Background: Many minimally invasive surgical procedures and assisting robotic systems have been developed to further minimize the number and size of incisions in the body surface. This paper presents a new idea combining the advantages of modular robotic surgery, single incision laparoscopic surgery and needlescopic surgery.
Material And Methods: In the proposed concept, modules carrying therapeutic or diagnostic tools are inserted in the abdominal cavity from the navel as in single incision laparoscopic surgery and assembled to 3-mm needle shafts penetrating the abdominal wall.
Results: A three degree-of-freedom robotic module measuring 16 mm in diameter and 51 mm in length was designed and prototyped. The performance of the three connected robotic modules was evaluated.
Conclusion: A new idea of modular robotic surgery was proposed, and demonstrated by prototyping a 3-DOF robotic module. The performance of the connected robotic modules was evaluated, and the challenges and future work were summarized.
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http://dx.doi.org/10.1080/13645706.2017.1288634 | DOI Listing |
Sensors (Basel)
January 2025
School of Automation, Southeast University, Nanjing 210096, China.
Transferring knowledge learned from standard GelSight sensors to other visuotactile sensors is appealing for reducing data collection and annotation. However, such cross-sensor transfer is challenging due to the differences between sensors in internal light sources, imaging effects, and elastomer properties. By understanding the data collected from each type of visuotactile sensors as domains, we propose a few-sample-driven style-to-content unsupervised domain adaptation method to reduce cross-sensor domain gaps.
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December 2024
Key Laboratory of Optoelectronic Technology and Systems of the Education Ministry of China, Chongqing University, Chongqing 400044, China.
Six degrees of freedom (6-DoF) object pose estimation is essential for robotic grasping and autonomous driving. While estimating pose from a single RGB image is highly desirable for real-world applications, it presents significant challenges. Many approaches incorporate supplementary information, such as depth data, to derive valuable geometric characteristics.
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December 2024
Institute of Mechanical Technology, Poznan University of Technology, 60-965 Poznan, Poland.
This article presents the fundamental principles of robot accuracy. It characterizes a modular robot, describes the measurement setup, and outlines the methodology for evaluating positioning accuracy across different configurations of the modular robot (four, five, and six modules) under varying loads of 6, 10, and 16 kg. An analysis was conducted on the impact of load changes on four- and five-module configurations, as well as the effect of configuration changes on the robot's performance with 6 and 10 kg loads.
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December 2024
School of Information Science and Engineering, Zhejiang Sci-Tech University, Hangzhou 310018, China.
Accurate detection and tracking of dynamic objects are critical for enabling skill demonstration and effective skill generalization in robotic skill learning and application scenarios. To further improve the detection accuracy and tracking speed of the YOLOv8s model in dynamic object tracking tasks, this paper proposes a method to enhance both detection precision and speed based on YOLOv8s architecture. Specifically, a Focused Linear Attention mechanism is introduced into the YOLOv8s backbone network to enhance dynamic object detection accuracy, while the Ghost module is incorporated into the neck network to improve the model's tracking speed for dynamic objects.
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December 2024
State Grid Tianjin Electric Power Research Institute, Tianjin 300180, China.
Large oil-immersed transformers have metal-enclosed shells, making it difficult to visually inspect the internal insulation condition. Visual inspection of internal defects is carried out using a self-developed micro-robot in this work. Carbon trace is the main visual characteristic of internal insulation defects.
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