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Jiang Y, Li Y, Tong X, Wang Z, Zhou Y, He B. Robotic flytrap with an ultra-sensitive 'trichome' and fast-response 'lobes'. BIOINSPIRATION & BIOMIMETICS 2024; 19:056017. [PMID: 39094623 DOI: 10.1088/1748-3190/ad6abf] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/05/2024] [Accepted: 08/01/2024] [Indexed: 08/04/2024]
Abstract
Nature abounds with examples of ultra-sensitive perception and agile body transformation for highly efficient predation as well as extraordinary adaptation to complex environments. Flytraps, as a representative example, could effectively detect the most minute physical stimulation of insects and respond instantly, inspiring numerous robotic designs and applications. However, current robotic flytraps face challenges in reproducing the ultra-sensitive insect-touch perception. In addition, fast and fully-covered capture of live insects with robotic flytraps remains elusive. Here we report a novel design of a robotic flytrap with an ultra-sensitive 'trichome' and bistable fast-response 'lobes'. Our results show that the 'trichome' of the proposed robotic flytrap could detect and respond to both the external stimulation of 0.45 mN and a tiny touch of a flying bee with a weight of 0.12 g. Besides, once the 'trichome' is triggered, the bistable 'lobes' could instantly close themselves in 0.2 s to form a fully-covered cage to trap the bees, and reopen to set them free after the tests. We introduce the design, modeling, optimization, and verification of the robotic flytrap, and envision broader applications of this technology in ultra-sensitive perception, fast-response grasping, and biomedical engineering studies.
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Affiliation(s)
- Yongkang Jiang
- College of Electronic and Information Engineering, Tongji University, Shanghai 201804, People's Republic of China
- National Key Laboratory of Autonomous Intelligent Unmanned Systems, Tongji University, Shanghai 201804, People's Republic of China
- Frontiers Science Center for Intelligent Autonomous Systems, Shanghai 201210, People's Republic of China
| | - Yingtian Li
- Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, People's Republic of China
| | - Xin Tong
- Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, People's Republic of China
| | - Zhipeng Wang
- College of Electronic and Information Engineering, Tongji University, Shanghai 201804, People's Republic of China
- National Key Laboratory of Autonomous Intelligent Unmanned Systems, Tongji University, Shanghai 201804, People's Republic of China
- Frontiers Science Center for Intelligent Autonomous Systems, Shanghai 201210, People's Republic of China
| | - Yanmin Zhou
- College of Electronic and Information Engineering, Tongji University, Shanghai 201804, People's Republic of China
- National Key Laboratory of Autonomous Intelligent Unmanned Systems, Tongji University, Shanghai 201804, People's Republic of China
- Frontiers Science Center for Intelligent Autonomous Systems, Shanghai 201210, People's Republic of China
| | - Bin He
- College of Electronic and Information Engineering, Tongji University, Shanghai 201804, People's Republic of China
- National Key Laboratory of Autonomous Intelligent Unmanned Systems, Tongji University, Shanghai 201804, People's Republic of China
- Frontiers Science Center for Intelligent Autonomous Systems, Shanghai 201210, People's Republic of China
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Huang Z, Gunderman AL, Wilcox SE, Sengupta S, Shah J, Lu A, Woodrum D, Chen Y. Body-Mounted MR-Conditional Robot for Minimally Invasive Liver Intervention. Ann Biomed Eng 2024; 52:2065-2075. [PMID: 38634953 DOI: 10.1007/s10439-024-03503-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2023] [Accepted: 03/25/2024] [Indexed: 04/19/2024]
Abstract
MR-guided microwave ablation (MWA) has proven effective in treating hepatocellular carcinoma (HCC) with small-sized tumors, but the state-of-the-art technique suffers from sub-optimal workflow due to the limited accuracy provided by the manual needle insertions. This paper presents a compact body-mounted MR-conditional robot that can operate in closed-bore MR scanners for accurate needle guidance. The robotic platform consists of two stacked Cartesian XY stages, each with two degrees of freedom, that facilitate needle insertion pose control. The robot is actuated using 3D-printed pneumatic turbines with MR-conditional bevel gear transmission systems. Pneumatic valves and control mechatronics are located inside the MRI control room and are connected to the robot with pneumatic transmission lines and optical fibers. Free-space experiments indicated robot-assisted needle insertion error of 2.6 ± 1.3 mm at an insertion depth of 80 mm. The MR-guided phantom studies were conducted to verify the MR-conditionality and targeting performance of the robot. Future work will focus on the system optimization and validations in animal trials.
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Affiliation(s)
- Zhefeng Huang
- Institute of Robotics and Intelligent Machines, Georgia Institute of Technology, 801 Atlantic Dr NW, Atlanta, GA, 30332, USA
| | - Anthony L Gunderman
- Institute of Robotics and Intelligent Machines, Georgia Institute of Technology, 801 Atlantic Dr NW, Atlanta, GA, 30332, USA
| | - Samuel E Wilcox
- Institute of Robotics and Intelligent Machines, Georgia Institute of Technology, 801 Atlantic Dr NW, Atlanta, GA, 30332, USA
| | - Saikat Sengupta
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, 1161 21st Ave South Medical Center North, Nashville, TN, 37232, USA
| | - Jay Shah
- Department of Radiology, Emory University, 1364 Clifton Rd, Atlanta, GA, 30329, USA
| | - Aiming Lu
- Department of Radiology, Mayo Clinic, 200 1st St SW, Rochester, MN, 55905, USA
| | - David Woodrum
- Department of Radiology, Mayo Clinic, 200 1st St SW, Rochester, MN, 55905, USA
| | - Yue Chen
- Institute of Robotics and Intelligent Machines, Georgia Institute of Technology, 801 Atlantic Dr NW, Atlanta, GA, 30332, USA.
- Department of Biomedical Engineering, Georgia Institute of Technology/Emory University, 313 Ferst Dr, Atlanta, GA, 30332, USA.
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Wang Y, Hrovat M, Kolandaivelu A, Gunderman AL, Halperin HR, Schmidt EJ, Chen Y. MR-Safe Cartesian Platform for Active Cardiac Shimming: Preliminary Validation. IEEE Trans Biomed Eng 2024; 71:2131-2142. [PMID: 38315598 PMCID: PMC11246563 DOI: 10.1109/tbme.2024.3362295] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2024]
Abstract
OBJECTIVE Implanted Cardioverter Defibrillators (ICDs) induce a large (100 parts per million) inhomogeneous magnetic field in the magnetic resonance imaging (MRI) scanner which cannot be corrected by the scanner's built-in shim coils, leading to significant image artifacts that can make portions of the heart unreadable. To compensate for the field inhomogeneity, an active shim coil capable of countering the field deviation in user-defined regions was designed that must be optimally placed at patient-specific locations. We aim to develop and evaluate an MR-safe robotic solution for automated shim coil positioning. METHODS We designed and fabricated an MR-safe Cartesian platform that holds the shim coil inside the scanner. The platform consists of three lead screw stages actuated by pneumatic motors, achieving decoupled translations of 140 mm in each direction. The platform is made of plastics and fiberglass with the control electronics placed outside the scanner room, ensuring MR safety. Mechanical modeling was derived to provide design specifications. RESULTS Experiments show that the platform achieves less than 2 mm average motion error and 0.5 mm repeatability in all directions, and reduces the adjustment time from 5 min to a few seconds. Phantom and animal trials were conducted, showing that the proposed system is able to position a heavy shim coil ( kg) for improved ICD artifact suppression. CONCLUSION This robotic platform provides an effective method for reliable shim coil positioning inside the scanner. SIGNIFICANCE This work contributes to improving cardiac MRI quality that could facilitate accurate diagnosis and treatment planning for patients with implanted ICDs.
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Gunderman AL, Sengupta S, Huang Z, Sigounas D, Oluigbo C, Godage IS, Cleary K, Chen Y. Towards MR-Guided Robotic Intracerebral Hemorrhage Evacuation: Aiming Device Design and ex vivo Ovine Head Trial. IEEE TRANSACTIONS ON MEDICAL ROBOTICS AND BIONICS 2024; 6:577-588. [PMID: 38911181 PMCID: PMC11189651 DOI: 10.1109/tmrb.2024.3385794] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/25/2024]
Abstract
Stereotactic neurosurgery is a well-established surgical technique for navigation and guidance during treatment of intracranial pathologies. Intracerebral hemorrhage (ICH) is an example of various neurosurgical conditions that can benefit from stereotactic neurosurgery. As a part of our ongoing work toward real-time MR-guided ICH evacuation, we aim to address an unmet clinical need for a skull-mounted frameless stereotactic aiming device that can be used with minimally invasive robotic systems for MR-guided interventions. In this paper, we present NICE-Aiming, a Neurosurgical, Interventional, Configurable device for Effective-Aiming in MR-guided robotic neurosurgical interventions. A kinematic model was developed and the system was used with a concentric tube robot (CTR) for ICH evacuation in (i) a skull phantom and (ii) in the first ever reported ex vivo CTR ICH evacuation using an ex vivo ovine head. The NICE-Aiming prototype provided a tip accuracy of 1.41±0.35 mm in free-space. In the MR-guided gel phantom experiment, the targeting accuracy was 2.07±0.42 mm and the residual hematoma volume was 12.87 mL (24.32% of the original volume). In the MR-guided ex vivo ovine head experiment, the targeting accuracy was 2.48±0.48 mm and the residual hematoma volume was 1.42 mL (25.08% of the original volume).
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Affiliation(s)
- Anthony L Gunderman
- Department of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA 30338 USA
| | - Saikat Sengupta
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN 37232 USA
| | - Zhefeng Huang
- Department of Mechanical Engineering, Georgia Institute of Technology, Atlanta, GA 30338 USA
| | - Dimitri Sigounas
- The George Washington University School of Medicine and Health Sciences, Department of Neurosurgery, The George Washington University, Washington, DC, US
| | - Chima Oluigbo
- Sheikh Zayed Institute for Pediatric Surgical Innovation, Children's National Hospital, Washington, DC 20010 USA
| | - Isuru S Godage
- Department of Engineering Technology and Industrial Distribution, Texas A&M University, College Station, TX, USA
| | - Kevin Cleary
- Sheikh Zayed Institute for Pediatric Surgical Innovation, Children's National Hospital, Washington, DC 20010 USA
| | - Yue Chen
- Biomedical Engineering Department, Georgia Institute of Technology/Emory, Atlanta 30338 USA
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