Importance and applications of robotic and autonomous systems (RAS) in railway maintenance sector: a review

Maintenance, which is critical for safe, reliable, quality, and cost-effective service, plays a dominant role in the railway industry. Therefore, this paper examines the importance and applications of Robotic and Autonomous Systems (RAS) in railway maintenance. More than 70 research publications, which are either in practice or under investigation describing RAS developments in the railway maintenance, are analysed. It has been found that the majority of RAS developed are for rolling-stock maintenance, followed by railway track maintenance. Further, it has been found that there is growing interest and demand for robotics and autonomous systems in the railway maintenance sector, which is largely due to the increased competition, rapid expansion and ever-increasing expense

SMART IMAGE-GUIDED NEEDLE INSERTION FOR TISSUE BIOPSY

M.S

Intelligent Information-Guided Robotic Surgery

Laparoscopic surgery is minimally invasive, providing various benefits for patients. On the other hand, it is technically demanding for physicians due to limited dexterity of tools, limited vision. In order to cope with those limitations, recent various engineering technologies are trying to help surgeon. Robotics is one of the major technologies in this field. Until today, da Vinci has been only one such robot. But recently, many other robotic systems are under development. Those new robots are introduced in this chapter first. Other than robotics, or in conjunction with robotics, navigation technologies are getting popularity in clinical use. Navigation is a technology that provides useful information such as preoperative images or distance between tool and lesion, etc. to surgeon. Our experience in clinical use of navigation system in robotic surgery is introduced. Finally, technologies applied for the training of surgeon are introduced and described

a computer assisted robotic platform for vascular procedures exploiting 3d us based tracking

AbstractBackground: Cardiovascular diseases are the first cause of death globally: an estimated 17.5 million people died in 2012. By combining the benefits of magnetic navigation and ultrasound (US) imaging, the authors proposed a robotic platform (i.e. the MicroVAST platform) for intravascular medical procedures.Methods: A 3D imaging US-based tracking algorithm is implemented for the navigation of a magnetic-dragged soft-tethered device. Tests were performed to evaluate the algorithm in terms of tracking error and precision of locomotion.Results: The 3D imaging US-based algorithm tracked the endovascular device with an error of 6.4 ± 2.8 pixels and a mean displacement between the endovascular device and the preoperative path of 13.6 ± 4.5 mm (computational time of 12.2 ± 1.5 ms and 30.7 ± 6.1 matched features).Conclusions: The MicroVAST platform includes innovative solutions for navigation allowing for an assisted magnetic locomotion of medical devices in the cardiovascular district by combining a 3D ima..

Smart Camera Robotic Assistant for Laparoscopic Surgery

The cognitive architecture also includes learning mechanisms to adapt the behavior of the robot to the different ways of working of surgeons, and to improve the robot behavior through experience, in a similar way as a human assistant would do. The theoretical concepts of this dissertation have been validated both through in-vitro experimentation in the labs of medical robotics of the University of Malaga and through in-vivo experimentation with pigs in the IACE Center (Instituto Andaluz de Cirugía Experimental), performed by expert surgeons.In the last decades, laparoscopic surgery has become a daily practice in operating rooms worldwide, which evolution is tending towards less invasive techniques. In this scenario, robotics has found a wide field of application, from slave robotic systems that replicate the movements of the surgeon to autonomous robots able to assist the surgeon in certain maneuvers or to perform autonomous surgical tasks. However, these systems require the direct supervision of the surgeon, and its capacity of making decisions and adapting to dynamic environments is very limited. This PhD dissertation presents the design and implementation of a smart camera robotic assistant to collaborate with the surgeon in a real surgical environment. First, it presents the design of a novel camera robotic assistant able to augment the capacities of current vision systems. This robotic assistant is based on an intra-abdominal camera robot, which is completely inserted into the patient’s abdomen and it can be freely moved along the abdominal cavity by means of magnetic interaction with an external magnet. To provide the camera with the autonomy of motion, the external magnet is coupled to the end effector of a robotic arm, which controls the shift of the camera robot along the abdominal wall. This way, the robotic assistant proposed in this dissertation has six degrees of freedom, which allow providing a wider field of view compared to the traditional vision systems, and also to have different perspectives of the operating area. On the other hand, the intelligence of the system is based on a cognitive architecture specially designed for autonomous collaboration with the surgeon in real surgical environments. The proposed architecture simulates the behavior of a human assistant, with a natural and intuitive human-robot interface for the communication between the robot and the surgeon

Context-aware learning for robot-assisted endovascular catheterization

Endovascular intervention has become a mainstream treatment of cardiovascular diseases. However, multiple challenges remain such as unwanted radiation exposures, limited two-dimensional image guidance, insufficient force perception and haptic cues. Fast evolving robot-assisted platforms improve the stability and accuracy of instrument manipulation. The master-slave system also removes radiation to the operator. However, the integration of robotic systems into the current surgical workflow is still debatable since repetitive, easy tasks have little value to be executed by the robotic teleoperation. Current systems offer very low autonomy, potential autonomous features could bring more benefits such as reduced cognitive workloads and human error, safer and more consistent instrument manipulation, ability to incorporate various medical imaging and sensing modalities. This research proposes frameworks for automated catheterisation with different machine learning-based algorithms, includes Learning-from-Demonstration, Reinforcement Learning, and Imitation Learning. Those frameworks focused on integrating context for tasks in the process of skill learning, hence achieving better adaptation to different situations and safer tool-tissue interactions. Furthermore, the autonomous feature was applied to next-generation, MR-safe robotic catheterisation platform. The results provide important insights into improving catheter navigation in the form of autonomous task planning, self-optimization with clinical relevant factors, and motivate the design of intelligent, intuitive, and collaborative robots under non-ionizing image modalities.Open Acces

Small business innovation research. Abstracts of 1988 phase 1 awards

Non-proprietary proposal abstracts of Phase 1 Small Business Innovation Research (SBIR) projects supported by NASA are presented. Projects in the fields of aeronautical propulsion, aerodynamics, acoustics, aircraft systems, materials and structures, teleoperators and robots, computer sciences, information systems, data processing, spacecraft propulsion, bioastronautics, satellite communication, and space processing are covered

A Review of Locomotion Systems for Capsule Endoscopy

Wireless capsule endoscopy for gastrointestinal (GI) tract is a modern technology that has the potential to replace conventional endoscopy techniques. Capsule endoscopy is a pill-shaped device embedded with a camera, a coin battery, and a data transfer. Without a locomotion system, this capsule endoscopy can only passively travel inside the GI tract via natural peristalsis, thus causing several disadvantages such as inability to control and stop, and risk of capsule retention. Therefore, a locomotion system needs to be added to optimize the current capsule endoscopy. This review summarizes the state-of-the-art locomotion methods along with the desired locomotion features such as size, speed, power, and temperature and compares the properties of different methods. In addition, properties and motility mechanisms of the GI tract are described. The main purpose of this review is to understand the features of GI tract and diverse locomotion methods in order to create a future capsule endoscopy compatible with GI tract properties