Importance and Applications of Robotic and Autonomous Systems (RAS) in Railway Maintenance Sector: A Review <s> RAS in other Railway Maintenance Tasks <s> Cleaning of rolling stock and stations is very important work in supplying comfortable service to customers. However, there are some problems with cleaning work, e.g. lack of workers who are getting older. To improve these problems, the East Japan Railway has developed several kinds of robots for cleaning. Here, I explain four types of floor cleaning robots. The first is a dust-collecting robot (the sweeper-type robot) for corners of station floors, the second is a cleaning robot (the scrubber-type robot) for use throughout a station and the third is a floor cleaning robot for commuter rail cars, all of which are self-propelled. The last one is a bonnet cleaning robot for Shinkansen rolling stock which has special axis mechanisms and a running mechanism. <s> BIB001 </s> Importance and Applications of Robotic and Autonomous Systems (RAS) in Railway Maintenance Sector: A Review <s> RAS in other Railway Maintenance Tasks <s> A grade crossing is a crossing of a railway line and a motor road. In 2009 alone there were 248 deaths and 682 injuries at grade crossings in the United States. Factors like the elevation profile of a crossing or the environment and foliage around the crossing can render it unsafe. Often, vehicles with low ground clearance bottom out on a crossing with a humped elevation profile. Excessive foliage around the crossing can obstruct the visibility of an approaching train, reducing the time a driver has to stop. Hence ensuring safety requires regular monitoring and timely maintenance of grade crossings across the country. In this paper, we describe our method for automatically inspecting grade crossings. Our work employs principled machine learning methods to detect grade crossings from sensor data and then reconstructs the profile of that rail-road intersection. We then show how traffic simulation on the reconstructed profile can be used to determine whether the crossing is unsafe. <s> BIB002 </s> Importance and Applications of Robotic and Autonomous Systems (RAS) in Railway Maintenance Sector: A Review <s> RAS in other Railway Maintenance Tasks <s> The task of cleaning a vertical flat surface with the help of a standing humanoid robot is considered. A trajectory/force tracking controller is introduced that is implemented under a mixed position/torque control mode. The arm joints are controlled with a conventional PD controller working under position control, while the ankle joints are torque controlled. The desired force is realized via a force tracking controller using CoM and ZMP position readings obtained from the pressure sensors in the feet. The trajectory/force tracking controller is implemented and experimentally evaluated with a miniature humanoid robot HOAP-2. <s> BIB003 </s> Importance and Applications of Robotic and Autonomous Systems (RAS) in Railway Maintenance Sector: A Review <s> RAS in other Railway Maintenance Tasks <s> In recent years, there has been an increasing interest in the adoption of drones for monitoring a variety of infrastructures. Infrastructure monitoring systems are widely adopted to detect faults before they can lead to severe failures. They can be found in a number of civil structures, including bridges and viaducts, and also in many other applications of smart-maintenance, prognostics, health and security monitoring. This paper explores the usage of drones in railways for early warning, situation assessment and decision support applications. It leverages already available technological and research achievements for drone-based surveillance. The aim of the study is to preliminarily evaluate drone capabilities in a railway monitoring framework including structural faults and security threat detection as well as investigation on the consequences of natural hazards and intentional attacks. <s> BIB004 </s> Importance and Applications of Robotic and Autonomous Systems (RAS) in Railway Maintenance Sector: A Review <s> RAS in other Railway Maintenance Tasks <s> Usually, a railway interlocking system gathers information from its insulated sections, also known as track circuits. Each section is consisting of a distinct electrical circuit that provides vital information regarding rolling stock position and presence. The track circuit is a critically safe component, and even in the case of a failure it must ensure that trains do not collide. Thus, the maintenance of these functional blocks is of a major importance in the automation process. If the maintenance procedures are implemented correctly and adequately the failures are potentially eliminated, or at least their frequency reduced, thus improving the safety and reducing maintenance costs. This paper presents an innovative solution to optimize the railway infrastructure maintenance operations in terms of time, need of human operators and energy consumption. A robotized, semi-automatic mobile platform is employed for different safety parameters measurement. Collected data can be either stored onboard or transmitted via a non-dedicated short-range communications technology to a control point, operated by maintenance engineers. As the track circuit is a vital component of the railway safety signaling systems this remote preventive tool can contribute significantly to a maximum level of efficiency of the maintenance policy for every railway administration. The architecture of the system, a virtual instrumentation algorithm and mathematical models are presented in the paper, along with conclusions and recommendations. <s> BIB005 </s> Importance and Applications of Robotic and Autonomous Systems (RAS) in Railway Maintenance Sector: A Review <s> RAS in other Railway Maintenance Tasks <s> Abstract National railways are typically large and complex systems. Their network infrastructure usually includes extended track sections, bridges, stations and other supporting assets. In recent years, railways have also become a data-rich environment. Railway infrastructure assets have a very long life, but inherently degrade. Interventions are necessary but they can cause lateness, damage and hazards. Every day, thousands of discrete maintenance jobs are scheduled according to time and urgency. Service disruption has a direct economic impact. Planning for maintenance can be complex, expensive and uncertain. Autonomous scheduling of maintenance jobs is essential. The design strategy of a novel integrated system for automatic job scheduling is presented; from concept formulation to the examination of the data to information transitional level interface, and at the decision making level. The underlying architecture configures high-level fusion of technical and business drivers; scheduling optimized intervention plans that factor-in cost impact and added value. A proof of concept demonstrator was developed to validate the system principle and to test algorithm functionality. It employs a dashboard for visualization of the system response and to present key information. Real track incident and inspection datasets were analyzed to raise degradation alarms that initiate the automatic scheduling of maintenance tasks. Optimum scheduling was realized through data analytics and job sequencing heuristic and genetic algorithms, taking into account specific cost & value inputs from comprehensive task cost modelling. Formal face validation was conducted with railway infrastructure specialists and stakeholders. The demonstrator structure was found fit for purpose with logical component relationships, offering further scope for research and commercial exploitation. <s> BIB006
RAS in other railway maintenance tasks include automated cleaning robots in train stations, monitoring of railway infrastructure using drones, monitoring and inspection of grade crossing at etc. Hiroshi has introduced two mobile cleaning robots, to clean stations in the East Japan Railway Company BIB001 . One robot is designed to sweep the and collect the dust that accumulated in the corners of station floor and another robot is designed to scrub the station floor. The sweeper type robot has three operational modes, namely 'magnetic guide method', where the robot follows the path of a magnetic tape, 'direct teaching method', where the robot memorizes the path taught by an operator, and a 'wall surface copy system', where the robot follows the wall while using ultrasonic distance sensors. The second robot, by Hiroshi, is capable of sprinkling water, scrubbing the floor, and removing consumed water by suction. The robot is fixed with a self-propelled system that includes a gyroscope in order to cope with wider station concourse. This robot consists of two operating modes, 'area set up mode', where the robot cleans the input length and width of the area and 'route map mode' where the robot cleans according to a built-in map. The area clean mode has the obstacle avoidance capability, while the built-in map mode does not. Furthermore, it is possible to upload up to nine built-in maps. Both of these robots consist of safety features, such as optical sensors to detect the presence of humans, melody chime, alarm lamp, emergency stop switches, and soft bumpers. A similar commercially available cleaning robot for various industrial applications, including railway platforms, is available at "Robotics Inventions" under original equipment manufacturer license. The system claims to have military grade autonomy and mapping capabilities, automated recognition of dirt type to be cleaned, and auto-service station with recycled water tank  . Besides, Flammini et al. have evaluated the drone capabilities in a railway-monitoring framework, which include structural health monitoring, such as bridge, tunnel, and other infrastructure inspection, track monitoring, and inspection to detect any faults or disturbances. Authors have presented several potential control and communication frameworks for the drones and claim that drones could represent a promising technology to efficiently monitor railway and mass transit infrastructures BIB004 . In addition, Ranganathan and Olson have proposed an automated grade crossing condition monitoring system. The required sensors are mounted to a vehicle and the developed algorithm is capable of processing data on the go. The presented system is able to identify a grade crossing with 90% accuracy while using SVM and identify any dangerous traffic flow lines/regions based on the surface profile of the grade crossing BIB002 BIB003 . A robotized, semi-automated platform is introduced in BIB005  to collect different safety parameter measurements that are linked to railway track circuits (TC). A system architecture, together with a virtual instrumentation and mathematical model, is presented. It has been concluded that the proposed system can become a viable solution for TC maintenance. Authors claim that this system would be an efficient solution for current manual maintenance practice and aim to improve the operator safety and reduce human errors. Railway maintenance as a whole is typically a large and complex system. Therefore, these tasks needs to be scheduled in an effective way to improve safety, reduce downtimes, eliminate corrective maintenance jobs, optimize asset/equipment life cycle, and reduce costs. One approach to overcome this challenge is to exploit a data rich environment of railway and introduce autonomous scheduling for maintenance jobs. In BIB006 , an automated task scheduling scheme is introducing by fusing data on railway's condition, planning, and costs. Here, a proof of concept is developed to validate the system and test algorithm functionality. Its authors conclude that the demonstrator found to be viable fit for the purpose. It is expected to conduct further research and evaluate commercial exploitation of the system. A similar system is introduced in  . Here, a genetic algorithm is used to optimize railway track maintenance and renewal job scheduling. The system was demonstrated to perform well and illustrated the ability to instead use corrective maintenance activities.