The demand for surgical robots has increased in recent years, accompanying the growing attention to minimally invasive surgery. To support the development of compact and cost-effective forceps for surgical robots, this paper proposes a novel forceps mechanism inspired by the pincers of crabs. The mechanism aims to reduce the number of components compared to conventional forceps, enabling a simpler, smaller, lighter, and compliant structure. Among organisms on Earth, crustaceans exhibit a high force-to-body-weight ratio, which led to our inspiration from crab chelae. The proposed mechanism, termed “Clawceps”, applies the crab’s scissor-like mechanism and incorporates the principle of leverage to stabilize force transmission. While the structure is compliant when no force is applied, the mechanism changes mode when the forceps are closed, engaging the joint to act as a fulcrum, thereby increasing the gripping force. The novel mechanism was evaluated using finite element analysis (FEA) with a PLA 3D-printed physical prototype. Models with and without a fulcrum were prepared to observe the gripping force. According to the FEA results, when the displacement was 1.5 mm, the gripping force of the model with a fulcrum was 7.8 N, while that without a fulcrum was 0.2 N. Experimental measurements with the actual prototype also showed significantly higher gripping force of the model with a fulcrum compared with that without a fulcrum, demonstrating the effectiveness of the mechanism. By implementing a mechanism that switches operation modes and transmits force using the principle of leverage, the Clawceps achieve both compliance and strong gripping force. This study successfully proved the concept of the proposed method to overcome a current limitation of compliant mechanism by incorporating principles derived from exoskeletal structures.

Colonoscopy is the most effective procedure for cancer screening. However, insertion of a colonoscope into the large intestine remains challenging because of the complex and highly variable anatomy of the colon, particularly variations in its inner diameter. Various self-propelled colonoscopy robots have been proposed to overcome these difficulties. Nevertheless, several existing systems require complex mechanisms for adaptation to changes in the inner diameter of the colon, which increases structural complexity and limits practicality. Therefore, simpler and more adaptive propulsion mechanisms are required. In this paper, we propose a self-propelled colonoscopy robot with an elastic wall-fitting mechanism. This mechanism utilizes the elastic force of shape memory alloy (SMA) wires to adaptively conform to variations in the inner diameter of the colon, ensuring continuous contact with the intestinal wall. A prototype robot was fabricated using a 3D printer. Evaluation experiments were conducted using simulated intestinal tract models with inner diameters ranging from 30 to 60 mm to assess propulsion performance and thrust generation. The experimental results demonstrated that the proposed robot successfully self-propelled in all the simulated intestinal models. The robot achieved a maximum propulsive speed of 11 mm/s and generated sufficient thrust across the diameter range tested, indicating stable propulsion performance despite changes in the inner diameter. These results confirm that the proposed elastic wall-fitting mechanism effectively adapts to variations in the inner diameter of the colon without requiring complex mechanical structures. By leveraging the elastic properties of the SMA wires, the robot maintained consistent wall contact and stable propulsion, suggesting its potential applicability in safe and efficient colonoscopy procedures.

In the treatment of esophageal cancer, the high postoperative complication rate is an issue because of the extensive lymph node resection for curative purposes. To optimize the extent of resection, we developed a forceps-type coincidence radiation detector based on the concept of positron emission tomography (PET) for precise intraoperative localization of metastases. The forceps-type coincidence radiation detector consists of a pair of miniaturized PET detectors mounted on the tip of the forceps. The forceps are clamped over a suspected metastatic site intraoperatively to measure the radiation and identify the site of metastasis based on 18F-labeled fluorodeoxyglucose accumulation above a certain threshold. However, the sensitivity of the forceps-type coincidence radiation detector depends on the distance between the pair of detectors mounted on the tips of the forceps, and maintaining a constant distance between these detectors is difficult because the handle is held in the palm of the surgeon operating the device. Achieving stable coincidence counting requires correction of the coincidence radiation sensitivity according to the distance between the detectors during measurement. Utilizing the fact that the distance between detectors depends on the tip angle of the forceps, we developed a system that executes the correction based on the forceps tip angle. A linear encoder was used to measure the displacement of the forceps shaft and estimate the forceps tip angle from the amount of displacement. We also evaluated the effect of correcting radiation detection sensitivity using an experimentally developed system. The radiation detection sensitivity was corrected to a mean (± standard deviation) dose of 22.3 ± 1.3 kBq compared to the true value of 21.3 kBq. The average correction error was 5%, indicating the correction capability of the developed system. However, the variations in correction values pose a risk of missing metastases. In the future, the accuracy of the correction system will be improved, and experiments will be conducted in the clinical environment.

Modern hepatectomies are planned along anatomical segments of the liver, and intraoperative injection of indocyanine green enables visualization of these segments using near-infrared fluorescence (NIRF) laparoscopy. However, subsegmental resections that extend partially beyond boundaries of the segments are increasingly attempted in patients with liver insufficiency, requiring additional anatomical understanding of the lesions. Recently, augmented reality (AR) has gained attention as a technique for overlaying preoperative anatomical information directly onto the surgical field. Nonetheless, achieving real-time and precise alignment of preoperative data onto surgical objects remains a challenge. To address this issue, we propose an AR system using a multimodal tissue marker detectable by both X-ray and NIRF, and an object-detection machine-learning model (YOLOv9). The multimodal AR marker was administered to excised porcine liver samples, and their NIRF laparoscopic and X-ray computed tomography (CT) images were acquired. Marker coordinates in the NIRF laparoscopic images were obtained using the YOLOv9 model, and the correspondence between markers in the CT and NIRF views were automatically determined using our original algorithm. CT marker images were reprojected onto the laparoscopic images based on their coordinates. The system achieved an 80.2% marker detection success rate in NIRF images, a 78.4% registration success rate, and a mean reprojection error of 3.9 pixels, with an average processing speed of 28.9 fps. These results demonstrate the potential of our proposed system to realize real-time AR navigation during laparoscopic liver surgeries. Although clinical application would require a hybrid operating room equipped with CT at the time of marker administration, this technology has the potential to superimpose internal structures of the liver onto the organ surface in the laparoscopic view on video monitors.