Bending soft robots must be structured and predictable to be used in applications such as a grasping hand. We developed soft robot fingers with embedded bones to improve the performance of a puppetry robot with haptic feedback. The manufacturing process for bone-inspired soft robots is described, and two mathematical models are reported: one to predict the stiffness and natural frequency of the robot finger and the other for trajectory planning. Experiments using different prototypes were used to set model parameters. The first model, which had a fourth-order lumped mass-spring-damper configuration, was able to predict the natural frequency of the soft robot with a maximum error of 18%. The model and the experimental data demonstrated that bone-inspired soft robots have higher natural frequency, lower phase shift, better controllability, and higher stiffness compared with traditional fiber-reinforced bending soft robots. We also showed that the dynamic performance of a bending soft robot is independent of whether water or air is used for the media and independent of the media pressure. Results from the second model showed that the path of a bone-inspired soft robot is a function of the relative lengths of the bone segments, which means that the model can be used to direct the design of the robot to achieve the desired trajectory. This model was able to correctly predict the trajectory path of the robot.
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http://dx.doi.org/10.1089/soro.2019.0183 | DOI Listing |
Bioinspir Biomim
January 2025
Inner Mongolia University, Department of Information Engineering, Ordos Institute of Applied Technology, Ordos 017000, China, Hohhot, 010021, CHINA.
Soft robots are usually manufactured using the pouring method and can only be configured with a fixed execution area, which often faces the problem of insufficient or wasteful performance in real-world applications, and cannot be reused for other tasks. In order to overcome this limitation, we propose a simple and controllable rather than redesigned method inspired by the bionic growth behavior of plants, and prepare bionic soft robots that can just meet the requirements of use, and transform biological intelligence into mechanical intelligence. Based on finite element method, we establish a theoretical model of soft robot performance.
View Article and Find Full Text PDFJ Robot Surg
January 2025
Pôle Santé Sud, Le Mans, France.
Pancreaticojejunostomy (PJ) is a critical step in pancreaticoduodenectomy (PD), often complicated by the risk of postoperative pancreatic fistula (POPF). This video report demonstrates a novel robotic PJ technique employing a self-expandable metallic stent. The method involves the use of the Da Vinci Xi robotic system and the WallFlex™ Biliary RX Stent for improved anastomotic support, particularly in high-risk cases defined by soft pancreatic texture and narrow duct diameter (<3 mm).
View Article and Find Full Text PDFGels
December 2024
Department of Mechanics and Engineering Science, School of Physics, Nanjing University of Science and Technology, Nanjing 210094, China.
Magnetic hydrogel soft robots have shown great potential in various fields. However, their contact dynamic behaviors are complex, considering stick-slip motion at the contact interface, and lack accurate computational models to analyze them. This paper improves the numerical computational method for hydrogel materials with magneto-mechanical coupling effect, analyses the inchworm-like contact motion of the biomimetic bipedal magnetic hydrogel soft robot, and designs and optimizes the robot's structure.
View Article and Find Full Text PDFBiomimetics (Basel)
January 2025
Group of Biomechatronics, Fachgebiet Biomechatronik, Technische Universität Ilmenau, D-98693 Ilmenau, Germany.
Anguilliform locomotion, an efficient aquatic locomotion mode where the whole body is engaged in fluid-body interaction, contains sophisticated physics. We hypothesized that data-driven modeling techniques may extract models or patterns of the swimmers' dynamics without implicitly measuring the hydrodynamic variables. This work proposes empirical kinematic control and data-driven modeling of a soft swimming robot.
View Article and Find Full Text PDFBiomimetics (Basel)
January 2025
Key Laboratory of Mechanism Theory and Equipment Design, Ministry of Education, Tianjin University, Tianjin 300072, China.
This paper presents a novel soft crawling robot controlled by gesture recognition, aimed at enhancing the operability and adaptability of soft robots through natural human-computer interactions. The Leap Motion sensor is employed to capture hand gesture data, and Unreal Engine is used for gesture recognition. Using the UE4Duino, gesture semantics are transmitted to an Arduino control system, enabling direct control over the robot's movements.
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