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Simultaneous Localization and Mapping (SLAM) addresses the problem of a robot navigating and acquiring spatial models of initially unknown environments, without an absolute localization means. To solve this problem, we propose a mapping system that builds feature-based geometrical maps by applying a modified Particle Swarm Optimization (PSO) algorithm. Particles are defined as the location of individual...
The problem of place recognition appears in different mobile robot navigation problems including localization, SLAM, or change detection in dynamic environments. Whereas this problem has been studied intensively in the context of robot vision, relatively few approaches are available for three-dimensional range data. In this paper, we present a novel and robust method for place recognition based on...
Mapping and localization play important roles for autonomous mobile robots. Since most of the conventional mapping methods assume static environment, the obtained map lacks reliability of localization when the assumption does not hold in the real environment. Additionally, when a robot wants to do some tasks (such as, open doors, push cabinets, etc.) during SLAM process, the robot need localize the...
In robotic applications of visual simultaneous localization and mapping techniques, loop-closure detection and global localization are two issues that require the capacity to recognize a previously visited place from current camera measurements. We present an online method that makes it possible to detect when an image comes from an already perceived scene using local shape and color information....
Localization and map building are two essential tasks for an autonomous mobile robot's indoor navigation without a prior map. This paper describes a mobile robot system designed for simultaneous localization and mapping (SLAM) for an autonomous mobile robot in an indoor environment. Due to variant sensor modeling for laser range finder and CCD camera, weighted least square fitting and Canny operator...
Many real-world applications require mobile robots to have 3D perception and mapping capabilities. This paper proposes a novel mechanism for augmenting a traditional 2D laser range finder to produce almost omni-directional 3D scans at degree resolution in 3 seconds. Also introduced is a multi-resolution sampling based algorithm for aligning generated range data stored as occupancy lists. This algorithm...
In the past few years, there has been significant advancement in localization and mapping using stereo cameras. Despite the recent successes, reliably generating an accurate geometric map of a large indoor area using stereo vision still poses significant challenges due to the accuracy and reliability of depth information especially with small baselines. Most stereo vision based applications presented...
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