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It is shown that the proposed mapping algorithm successfully estimates the position of a sample's edges. The principle is demonstrated in both simulation and laboratory-based experiments. A Bayesian mapping technique (Occupancy grid mapping) was used to map the boundaries of an irregular sample in a pseudo-pulse-echo mode. Shear Horizontal (SH) guided waves generated by Electro-Magnetic Acoustic Transducers (EMATs) are used for mapping steel samples with a nominal thickness of 10 mm. It considers the specific problem of mapping geometric features using the guided ultrasonic waves, which enables the localisation of edges and/or the welded joints. Experimentally, a range accuracy of < 1.7 mm (1σ) was achieved on a 1 × 2 m sample using miniaturised EMATs operating at a wavelength of 22 mm.ĪB - This paper evaluates the benefits of using ultrasonic guided waves for the mapping of a structure, when implemented on a mobile magnetic robotic platform. The proposed mapping system has been built in order to be completely autonomous and unassisted. The algorithm includes some simplifications in order to be used with low-cost hardware resources. An ad hoc algorithm for mapping based on the Occupancy Grid method has been developed. A Bayesian mapping technique (Occupancy grid mapping) was used to map the boundaries of an irregular sample in a pseudo-pulse-echo mode. This paper presents a mapping system that is suitable for small mobile robots. N2 - This paper evaluates the benefits of using ultrasonic guided waves for the mapping of a structure, when implemented on a mobile magnetic robotic platform. For example, a maze-like environment with walls at regular square grid distances, where it is simple to detect the presence of a wall in each direction of a grid cell.T1 - Application of ultrasonic guided waves to robotic occupancy grid mapping Structured environments may have a lower accuracy requirement.
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GPS), even with a laser scanner, you will need to be able to solve the problem of "closing the loop". If you are able to carefully control wheel slippage, wheel odometry can significantly improve localization in the short term (although an absolute method of localization is preferred). Of course, this depends on the scale of the robot, and if it is indoors, GPS may not be practical. Occupancy grid mapping is one of the vital areas of research in the field of mobile robotics which provides perception of the environment for diverse applications such as path planning, localization, autonomous navigation, 1,2,3. Thus, they are of negligible help in helping to localize (except in very structured environments).Ī GPS/IMU combination can be used to get reasonable localization. Ultrasound sensors are very fuzzy, they generally have a direction fuzziness of 20+ degrees, and anything in the general direction will be detected. In particular, this is an implementation of Table 9.1 and 9.2. in Chapter 9 of 'Probabilistic Robotics' By Sebastian Thrun et al. Robots that use laser scanners can make do with just odometry, because the data is relatively accurate, and the scanner data can be used to help localize in subsequent time steps. This is an implementation of Occupancy Grid Mapping as Presented. To do SLAM, you will need a relatively good estimate of position. In step S118, an integration module 18 establishes a composite grid (e.g., a composite occupancy grid) referenced to the vehicle coordinate reference frame or a ground reference frame, where the composite grid is based on the first mapping and the second mapping.