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We introduce a novel 3 degrees-of-freedom based robotic colonoscopy system that performs the necessary movements for colonoscopy while working within the movement range of a flexible colonoscope (FC). In addition, we have developed deep learning models to generate motor control signals directly from input images without the need for motor control signal labels. The first presented model comprises a deep learning algorithm for predicting steering points and an image-based visual servo control (IBVS) algorithm for generating the motor control signal. The experiments showed that the proposed model’s cecal intubation time (CIT) and rate (CIR) are comparable to those of human operators, despite requiring a shorter training time. Furthermore, we propose a model that replaces the IBVS algorithm with a deep learning algorithm that does not rely on rotation angles. The second model showed similar CIT (165s) and CIR (92%) compared to the first model. Finally, the last model, which solely comprises a single deep learning algorithm, demonstrates a reduction in CIT (127s) and an increase in CIR (96%), resulting in reduced physical demand for operators, improved safety, and shorter patient recovery time.

Over the last decade, large-scale antennas have been developed to enhance precise blue force tracking and improve situational awareness. In general, such large-scale antennas, ranging from 1 to up to 10 m, need a specific mechanism that can reconfigure their shapes and morphologies, resulting in stowing and deploying upon the given environment. In parallel, it must be noted that such deployable mechanisms should accommodate a large aperture diameter while ensuring they are lightweight, robust, and structurally rigid to avoid undesired deformations due to the deployment. With these in mind, this work presents a large frustum-shaped deployable antenna mechanism with a large aperture diameter of 7.5 m. The deployable mechanism is composed of hierarchical bayes the radial direction at 30° intervals. Twelve bayes in total identify the overall morphology of the deployable antenna, which features a dodecagon. Specifically, the bay is composed of three linkage structures: a six-bar linkage mechanism, a V-folding mechanism, and a single pantograph mechanism. As a result of static and dynamic simulations, it is identified that the mechanism achieves an area-to-mass ratio of 5.003 m2/kg and a safety factor of 323.8 upon deployment. Conclusively, this work demonstrates a strong potential of the deployable antenna mechanism, providing high rigidity and large aperture diameter while ensuring high stability in space environments.

This study introduces a fruit harvesting mechanism powered by a single motor, designed for integration with unmanned aerial vehicles (UAVs). The mechanism performs reciprocating motion by converting linear motion into rotational motion. Consequently, the end-effector can execute multi-dimensional kinematic trajectories, including biaxial and rotational movements, synchronized with the motor’s position. These axial and rotational motions facilitate the gripper’s ability to reach, retrieve, and detach fruit from branches during the harvesting process. Notably, a critical consideration in designing this fruit harvesting mechanism is to generate the necessary torque at the end-effector while minimizing reaction forces and torque that could destabilize the UAV during flight. With these considerations in mind, this preliminary study aimed to harvest a Fuji apple and conduct a dynamic analysis. We constructed a prototype of the single motor-driven fruit harvesting mechanism using a suitable servo motor. To assess its mechanical performance and evaluate its impact on the hexacopter, we developed both a specific test platform featuring a six-spherical-prismatic-spherical parallel structure and a virtual environmental flight simulator. Overall, the results demonstrate the successful harvesting of a Fuji apple weighing approximately 300 g by the single motor-driven fruit harvesting mechanism, with no adverse effects observed on the hexacopter’s operation.

We investigate dynamics of water (H2O) and methanol (CH3OH and CH3OD) inside mesoporous silica materials with pore diameters of 4.0, 2.5, and 1.5 nm using low-field (LF) nuclear magnetic resonance (NMR) relaxometry. Experiments were conducted to test the effects of pore size, pore volume, type of fluid, fluid/solid ratio, and temperature on fluid dynamics. Longitudinal relaxation times (T1) and transverse relaxation times (T2) were obtained for the above systems. We observe an increasing deviation in confined fluid behavior compared to that of bulk fluid with decreasing fluid-to-solid ratio. Our results show that the surface area-to-volume ratio is a critical parameter compared to pore diameter in the relaxation dynamics of confined water. An increase in temperature for the range between 25 and 50°C studied did not influence T2 times of confined water significantly. However, when the temperature was increased, T1 times of water confined in both silica-2.5 nm and silica-1.5 nm increased, while those of water in silica-4.0 nm did not change. Reductions in both T1 and T2 values as a function of fluid-to-solid ratio were independent of confined fluid species studied here. The parameter T1/T2 indicates that H2O interacts more strongly with the pore walls of silica-4.0 nm than CH3OH and CH3OD.

The rapid advancements in 3D printing technologies offer immense design flexibility and the ability to create complex structures with high resolution. Using these cutting-edge technologies and materials (i.e., a polylactic acid and fused deposition modeling), a novel design principle is introduced for a fingerless gripper, achieved through topological optimization. To realize the grasping capabilities, a coiled garter spring made of shape memory alloy (SMA) is incorporated at the end of the flexure beams. Based on the experiments, it is found that the gripper is very quick to respond, taking only 5 s to heat up and 15 s to cool down. This promising performance is achieved by carefully balancing the net force differential between the restoring force of the flexure beam and the force of the SMA coiled garter spring. In addition to its responsiveness, the gripper demonstrates a high force-to-weight ratio of 5.3, allowing it to lift heavy payloads of up to 4.91 N (0.5 kgf ) despite its lightweight design (total weight of 94.2 g). Overall, this work showcases the potential of 3D printed fingerless grippers in terms of high holding strength, lightweight, low cost, and simple fabrication. [ABSTRACT FROM AUTHOR]