Category: News

Thrilled to share our newly accepted paper in IEEE Transactions on Medical Robotics and Bionics, where we introduce a soft, endoscope-deployable microfluidic suction robot that combines multimodal intraluminal locomotion with localized aspiration and sampling for targeted mucus clearance and liquid biopsy.

🧠✨ What we developed:

A soft intraluminal robotic platform that:

🔹 Integrates Locomotion + Sampling: A pneumatically controlled 2×2 pouch matrix for multimodal actuation, paired with an independent microfluidic suction module for active liquid extraction and sample recovery.

🔹 Enables Stable Pitch Control: A balloon-based pitch control mechanism improves controllability for intraluminal operation, with the best overall performance observed at an initial pressure range of 2–3 kPa.

🔹 Balances Compliance and Safety: Single-pouch characterization guided the selection of a 2 mm pouch radius, achieving up to 246.91% maximum deformation; burst tests show a system safety factor ≈ 5.27 under the reported operating conditions.

🔹 Targets Real Clinical Pain Points: Designed for constrained lumens (e.g., distal airway) where conventional airway clearance approaches struggle with reach and effectiveness.

🎯 Key Results:

✅ Multimodal mobility: Differential actuation achieves 26.9 mm/min forward speed and 4.86° yaw per drive cycle.

✅ Robust suction across viscosities: Efficiently extracts 20–80% glycerol solutions within 10 s (via parameter tuning).

✅ In vivo feasibility: Endoscope-assisted porcine validation confirmed sequential pouch-driven motion and successful recovery of biological samples containing mucus and tissue fragments after saline irrigation.

💡 Why it matters:

This work demonstrates a compliant, integrated “move + anchor + suction” approach for narrow lumens—supporting safer localized intervention and sampling, with a path toward distal airway translation.

🌱 What’s next?

We’re moving toward more automated closed-loop pneumatic control, improved steerability/navigation, and miniaturization for deeper airway access—while expanding validation in airway-specific models.

May 29, 2026, Óbudai University – Prof. Hongliang Ren of The Chinese University of Hong Kong (CUHK) and Prof. Peter Kazanzides of Johns Hopkins University were invited to present a joint seminar at the Antal Bejczy Center for Intelligent Robotics (IROB), University Research and Innovation Center (EKIK), Óbuda University, Budapest, Hungary.

The seminar was held on 29 May 2026 at the BARK/IROB Nagylabor, with both in‑person and online attendance via Google Meet. The event was hosted by Prof. Tamás Haidegger, Medical Robotics Lead at IROB.

This bilateral academic exchange was supported by the Ministry of Science and Technology of China (MOST) and Hungarian bilateral research projects, fostering international collaboration in medical robotics.

Seminar Talks

Prof. Hongliang Ren presented a talk titled “Endoluminal Robotics & Embodied AI in vivo,” highlighting recent advances in continuum robotics, motion perception, and intelligent image‑guided minimally invasive procedures. He discussed how procedure‑specific telerobotic systems with variable stiffness and context awareness can assist surgeons in performing dexterous manipulations.

Prof. Peter Kazanzides presented a talk titled “Augmented Reality for Robotic Surgery,” sharing his extensive experience from the development of the da Vinci Research Kit (dVRK) and clinical systems.

Speaker Bios

Prof. Hongliang Ren is a Professor at The Chinese University of Hong Kong. He received his Ph.D. from CUHK in 2008 and has held positions at Johns Hopkins University, Harvard Medical School, and National University of Singapore. He is a recipient of the National Science Fund for Distinguished Young Scholars (Scheme A), the CUHK Young Researcher Award, and over 30 other prestigious awards. He has published over 240 papers with more than 22,000 citations and an H‑index of 75, and has been consistently listed among the world’s top 2% most‑cited scientists.

Prof. Peter Kazanzides is a Research Professor of Computer Science at Johns Hopkins University. He received his Ph.D. in Electrical Engineering from Brown University in 1988. He co‑founded Integrated Surgical Systems, which commercialized the Robodoc System for hip and knee replacement surgeries performed on over 20,000 patients. He later joined JHU and contributed to the development of the da Vinci Research Kit (dVRK).

Audience and Discussion

The seminar attracted researchers and students from IROB and partner institutions. Both talks were followed by a joint Q&A session, where attendees discussed technical challenges in continuum robotics, augmented reality guidance, and clinical translation of robotic systems. The event concluded with informal discussions over refreshments, reinforcing the bilateral collaboration between Chinese and Hungarian research groups.

May 21–23, 2026 – Prof. Hongliang Ren of The Chinese University of Hong Kong (CUHK) was invited to deliver a keynote lecture at the 6th International Conference on Robotics and Control Engineering (RobCE 2026), held at The Hong Kong Polytechnic University.

The conference was co‑organized by The Hong Kong Polytechnic University and Southeast University, with support from several engineering societies. Prof. Ren served on the Program Committee of the conference.

Keynote Lecture: Endoluminal Robotics & Embodied AI in vivo

On the morning of 22 May 2026, Prof. Ren presented a talk titled “Endoluminal Robotics & Embodied AI in vivo.” The lecture focused on recent developments in dexterous robotic motion generation and motion perception for intelligent image‑guided minimally invasive procedures.

Prof. Ren highlighted how procedure‑specific telerobotic surgical systems can assist surgeons in performing dexterous manipulations using continuum motion generation mechanisms with variable stiffness and context awareness. The talk addressed the opportunities and challenges brought by minimally invasive surgeries, particularly in surgical motion generation, motion understanding, and intelligent robotic manipulation.

Short Bio of Prof. Hongliang Ren

Prof. Ren received his Ph.D. in Electronic Engineering (Biomedical Engineering) from CUHK in 2008. He has held academic positions at Johns Hopkins University, Boston Children’s Hospital, Harvard Medical School, and the National University of Singapore. He is a recipient of the National Science Fund for Distinguished Young Scholars (Scheme A), the CUHK Young Researcher Award, and multiple best paper awards. He has been consistently listed among the world’s top 2% most‑cited scientists by Stanford University. He has published over 240 papers with more than 22,770 citations and an H‑index of 75.

Audience Engagement

The keynote session was attended by researchers, faculty members, and students from both online and offline venues. Prof. Ren’s talk was followed by a brief Q&A session, where the audience engaged in discussion on continuum robotics, embodied AI, and clinical translation of surgical robots.

NANJING, May 16, 2026 – Prof. Hongliang Ren of The Chinese University of Hong Kong attended the 38th Chinese Control and Decision Conference (CCDC 2026), which opened at the Nanjing Fengda International Hotel and featured a forum titled “Knowledge and Data-Driven Intelligent Diagnosis and Treatment“. The forum gathered leading experts in control theory, biomedical engineering, and artificial intelligence to explore how modern intelligent systems are reshaping the future of healthcare.

Chaired by Prof. Guanglin Li of the Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, the forum featured invited speakers (Profs. YT Zhang, Max QH Meng, L Meng, HL. Ren, HR. Li & Y Chen) sharing perspectives on how knowledge-driven models, data-driven methods, and intelligent control technologies can support the next generation of diagnosis, treatment, and clinical decision-making.

The forum’s central theme revolved around the integration of “knowledge-driven” and “data-driven” paradigms for intelligent diagnosis and treatment. Panelists deliberated on how cutting-edge technologies—including advanced AI theories, modern signal processing, and intelligent decision-making and feedback mechanisms—can be applied across the entire clinical workflow, ranging from model-based disease dynamic prediction and intelligent drug dosage regulation to personalized rehabilitation robots and closed-loop neuromodulation systems. This multi-disciplinary exchange aims to drive the transformation of diagnostic and therapeutic models from passive and static to active, dynamic, and closed-loop interventions.

Connecting Robotics Innovation with Intelligent Healthcare

Prof. Ren leads pioneering work in intelligent surgical robotics, soft continuum robots, and medical mechatronics, with a strong focus on translational biomedical engineering. His recent project, “Embodied Intelligence Systems for Fine Perception and Dexterous Manipulation in Flexible Endoscopy,” funded as a key national project, aims to develop perceptive, compliant, and intelligent surgical systems.

Following the talk, Prof. Ren received a Certificate of Appreciation from CCDC 2026 and was pictured with Forum Chair Prof. Guanglin Li.

Prof. Ren’s team’s developing miniature flexible robots capable of navigating narrow, tortuous lumen branches to perform multi-modal micro-biopsy and immune-sensing in the vicinity of small confined spaces.

The forum concluded with a forward-looking discussion on how the integration of AI, control theory, and robotics can address major clinical challenges, catalyze original technological breakthroughs, and provide strategic support for the development of intelligent healthcare system, bridging foundational robotics and mechatronics with clinical needs to create next-generation smart surgical systems.

On 13 May 2026, Prof. Ren Hongliang’s research group visited the Endoscopy Center at the Sixth Affiliated Hospital of Sun Yat‑sen University in Guangzhou. The visit was hosted by Prof. Hu Jiancong.

Activities

• 16:00 – 17:00: Tour of the endoscopy unit and introduction to the center’s clinical work (Prof. Hu).
• 17:00 – 18:30: Research presentations from the CUHK group in the seminar room. Prof. Ren gave an overview of the group’s recent work, followed by talks from four lab members:
  – Wu Zhijie on a vision‑language‑action model for endoscopic assistance
  – Wang Erqi on 3D intelligent perception and navigation for endoscopic ultrasound
  – Wang Guankun on multimodal models applied to continuum robotics
  – Zhou Rulin on a model‑based autonomous control system for surgery
• 18:30 – 18:45: Summary and open discussion chaired by Prof. Hu and Prof. Ren.

The visit provided an opportunity to exchange perspectives on clinical needs and technical developments in endoscopy and continuum robotics.

On Tuesday, 12 May 2026, Prof. Guangzhong Yang visited Prof. Ren Hongliang’s laboratory.

During the visit, lab members presented ongoing research through a series of demonstrations. Dr. Yang Yang, Dr. Gao Huxin, Dr. Liu Tangyou, Botao, Haoxuan, and other members showcased recent work including:

• Sub‑mm continuum robots
• Endoscopy systems
• Sensing technologies for medical applications

The visit provided an opportunity for technical exchange and discussion on future directions in medical robotics and minimally invasive devices.

Short bio of Prof. Guangzhong Yang

Prof. Guangzhong Yang received his Bachelor’s degree from Shanghai Jiao Tong University and his Ph.D. from Imperial College of Science, Technology and Medicine. He was a Principal Scientist at Royal Brompton Hospital London and later served as Lecturer, Reader, and Full Professor at Imperial College London, where he founded and directed the Hamlyn Centre for Robotic Surgery. He is currently Chair Professor and Founding Dean of the Institute of Medical Robotics at Shanghai Jiao Tong University. His research focuses on medical imaging, sensing, and robotics. He is a Fellow of the Royal Academy of Engineering, IEEE, IET, AIMBE, IAMBE, MICCAI, and CGI, a recipient of the Royal Society Research Merit Award, the Founding Editor of Science Robotics, and was awarded a CBE in the Queen’s 2017 New Year Honours for contributions to biomedical engineering.

Changsha, China, May 9, 2026 — Professor Hongliang Ren from the Department of Electronic Engineering, The Chinese University of Hong Kong, was invited to speak at High-Level Talent Forum III during the 41st Youth Academic Annual Conference of Chinese Association of Automation (YAC2026).

At High-Level Talent Forum III, Professor Ren delivered an invited presentation titled “Flexible Robots and Embodied Intelligence for Minimally Invasive Intraluminal Procedures.” His talk focused on recent advances in dexterous robotic motion generation and motion perception for image-guided minimally invasive procedures. He discussed how flexible robotic systems, multi-sensory perception, and embodied intelligence can support more precise, adaptable, and repeatable robotic intervention in confined anatomical environments.

Professor Ren’s research spans medical embodied intelligence, biomedical and surgical robotics, intelligent control, medical mechatronics, soft continuum robots, soft sensors, and multi-sensory learning for medical robotics.

About YAC

YAC is a national annual academic conference organized by the Chinese Association of Automation and its Youth Working Committee. The 2026 conference was held in Changsha from May 8 to 10, 2026, and hosted by Hunan University. It brought together researchers, young scholars, graduate students, and professionals from automation, artificial intelligence, robotics, intelligent systems, and related disciplines. The conference provided a platform for presenting recent theoretical advances, emerging technologies, and interdisciplinary research outcomes.

May 6, 2026 – The research group of Prof. Hongliang Ren was pleased to host Prof. Pierre Dupont as part of the Faculty of Engineering Distinguished Lecture series.

Prof. Dupont is a Professor of Surgery at Harvard Medical School, Chief of Pediatric Cardiac Bioengineering at Boston Children’s Hospital, and an IEEE Fellow. In his talk titled “Continuum Robotics for Minimally Invasive Interventions: Design Tradeoffs for Clinical Applications,” he presented an engineering perspective grounded in real‑world clinical challenges.

Prof. Dupont discussed three complementary continuum robot architectures – concentric tube robots, magnetic ball chains, and tendon‑actuated systems – each involving distinct tradeoffs in stiffness, steerability, force capability, and hysteresis.

Key highlights from the lecture:

• Concentric tube robots enable precise intracardiac catheterization and bimanual neuroendoscopy.
• Magnetic ball chains offer outstanding steerability for cardiac ablation procedures.
• Tendon‑actuated systems provide a balanced tradeoff between stiffness and dexterity for transcatheter heart valve repair.

The lecture illustrated how tailoring robotic designs to specific clinical constraints can meaningfully expand the capabilities of minimally invasive interventions.

Short bio of Prof. Pierre Dupont

Prof. Dupont received his B.S., M.S., and Ph.D. in Mechanical Engineering from Rensselaer Polytechnic Institute. He was a Postdoctoral Fellow at Harvard University, later a Professor of Mechanical and Biomedical Engineering at Boston University, and is now Chief of Pediatric Cardiac Bioengineering at Boston Children’s Hospital and Professor of Surgery at Harvard Medical School. He is an IEEE Fellow, a former Senior Editor for IEEE Transactions on Robotics, and a member of the Advisory Board for Science Robotics.

Audience engagement

The lecture attracted faculty members and students from engineering and medical backgrounds, followed by a lively Q&A session. Attendees appreciated Prof. Dupont’s clinically driven approach to robotic design, and the discussion continued informally after the talk.

🤖🪢
Thrilled to share our latest work published on Nature Communication, which redefines actuation for tendon-driven continuum robots — achieving full 3D omnidirectional motion and body twist using only a single tendon.

🧠✨ What we developed: A new class of continuum robots that:
🔹 Breaks Design Constraints: Eliminates the inherent trade-off between miniaturization and 3D manipulability by replacing multiple tendons with a single eccentric one.
🔹 Push-Pull-Twist Actuation: Achieves complex spatial movement through a unique driving mechanism.
🔹 High Efficiency: Features an outer diameter of 2.0–3.5 mm with a hollow ratio exceeding 57% — doubling the spatial utilization of traditional designs.
🔹 Open-Source Support: Includes a derived kinematics model and an open-source simulator for the robotics community.

🎯 Key Results:

• ✅ >1,000-fold Improvement: Massive increase in manipulability compared to conventional multi-tendon mechanisms.
• ✅ High Force Retention: Retains at least 70% of tip force across all directions.
• ✅ Versatile Demonstration: Proven success in teleoperation, navigation through tortuous environments, and “chopstick-like” continuum grippers.

💡 Why it matters: This work proves that miniature robots can maintain high dexterity and power without the bulk of traditional hardware, pointing toward the next generation of surgical actuators.

🌱 What’s next? We are exploring potential medical applications and the integration of these actuators into complex surgical procedures.

Thrilled to share our latest international collaboration! At NVIDIA GTC 2026 in San Jose, CA, the team led by Professor Hongliang Ren from The Chinese University of Hong Kong (CUHK), in partnership with NVIDIA and 35 leading global institutions, officially released Open-H-Embodiment, the world’s first and largest open-source dataset for medical robotics, now available on HuggingFace.

During the GTC keynote, Kimberly Powell, NVIDIA’s VP of Healthcare, highlighted this milestone. Our lab is honored to be a primary contributor, filling the critical gap in Embodied AI for medical robotics by providing high-fidelity data for contact dynamics and closed-loop control.

🧠✨ What we contributed & developed:

This project breaks the “perception-heavy, execution-light” limitation of traditional medical AI. Key highlights include:

🔹 778 Hours of Massive Multimodal Data: The dataset covers 400 complete clinical surgeries and 9 major robotic platforms (e.g., dVRK, CMR Versius, Kuka). It includes 65% clinical data, 23% bench-top experiments, and 12% simulation data.

🔹 Three High-Value Specialized Datasets from Our Lab:

• Dual-Source Ultrasound Dataset: Experts-level trajectories covering in-vivo porcine EUS and human forearm scanning, overcoming complex organ environments and multi-device calibration.
• Robotic Surgery Skill Dataset: Multi-modal data (RGB/RGB-D + Kinematics) for tissue manipulation and suturing, featuring millisecond-level synchronization and dual-mode control (teleoperation & automation).
• Flexible Endoscope Tracking Baseline: A standardized dataset addressing hysteresis and deformation in flexible endoscopy, supporting nanosecond-level time synchronization.

🔹 Surgical VLA & World Models:

• GR00T-H: A 3B-parameter Vision-Language-Action model based on NVIDIA Isaac GR00T, capable of long-horizon dexterous tasks like end-to-end suturing.
• Cosmos-H-Surgical-Simulator: An action-conditioned world model that boosts simulation efficiency by over 70x, bridging the sim-to-real gap.

🎯 Key Results: ✅ Global Standardization: First effort to unify medical robotic data across different devices and institutions under CC-BY-4.0. ✅ Efficiency Boost: Accelerated surgical simulation (600 sims in 40 mins) to generate high-fidelity video-action pairs. ✅ Clinical Relevance: Successfully captured nearly 500 hours of real-world clinical data for hernia, gallbladder, and uterine surgeries.

💡 Why it matters: This initiative provides the foundational “bedrock” for Medical Physical AI. By sharing high-quality, synchronized data for surgery, ultrasound, and endoscopy, we are lowering the barrier for researchers worldwide to develop autonomous surgical agents that are both explainable and adaptive.

🌱 What’s next? Our lab is continuing to deepen research in: 🔹 Reasoning-based autonomous control for surgical robots. 🔹 Cross-platform generalization of Medical VLA models. 🔹 Clinical translation of Embodied AI to improve patient outcomes.

Datasets address: https://huggingface.co/datasets/nvidia/PhysicalAI-Robotics-Open-H-Embodiment

Project website: https://github.com/open-h

#NVIDIAGTC2026 #MedicalRobotics #EmbodiedAI #HuggingFace #CUHK #OpenSource #HealthcareInnovation