Center for Intelligent Robotics (智能机器人研究中心)

Key research focus

The Center for Intelligent Robotics aims to advance the science and engineering of Robotics with emphasis on intelligent robot systems. By developing our core expertise in three pillars, namely, (A) Robot Control & Automation, (B) Computational Robotics as well as (C) Robotic Systems & Devices, the center hopes to engage actively in frontier research directed towards the development of cutting-edge technology for Intelligent Robot Systems. At the intersections of these pillars are subjects including Mechatronics, Cybernetics and Cyber-Physical Systems which in turn converge towards our focus on Intelligent Robotics. The envisioned areas include, but are not limited to, (i) robot planning, control & perception, (ii) collaborative robots & physical human-robot interaction (pHRI), (iii) human-machine interface, (iv) smart sensing devices & intelligent imaging technology for robotic systems, (v) probabilistic, knowledge-based, data-driven & cloud robotics, etc. Through a multidisciplinary approach encompassing Robotics, Computational Intelligence and Engineering Design, the center hopes foster strong cross-disciplinary research collaboration and synergize faculty expertise towards the area of Intelligent Robotics unique to ZJUI.

Research projects: Representative research projects include, but not limited to, the following: (some examples, to be consolidated and streamlined towards the center vision)

Robotics in HUMAN supervised (CYBER-PHYSICAL) System for Agriculture [1-2]

•    Mobile Robotics Platform for Poultry Production

•    Mobile Robotics Platform for Plant Factories

•    Autonomous Navigation under Plant Canopy

Robotic Image-Guided Planning, Control & Perception

•    Image-Guided Surgical Planning and Robotic Interventional Procedures [3]

•    Intelligent Intraoperative Imaging [4-7]

•    Robot Vision for Micromanipulator Control [8-12]

Data-Driven Robot-Assisted Surgical Procedures and Training

•    Surgical Video-Data-Driven Trajectory Analysis [13]

•    Kinesthetic Training System for Robotic Surgery [14-15]

•    Human-Robot Interaction and Collaborative Control [16]

Prospective Scope

Adaptive Cyber-Physical Systems

•    Communicating robots in production, e.g. welding robots in car manufacturing

•    Cloud-controlled robots in health care at home, in hospitals and rest-homes

•    Interaction with non-robotic cyber-physical systems

Field Robotics

•    Mobile Robots: Airborne, Underwater, Ground, Wheeled, legged

•    Adaptive Robots: Reconfigurable Robots, Soft Robots, Swarm Robotics

The New-Generation Robotics

Bio-robotics, Cyborg, Molecular Robotics, Quantum Robotics

4) Key members of the center

Hongwei Wang; Huan Hu, Jiahuan Cui; Klaus-Dieter Schewe; Kuan-Chong Ting; Liangjing Yang; Mark Butala; Shurun Tan, Wee-Liat Ong; Yu Lin

Collaborators

College of Control Science & Engineering, ZJU: Chao Xu

School of Mechanical Engineering, ZJU: Tao Liu, Yong Lei

College of Biosystems Engineering and Food Science, ZJU: Tao Lin, Yibin Ying

UIUC: Elizabeth Hsiao-Wecksler, Thenkurussi “Kesh” Kesavadas, Girish Chowdhary

Postdoctoral Researchers: Santosh Kumar Singh

References

1.     G. Ren, T. Lin, Y. Ying, G. Chowdhary, K-C. Ting, “Agricultural robotics research applicable to poultry production: A review”, Computers and Electronics in Agriculture, 169, 105216, 2020

2.     G. Ren, E. B. Velasquez, T. Wu, T. Lin, Y. Ying, G. Chowdhary, K-C. Ting, “Autonomous navigation under plant canopy using an improved YOLO-based model”, in preparation

3.  L. Yang, R. Wen, J. Qin, C.-K. Chui, K.-B. Lim, and S. K. Y. Chang, "A Robotic System for Overlapping Radiofrequency Ablation in Large Tumor Treatment," Mechatronics, IEEE/ASME Transactions on, vol. 15, pp. 887-897, 2010.

4.  L. Yang, J. Wang, T. Ando, et al. "Self-contained image mapping of placental vasculature in 3D ultrasound-guided fetoscopy." Surgical Endoscopy, v 12, pp. 4136-4149, 2015

5.  L. Yang, J. Wang, T. Ando, et al. " Towards scene adaptive image correspondence for placental vasculature mosaic in computer assisted fetoscopic," International Journal of Medical Robotics and Computer Assisted Surgery, vol 12, pp. 375-386, 2016

6.  L Yang, J Wang, E Kobayashi, et al. "Image mapping of untracked free-hand endoscopic views to an ultrasound image-constructed 3D placenta model," International Journal of Medical Robotics and Computer Assisted Surgery, vol 11(2), pp. 223-234, 2015

7.  L. Yang, J. Wang, T. Ando, et al. "Vision-based endoscope tracking in 3D ultrasound image-guided fetoscopic procedures," Computerized Medical Imaging and Graphics, vol. 40, pp. 205-216, 2014

8.  L. Yang, K. Youcef-Toumi, U. Tan, “Towards Automatic Robot-Assisted Microscopy: An Uncalibrated Approach for Robotic Vision-Guided Micromanipulation,” in Intelligent Robots and System, IROS 2016, Daejeon, Korea, 2016.

9.  L. Yang, I. Paranawithana, et al., “Automatic Vision-Guided Micromanipulation for Versatile Deployment and Portable Setup”, Automation Science and Engineering, IEEE Transactions, v15 pp.1609-15, 2018 (DOI: 10.1109/TASE.2017.2754517)

10. L. Yang, K. Youcef-Toumi, U. Tan, “Detect-Focus-Track-Servo (DFTS): A Vision-Based Workflow Algorithm for Robotic Image-Guided Micromanipulation,” in Robotics and Automation, ICRA 2017, Singapore, 2017

11. L. Yang, I. Paranawithana, K. Youcef-Toumi, U. Tan, “Self-initialization and recovery for uninterrupted tracking in vision-guided micromanipulation,” in Intelligent Robots and System, IROS 2017, Vancouver, Canada, 2017

12. L. Yang, I. Paranawithana, K. Youcef-Toumi, U. Tan, “Confidence-Based Hybrid Tracking to Overcome Visual Tracking Failures in Calibration-less Vision-Guided Micromanipulation”, Automation Science and Engineering, IEEE Transactions， v 17, pp. 524-536, Jan. 2020

13.  J. Huang, X. Li, T. Kesavadas, L. Yang. “Feature Extraction of Video Data for Automatic Visual Tool Tracking in Robot Assisted Surgery”. In Proceedings of the 4th International Conference on Robotics, Control and Automation pp. 121-127, Jul. 2019.

14. T. Yang, L. Yang, J. Liu, C.-K. Chui, et. al., “Robotic Surgical Trainer for Image-guided Robot-Assisted Surgical Training” US 20130224710 A1, Date of Publication 2013

15. K. Hong, Y. Sun, J. He, Y. Lei, L. Yang, “Preliminary design of a robotic system for kinaesthetic training of surgical tasks”, The Journal of Engineering, v 14, p. 490 – 494, 2019

16. H-Y. Li, I. Paranawithana, L. Yang, et al.., “Stable and Compliant Motion of Physical Human-Robot Interaction Coupled with a Moving Environment using Variable Admittance and Adaptive Control”, IEEE Robotics and Automation Letters , v 3, pp. 2493-2500, July 2018

Center for Research On Sustainable Systems （CROSS）

i.         Key research focuses:

The Center for Research On Sustainable Systems (CROSS) is an international and interdisciplinary research platform currently under development by a group of faculty members of the ZJUI. The research focuses include both macro systems such as global ecological environment and the micro systems such as indoor environment and green buildings. The research objectives are to explore the occurrence mechanisms and loss control of natural and man-made disasters, as well as life-cycle design and operation of sustainable systems.

Current research projects are in following directions.

Research directions:  

l  Bio-based materials and structures

bio-based materials and constructions lab

The research will challenge the implementation of the ecological bio-based resources such as bamboo into modern construction, through fundamental material studies, digital design and manufacture. The goal is to contribute to reduce the growing ecological burden on the earth system due to over-development and to improve living environment.

l  Environment and urban infrastructure

The development of future transport systems for mega-cities is an opportunity to achieve many of the United Nation Sustainable Development Goals. The expansion of conventional mass-transit systems alone is not capable of keeping up with the rapid growth in demand. Moreover, it fails to provide inclusivity, as it is often not possible or convenient for the elderly or people with disabilities to use conventional public transport. Therefore, it is of strategical importance to find innovative solutions to complement traditional public transport modes.

l  Water Resource Systems Engineering

The outcome of this project is expected to improve the coordination between hydropower and all competing uses. These improvements will be the result of implementation of promising water management alternatives for reconciling those water uses, including modified operations for hydropower reservoirs that can better meet the requirements of other uses without any significant negative impact on the energy sector.

l  Health monitoring

Based on Dr Li’s research in time-domain Bayesian Operational modal analysis （OMA）, the following contents will be investigated: (1) develop a fast-variational Bayes algorithm to enhance its efficiency; (2) remove spurious modes using sparse Bayesian learning for an automated implementation; (3) extend the study to the case of multi-setup OMA of large-span bridges.

ii.         Key members

iii.         Typical research projects

CROSS Spring 2020.pdf

CROSS WINTER 2020 JOURNAL.pdf

Research Center for Ubiquitous Sensing and Intelligent Chip

泛在感知与智能芯片研究中心

Research Focus:

Information is becoming a fundamental infrastructure/support for our future world like the role of power, water, and transportation in our current world. The Ubiquitous Sensing and Intelligent Chip research center focuses on the fundamentals and frontiers of information science and engineering, such as information acquisition and perception, ubiquitous interconnection and communication, intelligent chips for beyond Moore and non-Von Neumann computing, and advanced heterogenous integration, etc. We aim to revolutionize the information science and engineering and break information barriers in other critical infrastructural systems including communication, transportation, manufacturing, computation, health care, food, water, energy, and environments, etc.

We push forward the technology advancement in the following directions:

·       Developing intelligent sensing devices, platforms, systems, and algorithms to enhance the quality of life and to support sustainable development, including but not limited to smart wave-functional materials, intelligent sensors, advanced distributed sensor networks, quantum sensing, energy efficient integrated circuits, implantable and wearable devices, super-resolution microwave and optical imaging techniques, active lidar systems, remote sensing technology for food, water, energy, environment, and space, traffic monitoring and smart cities.  

Developing techniques that enable future intelligent connectivity, mobility, and communication, including but not limited to beyond 5G wideband and ultra-high-speed communication techniques through microwave, terahertz, and quantum optics, space-borne networks, internet of things, connected vehicles, smart homes and cities, and innovative computer-brain interfaces.

·       Developing techniques that enable design and integration of neuromorphic and brain-like intelligent chip and quantum computing, including but not limited to spiking neural networks, novel architectures for cognitive computing, neuromorphic sensing, intelligent chips for healthcare, communication and sensing, power efficient digital chip design, and electromagnetic integrity and security associated with artificial intelligent chip.

·       Developing advanced heterogeneous integration technologies for complex devices, circuits and systems, including but not limited to advanced semiconductor fabrication techniques, micro-electromechanical systems, system in a package and system on a chip, high-speed interconnections, and advanced EDA tools and methods to ensure electromagnetic compatibility, security, and signal integrity.

·       Fundamental research in electromagnetics, optics, bio-electromagnetics, multi-physics, and signal processing.

Key Members: (named alphabetically)

ZJUI: Mark Butala, Wenchao Chen, Huan Hu, Simon Hu, Erping Li, Yu Lin, Shurun Tan, Aili Wang

UIUC: Peter Dragic, Jean-Pierre Leburton, Jose E. Schutt-Aine

ZJU: Hongsheng Chen, Yang Du, Wei Sha, Yang Xu

Typical Research Projects:

Ubiquitous Sensing

·       Magenetotellurics: time series analysis / transfer function estimation / system identification (NSFC) - Mark Butala

·       Solar tomography: imaging / inverse problems - Mark Butala

·       Dynamic inverse problems: detection / estimation of switching dynamic linear systems - Mark Butala

·       Efficient methods for photonic band characterization, and electromagnetic scattering from bounded periodic structures and topological photonics (NSFC) - Shurun Tan

·       Novel microwave remote sensing systems based on signal of opportunity from Global Navigational Satellite Systems for environmental observation and precision agriculture - Shurun Tan

·       UAV based traffic monitoring and sensing - Simon Hu

·       CAV based cooperative traffic management and road sensing (a funded MoST project) - Simon Hu

·       Combined CAV and UAV based sensing for smart cities - Simon Hu

Future Communication

·       5G Communication antenna design - Erping Li

·       Artificial intelligence for 5G communication and electromagnetic compatibility - Erping Li

·       Effects of random surfaces and random volumes on high-speed wireless communication links - Shurun Tan

·       Semiclassical quantum electromagnetics model for nanoantennas (NSFC) - Wei Sha

Intelligent Chip

·       Artificial intelligence spiking neuromorphic chip and its associated electromagnetic integrity - Erping Li

Advanced Integration

·       Multiphysics processes and ultrafast response mechanisms in ballistic avalanche heterojunction (NSFC) - Wenchao Chen

Center for Research On Sustainable Systems （CROSS）

i.         Key research focuses:

The Center for Research On Sustainable Systems (CROSS) is an international and interdisciplinary research platform currently under development by a group of faculty members of the ZJUI. The research focuses include both macro systems such as global ecological environment and the micro systems such as indoor environment and green buildings. The research objectives are to explore the occurrence mechanisms and loss control of natural and man-made disasters, as well as life-cycle design and operation of sustainable systems.

Current research projects are in following directions.

Research directions:  

l  Bio-based materials and structures

bio-based materials and constructions lab

The research will challenge the implementation of the ecological bio-based resources such as bamboo into modern construction, through fundamental material studies, digital design and manufacture. The goal is to contribute to reduce the growing ecological burden on the earth system due to over-development and to improve living environment.

l  Environment and urban infrastructure

The development of future transport systems for mega-cities is an opportunity to achieve many of the United Nation Sustainable Development Goals. The expansion of conventional mass-transit systems alone is not capable of keeping up with the rapid growth in demand. Moreover, it fails to provide inclusivity, as it is often not possible or convenient for the elderly or people with disabilities to use conventional public transport. Therefore, it is of strategical importance to find innovative solutions to complement traditional public transport modes.

l  Water Resource Systems Engineering

The outcome of this project is expected to improve the coordination between hydropower and all competing uses. These improvements will be the result of implementation of promising water management alternatives for reconciling those water uses, including modified operations for hydropower reservoirs that can better meet the requirements of other uses without any significant negative impact on the energy sector.

l  Health monitoring

Based on Dr Li’s research in time-domain Bayesian Operational modal analysis （OMA）, the following contents will be investigated: (1) develop a fast-variational Bayes algorithm to enhance its efficiency; (2) remove spurious modes using sparse Bayesian learning for an automated implementation; (3) extend the study to the case of multi-setup OMA of large-span bridges.

ii.         Key members

iii.         Typical research projects

CROSS Spring 2020.pdf