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handle: 10533/139319
SUMMARYThis paper presents a novel method for localization of mobile robots in structured environments. The estimation of the position and orientation of the robot relies on the minimisation of the partial Hausdorff distance between ladar range measurements and a floor plan image of the building. The approach is employed in combination with an extended Kalman filter to obtain accurate estimates of the robot's position, heading and velocity. Good estimates of these variables were obtained during tests performed using a differential drive robot, thus demonstrating that the approach provides an accurate, reliable and computationally feasible alternative for indoor robot localization and autonomous navigation.
mobile robot localization, ALIGNMENT, 11 Ciudades y comunidades sostenibles, Hausdorff distance, IMAGES, NAVIGATION, REGISTRATION, 11 Sustainable Cities and Communities, map-matching, 004, 620
mobile robot localization, ALIGNMENT, 11 Ciudades y comunidades sostenibles, Hausdorff distance, IMAGES, NAVIGATION, REGISTRATION, 11 Sustainable Cities and Communities, map-matching, 004, 620
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 29 | |
popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |