Abstract: This paper reports on a navigation method for the snow-removal robot called SnowEater. The robot is designed to work autonomously within small areas (around 30 m2 or less) following line segment paths. The line segment paths are laid out so as much snow as possible can be cleared from an area. Navigation is accomplished by using an onboard low-resolution USB camera and a small marker located in the area to be cleared. Low-resolution cameras allow only limited localization and present significant errors. However, these errors can be overcome by using an efficient navigation algorithm to exploit the merits of these cameras. For stable robust autonomous snow removal using this limited information, the most reliable data are selected and the travel paths are controlled. The navigation paths are a set of radially arranged line segments emanating from a marker placed in the environment area to be cleared, in a place where it is not covered by snow. With this method, by using a low-resolution camera (640 × 480 pixels) and a small marker (100 × 100 mm), the robot covered the testing area following line segments. For a reference angle of 4.5° between line paths, the average results are: 4° for motion on hard floor and 4.8° for motion on compacted snow. The main contribution of this study is the design of a path-following control algorithm capable of absorbing the errors generated by a low-cost camera.
Abstract: Concentrated solar power (CSP) plants are expansive facilities that require substantial inspection and maintenance. A fully automated inspection robot increases the efficiency of maintenance work, reduces operating and maintenance costs, and improves safety and work conditions for service technicians. This paper describes a climbing robot that is capable of performing inspection and maintenance on vertical surfaces of solar power plants, e.g., the tubes of the receiver in a central tower CSP plant. Specifically, the service robot’s climbing mechanism is explained and the results of the nondestructive inspection methods are reviewed. The robot moves on the panels of the receiver in the tower and aligns the sensors correctly for inspection. The vertical movement of the climbing kinematics is synchronized with the movement of the tower’s crane. Various devices that detect surface defects and thickness losses inside the tube were integrated into the robot. Since the tubes are exposed to very high radiation, they need to be inspected regularly.
Abstract: In this paper we propose a probabilistic sequential model of Human-Robot Spatial Interaction (HRSI) using a well-established Qualitative Trajectory Calculus (QTC) to encode HRSI between a human and a mobile robot in a meaningful, tractable, and systematic manner. Our key contribution is to utilise QTC as a state descriptor and model HRSI as a probabilistic sequence of such states. Apart from the sole direction of movements of human and robot modelled by QTC, attributes of HRSI like proxemics and velocity profiles play vital roles for the modelling and generation of HRSI behaviour. In this paper, we particularly present how the concept of proxemics can be embedded in QTC to facilitate richer models. To facilitate reasoning on HRSI with qualitative representations, we show how we can combine the representational power of QTC with the concept of proxemics in a concise framework, enriching our probabilistic representation by implicitly modelling distances. We show the appropriateness of our sequential model of QTC by encoding different HRSI behaviours observed in two spatial interaction experiments. We classify these encounters, creating a comparative measurement, showing the representational capabilities of the model.
Abstract: In this work the velocity, acceleration, and jerk analyses of a two-degrees-of-freedom parallel wrist are approached by means of the theory of screws. For the sake of completeness, the finite kinematics of the manipulator is also investigated. As far as the authors are aware, the equation of jerk in screw form of the robot at hand is introduced by the first time in this contribution. In order to exemplify the method, a case study is included. The numerical example is verified with the aid of commercially available software.
Abstract: This paper presents an autonomous docking system with novel integrated algorithms for mobile self-reconfigurable robots equipped with inexpensive sensors. A novel docking algorithm was developed to determine the initial distance and orientation of the two modules, and sensor models were established through experiments. Both Extended Kalman filter (EKF) and particle filter (PF) were deployed to fuse the measurements from IR and encoders and provide accurate estimates of orientation and distance. Simulation experiments were carried out first and then real experiments were conducted to verify the feasibility and good performance of the proposed docking algorithm and system. The proposed system provides a robust and reliable docking solution using low cost sensors.