with a visual servoing controller. The design of this method requires an image-based visual servoing steering function, which simulates a visual control law to generate local trajectories that extend the current tree. These trajectories must be validated to ensure that they are collision-free and that all image features remain unoccluded and within the camera field of view throughout the local trajectory. First, we provide a theorem showing that the proposed approach is probabilistically complete. Then, results are presented where the strategy is extended to generate asymptotically minimum cost trajectories in the state space using visual control. The method is validated using several robotic systems, both in simulation and with experiments in real robots.
Keywords🤖 robotics🎯 motion planning🎛️ automatic control
Prof. Toshie Takahashi

Prof. Toshie Takahashi

Professor @ Waseda University

Japan

Toshie Takahashi is a Professor at Waseda University, Tokyo. She has been appointed as an Associate Fellow of the CFI, the University of Cambridge. She has held visiting appointments at the University of Oxford, the BKC at Harvard University, and Columbia University. She conducts cross-cultural and trans-disciplinary research on the social impact of robots as well as the potential of AI for Good. She is currently leading two projects on youth and AI. The Goal of both projects is to contribute towards a vision of a future where human happiness takes center stage. The first one is "A Future with AI" project in collaboration with the United Nations. The other project is the Moonshot R&D program by leading the Gen ZAI project, engaging youths now for a global AI future. Finally, Takahashi sits on the advisory committee of the Information and Communication Council, Ministry of the Internal Affairs and Communications, Japan.

Presentation TitleHuman-First Physical AI Innovation: Lessons from the UN and the JST Moonshot Project
Presentation AbstractHow should we understand the paradigm shift brought about by the integration of AI, robotics, and agentic systems? This talk begins by outlining the need for a complex-systems perspective on human-AI interaction, drawing on the "complexity model of communication," which identifies four layers of interaction among individuals, social groups, and culture. I then discuss emerging risks highlighted by leading AI researchers such as Geoffrey Hinton and Yoshua Bengio, particularly the rise of autonomous agentic AI in dynamic socio-technical environments. Cross-cultural comparisons reveal that narratives around AI diverge significantly: Japan emphasizes social benefits, especially in addressing demographic aging, while Western societies express dystopian concerns such as inequality and job displacement. How, then, can we build a future that places human happiness at the center in an increasingly complex and uncertain global society? To address this question, I outline the Human-First Innovation framework, grounded in three pillars: Human-First, Cross-disciplinary innovation, and Self-creation. I present insights from two global youth-centered projects, A Future with AI (United Nations) and Project GenZAI (JST Moonshot), including survey data from 6,000 young people and interviews across seven countries. Finally, I introduce the Smart Robot Ethics Basic Policy and a corresponding checklist to guide the human-centered design and governance of Physical AI.
Keywords🧠 artificial intelligence🤖 robotics🤝 communication
Prof. Vicente Parra Vega

Prof. Vicente Parra Vega

Professor @ Centro de Investigación y de Estudios Avanzados del Instituto Politécnico Nacional (CINVESTAV)

Mexico

Vicente Parra Vega earned two simultaneous degrees, graduating a semester early, from the Universidad Autónoma de Nuevo León (UANL) in 1987, and completed a Master's degree in Automatic Control at CINVESTAV in 1989. He went on to earn a Ph.D. in 1995 from the Department of Mathematical Engineering and Information Physics at the University of Tokyo. His postdoctoral research was conducted at the German Aerospace Center (DLR) in the Department of Robotics and Mechatronics in 2000, followed by a sabbatical in 2010 at the Laboratory for Intelligent Robotics Systems at the University of Texas. He has authored over 300 peer-reviewed publications, including 82 articles in indexed journals and 8 book chapters. Much of this work is based on the original contributions of the 15 Ph.D. and 49 Master's theses he has supervised, many with the students as first authors. His research focuses on robotics and mechatronics, with a particular interest in the modeling and control of nonlinear, uncertain, and perturbed dynamic systems. Since 1990, he has been affiliated with CINVESTAV, where he is currently part of the Department of Robotics and Advanced Manufacturing, a division he co-founded in 2006. He also leads the Laboratory of Emerging Robotic Systems.

Presentation TitleThe Key Role of Integral Sliding Mode Error Coordinate Transformation for Lagrangian Robots
Presentation AbstractAdvanced robots require seamless information flow, process coordination, and shared objectives of each of the interconnected subsystems they are composed of, requiring a just-in-time-and-scale transversal integration. These subsystems introduce highly nonlinear, intertwined frequency-time local dependencies across functional domains. When we consider such local phenomena, consistent assumptions and axioms can be introduced to obtain representative dynamic robot models, which consequently facilitate the design of actionable stability-guaranteed controllers. In this talk, and considering a wide class of Lagrangian advanced robots, we address some fundamentals of a dynamic extension of the Lagrangian system introduced through an integral sliding mode (ISM) error coordinate transformation. It substantiates a convenient open-loop error equation to design model-free and chatterless ISM that guarantees local exponential tracking. This transformation is also instrumental for motor learning on a lower-dimensional manifold, advantageously to design physics-informed neurocontrol and energy-based reinforcement learning. We briefly show some results not only for different configurations and tasks of inertial (manipulators, bimanual and hands, cooperative) and of noninertial robots (aerial, underwater, terrestrial), but also of novel (wearable and exosuit, continuum soft robots, rigid-soft) robots and of human-robot interaction, rehabilitation, and brain-robot interfaces, to name a few.
Keywords🤖 emerging robotics🎛️ nonlinear control⚙️ dynamic systems
Prof. Katja Mombaur

Prof. Katja Mombaur

Professor @ Karlsruhe Institute of Technology (KIT)

Germany

Katja Mombaur is a Full Professor at Karlsruhe Institute of Technology (KIT) in Germany, where she holds the Chair for Optimization & Biomechanics for Human-Centred Robotics and directs the BioRobotics Lab. In addition, she holds an affiliation with the University of Waterloo in Canada, where she has been a Full Professor and Canada Excellence Research Chair (CERC) for Human-Centred Robotics & Machine Intelligence since 2020. Prior to moving to Canada, she was a Full Professor at Heidelberg University, where she directed the Optimization, Robotics & Biomechanics Chair, as well as the Heidelberg Center for Motion Research. Her international experience includes two years as a visiting researcher at LAAS-CNRS in Toulouse and a Postdoc at Seoul National University. She studied Aerospace Engineering at the University of Stuttgart and SupAéro in Toulouse and holds a PhD in Mathematics from Heidelberg University. Katja Mombaur currently serves as the Vice President for Member Activities of the IEEE Robotics & Automation Society and as Senior Editor of the IEEE Transactions on Robotics and has actively contributed to the organization of many conferences and workshops. She is the KIT Spokesperson of the Helmholtz Graduate School of Information and Data Science for Health (HIDSS4Health). Katja's research focuses on understanding human movement by a combined approach of model-based optimization, learning, and experiments, and using this knowledge to improve motions of humanoid robots and the interactions of humans with exoskeletons, prostheses, and external physical devices. Her goal is to endow humanoid and wearable robots with motion intelligence that allows them to operate safely in a complex human world. The development of efficient algorithms for motion generation, control, and learning is a core component of her research.

Presentation TitleTowards Human-Exoskeleton Symbiosis with Predictive Digital Twins
Presentation AbstractExoskeletons hold significant potential in medical and workplace environments, from helping individuals with spinal cord injuries regain mobility to supporting workers and preventing injuries. Unlike many robotic systems, exoskeletons function through direct, continuous physical contact with the user, who becomes effectively integrated into the robot's mechanical structure. This close and long-term interaction presents substantial challenges for control, safety, and user comfort. From a systems integration perspective, achieving true human-exoskeleton cooperation requires addressing the variability and unpredictability of the human user, who remains an essential and adaptable part of the control loop. Instead of viewing the human and the robot as separate entities, effective assistance involves a unified approach to the combined system. This includes customizing mechanical design, control strategies, and assistance profiles to meet individual needs and goals. Key open questions include how exoskeletons should best support human movements, how forces are best transmitted and how humans adapt their motor strategies in response to assistance. Data-driven, optimization-based digital twins of the combined human-exoskeleton system show promise for tackling these questions. By offering predictive models of human biomechanics and movement adaptation, they facilitate simulation-based design and control optimization that consider expected human responses. In this talk, I will cover recent research into human-exoskeleton integration, emphasizing methods for personalized assistance, co-adaptive control, and the use of digital twins to speed up the development of safe, effective, and human-centred exoskeleton technologies.
Keywords🎯 optimization🦾 biomechanics🧑‍🤝‍🧑 human-centred robotics
Prof. Ryo Kurazume

Prof. Ryo Kurazume

Professor @ Kyushu University

Japan

Ryo Kurazume received his Ph.D. from the Tokyo Institute of Technology in 1998. He is currently a Professor and Vice Dean at the Graduate School of Information Science and Electrical Engineering, Kyushu University. He was a director of the Robotics Society of Japan (RSJ), a director of the Society of Instrument and Control Engineers (SICE), and a chairman of the Japan Society of Mechanical Engineers (JSME) Robotics and Mechatronics Division. He received JSME Robotics and Mechatronics Academic Achievement Award, SICE System Integration Division Academic Achievement Award, and JSME Robotics and Mechatronics Division Robotics and Mechatronics Award. He is RSJ Fellow, JSME Fellow, SICE Fellow, and a Senior Member of IEEE.

Presentation TitleInformationally Structured Environment for Service and Construction Robots
Presentation AbstractAn Informationally Structured Environment is an approach in which a wide variety of sensors are installed throughout the environment in which robots operate, and the diverse information collected by these sensors is managed and provided to robots as needed. By doing so, the environment is pre-prepared to facilitate the introduction and operation of robots. In this talk, I will introduce the progression of my research, from early studies on environmental information structuring in indoor settings to more recent developments in civil engineering and construction sites, illustrating how the concept has evolved. I will also discuss the technologies that will be essential for the realization of a future society in which humans and robots coexist.
Keywords🌐 informationally structured environment🏗️ autonomous construction🥽 XR-based human-robot interaction