Research Projects
Currently, our research on enabling technologies includes sensors and actuators inspired by biological principles. Experimental applications include medical soft robots, and specifically assistive soft arms for eldercare, as well as robots for monitoring the marine ecosystem. This research relies on multidisciplinary expertise in mechanical design, fabrication technologies, modelling and control.
1. Bioinspired soft robotics
DESTRO - Dextrous, strong yet soft robots
An ITALY – SINGAPORE SCIENCE AND TECHNOLOGY COOPERATION aimed at studying muscular hydrostats. Muscular hydrostats work inside (e.g., octopus arms) and outside (e.g., elephant trunks) water, but nature evolved different muscular structures for the different environments. This project aims to comparatively unveil the key principles of muscular hydrostats, for robotics purposes. We include biological studies and advanced modeling techniques, and we rely on the soft robotics technologies and materials available at the institutions in Singapore and Italy for comparatively testing robotic muscular hydrostats. A soft arm prototype will be used for a joint study on its use, taking advantage of a teleoperation platform available in Singapore. Thanks to the expertise of teams in Italy and Singapore on related neuroscience, the study will focus on how a human brain can control a soft arm with completely different shape and dexterity.
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Project Timeline
Start Date: 7/1/2023
End Date: 6/30/2026
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People
Cecilia LASCHI
Yiyuan ZHANG
Yuchen SUN
Linxin HOU
QIN Zhihang
Adamya Singh DHAKER
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Huishi HUANG
Ng Hong Wei
Sharun Arumugam
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Funding Agencies
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Publications
Wang, Peiyi, Zhexin Xie, Wenci Xin, Zhiqiang Tang, Xinhua Yang, Muralidharan Mohanakrishnan, Sheng Guo, and Cecilia Laschi. “Sensing Expectation Enables Simultaneous Proprioception and Contact Detection in an Intelligent Soft Continuum Robot.” Nature Communications 15, no. 1 (2024): 9978.
REBOT - Rethinking underwater robot manipulation:
REBOT aims to demonstrate that octopus-inspired strategies are more efficient for manipulation in water. We aim at first demonstrating it mathematically, with models and simulations. Then we test our findings ecperimentally with an octopus-inspired soft robot arm.Our results can bring a revolutionary impact on underwater robotics, by providing efficient and effective grasping strategies that can increase underwater robot adoption.Possible applications span from off-shore industry to biology and oceanography.
Project Timeline
Start Date: 8/1/2022
End Date: 7/31/2025
People
Cecilia LASCHI
Yiyuan ZHANG
Yuchen SUN
Linxin HOU
QIN Zhihang
Adamya Singh DHAKER
Ng Hong Wei
Sharun Arumugam
Funding Agency
Funded by Singapore Ministry of Education (MOE), Tier 2 Grant.
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Grant Number:
Moe-t2eP50221-0010
Publications
Wang, Peiyi, Zhexin Xie, Wenci Xin, Zhiqiang Tang, Xinhua Yang, Muralidharan Mohanakrishnan, Sheng Guo, and Cecilia Laschi. “Sensing Expectation Enables Simultaneous Proprioception and Contact Detection in an Intelligent Soft Continuum Robot.” Nature Communications 15, no. 1 (2024): 9978.
Mengaldo, Gianmarco, Federico Renda, Steven L. Brunton, Moritz Bächer, Marcello Calisti, Christian Duriez, Gregory S. Chirikjian, and Cecilia Laschi. “A Concise Guide to Modelling the Physics of Embodied Intelligence in Soft Robotics.” Nature Reviews Physics 4, no. 9 (2022)
Tan, Yu Jun, Gianmarco Mengaldo, and Cecilia Laschi. “Artificial Muscles for Underwater Soft Robots: Materials and Their Interactions.” Annual Review of Condensed Matter Physics 15, no. Volume 15, 2024 (2024)
Xie, Zhexin, Feiyang Yuan, Jiaqi Liu, Lufeng Tian, Bohan Chen, Zhongqiang Fu, Sizhe Mao, et al. “Octopus-Inspired Sensorized Soft Arm for Environmental Interaction.” Science Robotics 8, no. 84 (2023): eadh7852.
RoboLife – Soft robots with morphological adaptation and life-like abilities:
We take a bioinspired approach to investigate abilities that robots do not have yet, leveraging on the potential of soft robotics technologies. We mostly address marine species and the benthic area, to create robots with different locomotion patterns, new forms of grasping and manipulation, shape adaptation. They have potential to accomplish diverse tasks of exploration of benthic areas and intervention in industrial plants, e.g., monitoring, sampling, maintenance, others.
Project Timeline
Start Date: 4/1/2021
End Date: 3/31/2025
People
Cecilia LASCHI
WANG Peiyi
Wenci XIN
KAN Longxin
Huishi HUANG
Yuanyuan LI
KOH Hui Fang
Muhammad Sunny Nazeer
Matteo Lo Preti
Funding Agency
Publications
Wang, Peiyi, Zhexin Xie, Wenci Xin, Zhiqiang Tang, Xinhua Yang, Muralidharan Mohanakrishnan, Sheng Guo, and Cecilia Laschi. “Sensing Expectation Enables Simultaneous Proprioception and Contact Detection in an Intelligent Soft Continuum Robot.” Nature Communications 15, no. 1 (2024): 9978.
Laschi, Cecilia. “The Physics of Interactions in Soft Robotics.” In APS March Meeting Abstracts, 2022:K03-001, 2022.
Mengaldo, Gianmarco, Federico Renda, Steven L. Brunton, Moritz Bächer, Marcello Calisti, Christian Duriez, Gregory S. Chirikjian, and Cecilia Laschi. “A Concise Guide to Modelling the Physics of Embodied Intelligence in Soft Robotics.” Nature Reviews Physics 4, no. 9 (2022): 595–610.
Tan, Yu Jun, Gianmarco Mengaldo, and Cecilia Laschi. “Artificial Muscles for Underwater Soft Robots: Materials and Their Interactions.” Annual Review of Condensed Matter Physics 15, no. Volume 15, 2024 (2024): 45–61.
Xie, Zhexin, Feiyang Yuan, Jiaqi Liu, Lufeng Tian, Bohan Chen, Zhongqiang Fu, Sizhe Mao, et al. “Octopus-Inspired Sensorized Soft Arm for Environmental Interaction.” Science Robotics 8, no. 84 (2023): eadh7852.
Xin, Wenci, Fangmeng Zhu, Peiyi Wang, Zhexin Xie, Zhiqiang Tang, and Cecilia Laschi. “Electrical Impedance Tomographic Shape Sensing for Soft Robots.” IEEE Robotics and Automation Letters 8, no. 3 (2023): 1555–62.
2. Assistive soft robotics
CARTIN - Center for Advanced Robotics Technology Innovation
An NRF Medium-Size Center, established in March 2021 and funded for 5 years.At NUS, we investigate robots for eldercare and the Soft Robotics Lab contributes with assistive soft robots designed after our users' need.
At NUS, we aim at answering the following question: Can robots help with the growing need for assistance to our ageing citizens? We believe that assistive robots can help seniors have a longer active life. We adopt a user-centred design (UCD) approach to ensure that we respond to the needs of elderly and caregivers, and ultimately promote a wide adoption of robots.
Read more about CARTIN ->
Project Timeline
Start Date: 3/30/2021
End Date: 3/29/2026
People
Cecilia LASCHI
Muralidharan Mohanakrishnan
Zhexin XIE
Zhiqiang TANG
LI Keyi
Elham Azadfar
Funding Agency
Publications
Wang, Peiyi, Zhexin Xie, Wenci Xin, Zhiqiang Tang, Xinhua Yang, Muralidharan Mohanakrishnan, Sheng Guo, and Cecilia Laschi. “Sensing Expectation Enables Simultaneous Proprioception and Contact Detection in an Intelligent Soft Continuum Robot.” Nature Communications 15, no. 1 (2024): 9978.
Mengaldo, Gianmarco, Federico Renda, Steven L. Brunton, Moritz Bächer, Marcello Calisti, Christian Duriez, Gregory S. Chirikjian, and Cecilia Laschi. “A Concise Guide to Modelling the Physics of Embodied Intelligence in Soft Robotics.” Nature Reviews Physics 4, no. 9 (2022): 595–610.
Tang, Zhiqiang, Peiyi Wang, Wenci Xin, and Cecilia Laschi. “Learning-Based Approach for a Soft Assistive Robotic Arm to Achieve Simultaneous Position and Force Control.” IEEE Robotics and Automation Letters 7, no. 3 (2022): 8315–22.
Tang, Zhiqiang, Peiyi Wang, Wenci Xin, Zhexin Xie, Longxin Kan, Muralidharan Mohanakrishnan, and Cecilia Laschi. “Meta-Learning-Based Optimal Control for Soft Robotic Manipulators to Interact with Unknown Environments.” In 2023 IEEE International Conference on Robotics and Automation (ICRA), 982–88. London, United Kingdom: IEEE, 2023.
Tang, Zhiqiang, Wenci Xin, Peiyi Wang, and Cecilia Laschi. “Learning-Based Control for Soft Robot–Environment Interaction with Force/Position Tracking Capability.” Soft Robotics, February 20, 2024.
Wang, Peiyi, Zhiqiang Tang, Wenci Xin, Zhexin Xie, Sheng Guo, and Cecilia Laschi. “Design and Experimental Characterization of a Push-Pull Flexible Rod-Driven Soft-Bodied Robot.” IEEE Robotics and Automation Letters 7, no. 4 (2022): 8933–40.
Xie, Zhexin, Muralidharan Mohanakrishnan, Peiyi Wang, Jiaqi Liu, Wenci Xin, Zhiqiang Tang, Li Wen, and Cecilia Laschi. “Soft Robotic Arm With Extensible Stiffening Layer.” IEEE Robotics and Automation Letters 8, no. 6 (2023): 3597–3604.
Xin, Wenci, Fangmeng Zhu, Peiyi Wang, Zhexin Xie, Zhiqiang Tang, and Cecilia Laschi. “Electrical Impedance Tomographic Shape Sensing for Soft Robots.” IEEE Robotics and Automation Letters 8, no. 3 (2023): 1555–62.
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Collaborators
M3S - Mens, Manus and Machina
An interdisciplinary program of SMART, MIT’s research enterprise in Singapore, aimed to study the introduction of AI and robots in the society. The research at M3S addresses critical questions concerning the design of technology, the development of human skills, and the adaptation of institutions and social structures to effectively navigate the transformative impact of AI, automation, and robotics.
About M3S | SMART| Singapore (mit.edu)
Project Timeline
Start Date: 7/1/2023
End Date: 6/30/2028
Funding Agencies
Soft and Hybrid Phase 2a (complete)
Project Timeline
Start Date: 1/7/2021
End Date: 31/10/2022
People
Cecilia LASCHI
Zhiqiang TANG
Wenci XIN
WANG Peiyi
Funding Agency
Publications
Tang, Zhiqiang, Peiyi Wang, Wenci Xin, and Cecilia Laschi. “Learning-Based Approach for a Soft Assistive Robotic Arm to Achieve Simultaneous Position and Force Control.” IEEE Robotics and Automation Letters 7, no. 3 (July 2022): 8315–22.
Tang, Zhiqiang, Peiyi Wang, Wenci Xin, Zhexin Xie, Longxin Kan, Muralidharan Mohanakrishnan, and Cecilia Laschi. “Meta-Learning-Based Optimal Control for Soft Robotic Manipulators to Interact with Unknown Environments.” In 2023 IEEE International Conference on Robotics and Automation (ICRA), 982–88. London, United Kingdom: IEEE, 2023.
Tang, Zhiqiang, Wenci Xin, Peiyi Wang, and Cecilia Laschi. “Learning-Based Control for Soft Robot–Environment Interaction with Force/Position Tracking Capability.” Soft Robotics, February 20, 2024.
Xin, Wenci, Fangmeng Zhu, Peiyi Wang, Zhexin Xie, Zhiqiang Tang, and Cecilia Laschi. “Electrical Impedance Tomographic Shape Sensing for Soft Robots.” IEEE Robotics and Automation Letters 8, no. 3 (March 2023): 1555–62.
