Current Issue : October-December Volume : 2025 Issue Number : 4 Articles : 5 Articles
Variable stiffness actuators (VSAs) have attracted considerable attention in wearable robotics and soft exoskeletons due to their ability to adapt to various load conditions. This study presents a modular design for VSAs that incorporates a chain mail structure with various link topologies, allowing for a reconfiguration of stiffness. The proposed VSA consists of three main parts: the vacuum chamber, the VSA actuator, and the chain mail structure. The VSA fabrication process was carried out in five stages: (1) mold fabrication by 3D FDM printing, incorporating a film of oil to facilitate easy demolding; (2) mold preparation using silicone, with a precise ratio of 1:1 weight-based mixture to optimize material utilization; (3) silicone pouring into molds while applying vibration to eliminate air bubbles; (4) curing for four hours to achieve optimal mechanical properties; and (5) careful demolding to prevent damage. Experimental tests were conducted to characterize the stiffness of actuators with different chain mail fabric configurations, using an experimental setup designed to securely fix the actuator and accurately measure the pneumatic pressure and the angle of deformation after applying weights at its end. The European 6-in-1 and rounded square configurations were shown to be the most effective, increasing stiffness up to 382% compared to the chain mail-free configuration, highlighting the positive impact of these structural designs....
This paper discusses the issue of the self-heating effect of resistance sensors during temperature measurement. The self-heating effect causes temperature measurement errors. The aim of this work was to develop a method for in situ assessment of the thermal resistance between a self-heating thermometer and its surrounding environment, the temperature of which is measured. The proposed method is used to assess the uncertainty resulting from the heat transfer from the thermometer to the surrounding environment, which allows increased measurement accuracy. The proposed method consists of experimental determination of the sensor’s temperature characteristics in relation to the heating power for different values of the measuring current. Sample measurements were carried out on a representative group of resistance temperature sensors. The relationship of the internal thermal resistance to the type of sensor design and the relationship of the external resistance to the ambient conditions were demonstrated. The developed method allows the appropriate measuring current of the resistance temperature sensor to be selected according to its design, the mounting method, and the environmental conditions, which ensures that measurement errors are maintained at an appropriately low level....
The development of an intelligent ultrasonic aspirator controlled by a fiberoptic neoplasm sensor that detects 5-aminolevulinic acid-derived porphyrin fluorescence presents a significant advancement in glioma surgery. By leveraging the fluorescence phenomenon associated with 5-aminolevulinic acid in malignant neoplasms, this device integrates an excitation laser and a high-sensitivity photodiode into the tip of an ultrasonic aspirator handpiece. This setup allows for real-time tumor fluorescence detection, which in turn modulates the aspirator’s power based on fluorescence intensity. Preliminary testing demonstrated high sensitivity, with the device capable of differentiating between weak, strong, and no fluorescence. The sensor sensitivity was comparable to human visual perception, enabling effective tumor differentiation. Tumors with strong fluorescence were effectively crushed, while the aspirator ceased operation in non-fluorescent areas, enabling precise tissue resection. Furthermore, the device functioned efficiently in bright surgical environments and was designed to maintain a clean sensor tip through constant saline irrigation. The system was successfully applied in a surgical case of recurrent glioblastoma, selectively removing tumor tissue while preserving surrounding brain tissue. This innovative approach shows promise for safer, more efficient glioma surgeries and may pave the way for sensor-based robotic surgical systems integrated with navigation technologies....
The structural deformations induced by rocket launch vibrations, on-orbit thermal gradients, and gravitation fluctuations can lead to significant deployment errors for largeaperture, segmented space telescopes. As the size and number of segments increase in future telescopes, the optical-based methods for detecting deployment errors suffer from the range limitations of the millimeter scale and time-consuming processes of the month scale. To address this, we propose a new method for rapid-deployment error detection based on long-range, high-precision capacitive edge sensors. These sensors feature a measurement range of ±13 mm, with a precision better than 7.3 nm, enabling efficient and simultaneous error detection across all segments. This approach significantly reduces the time and steps required compared to traditional optical methods. Through experimental validation, the designed system demonstrated the ability to detect and correct large deployment errors and maintain co-phasing precision, meeting the stringent requirements for future space telescopes. The proposed sensor system enhances deployment efficiency, offering a viable solution for the next generation of segmented space telescopes....
Given the growth of unmanned aerial vehicles (UAVs), their detection has become a recent and complex problem. The literature has addressed this problem by applying traditional computer vision algorithms and, more recently, deep learning architectures, which, while proven more effective than previous ones, are computationally more expensive. In this paper, following the approach of applying deep learning architectures, we propose a simplified LSL-Net-based architecture for UAV detection. This architecture integrates the ability to track and detect UAVs using convolutional neural networks. The biggest challenge lies in creating a model that allows us to obtain good results without requiring considerable computational resources. To address this problem, we built on a recent successful LSL-Net architecture. We introduce a simplified LSL-Net architecture using dilated convolutions to achieve a lower-cost architecture with good detection capabilities. Experiments demonstrate that our architecture performs well with limited resources, reaching 98% accuracy in detecting UAVs....
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