In this paper, we present a complete description of the hardware design and control architecture of our custom built quadruped robot, called the Stoch. Our goal is to realize a robust, modular, and a reliable quadrupedal platform, using which various locomotion behaviors are explored. This platform enables us to explore different research problems in legged locomotion, which use both traditional and learning based techniques. We discuss the merits and limitations of the platform in terms of exploitation of available behaviours, fast rapid prototyping, reproduction and repair. Towards the end, we will demonstrate trotting, bounding behaviors, and preliminary results in turning. In addition, we will also show various gait transitions i.e., trot-to-turn and trot-to-bound behaviors.
Optical Coherence Tomography (OCT) is an optical imaging technology occupying a unique position in the resolution vs. imaging depth spectrum. It is already well established in the field of ophthalmology, and its application in other fields of medicine is growing. This is motivated by the fact that OCT is a real-time sensing technology with high sensitivity to precancerous lesions in epithelial tissues, which can be exploited to provide valuable information to clinicians. In the prospective case of OCT-guided endoscopic laser surgery, these real-time data will be used to assist surgeons in challenging endoscopic procedures in which high-power lasers are used to eradicate diseases. The combination of OCT and laser is expected to enhance the detection of tumors, the identification of tumor margins, and ensure total disease eradication while avoiding damage to healthy tissue and critical anatomical structures. Therefore, OCT-guided endoscopic laser surgery is an important nascent research area. This paper aims to contribute to this field with a comprehensive review of state-of-the-art technologies that may be exploited as the building blocks for achieving such a system. The paper begins with a review of the principles and technical details of endoscopic OCT, highlighting challenges and proposed solutions. Then, once the state of the art of the base imaging technology is outlined, the new OCT-guided endoscopic laser surgery frontier is reviewed. Finally, the paper concludes with a discussion on the constraints, benefits and open challenges associated with this new type of surgical technology.
Optical coherence tomography (OCT) is a rapidly evolving imaging technology that combines a broadband and low-coherence light source with interferometry and signal processing to produce high-resolution images of living tissues. However, the speckle noise introduced by the low-coherence interferometry and the blur from device motions significantly degrade the quality of OCT images. Convolutional neural networks (CNNs) are a potential solution to deal with these issues and enhance OCT image quality. However, training such networks based on traditional supervised learning methods is impractical due to the lack of clean ground truth images. Consequently, this research proposes an unsupervised learning method for OCT image enhancement, termed one-step enhancer (OSE). Specifically, OSE performs denoising and deblurring based on a single step process. A generative adversarial network (GAN) is used for this. Encoders disentangle the raw images into a content domain, blur domain and noise domain to extract features. Then, the generator can generate clean images from the extracted features. To regularize the distribution range of retrieved blur characteristics, KL divergence loss is employed. Meanwhile, noise patches are enforced to promote more accurate disentanglement. These strategies considerably increase the effectiveness of GAN training for OCT image enhancement when used jointly. Both quantitative and qualitative visual findings demonstrate that the proposed method is effective for OCT image denoising and deblurring. These results are significant not only to provide an enhanced visual experience for clinicians but also to supply good quality data for OCT-guide operations. The enhanced images are needed, e.g., for the development of robust, reliable and accurate autonomous OCT-guided surgical robotic systems.
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