Page 260 - Introduction to Autonomous Mobile Robots
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Mobile Robot Localization


                                                                 50 m                 P 3      245
                                                                                     L 2
                                                              50 m
                                         Z-shaped landmark                          x 2
                                                                                      P 2
                                                       50 m
                                                                                    L 1
                                                                               P 1


                           Figure 5.35
                           Z-shaped landmarks on the ground. Komatsu Ltd., Japan [5 pp. 179-180]



                           employ modifications of the robot’s environment, something that the Markov localization
                           and Kalman filter localization communities eschew. In the following sections, we briefly
                           identify the general strategy incorporated by each category and reference example systems,
                           including, as appropriate, those that modify the environment and those that function with-
                           out environmental modification.

                           5.7.1   Landmark-based navigation
                           Landmarks are generally defined as passive objects in the environment that provide a high
                           degree of localization accuracy when they are within the robot’s field of view. Mobile
                           robots that make use of landmarks for localization generally use artificial markers that have
                           been placed by the robot’s designers to make localization easy.
                             The control system for a landmark-based navigator consists of two discrete phases.
                           When a landmark is in view, the robot localizes frequently and accurately, using action
                           update and perception update to track its position without cumulative error. But when the
                           robot is in no landmark “zone,” then only action update occurs, and the robot accumulates
                           position uncertainty until the next landmark enters the robot’s field of view.
                             The robot is thus effectively dead-reckoning from landmark zone to landmark zone.
                           This in turn means the robot must consult its map carefully, ensuring that each motion
                           between landmarks is sufficiently short, given its motion model, that it will be able to local-
                           ize successfully upon reaching the next landmark.
                             Figure 5.35 shows one instantiation of landmark-based localization. The particular
                           shape of the landmarks enables reliable and accurate pose estimation by the robot, which
                           must travel using dead reckoning between the landmarks.
                             One key advantage of the landmark-based navigation approach is that a strong formal
                           theory has been developed for this general system architecture [98]. In this work, the
                           authors have shown precise assumptions and conditions which, when satisfied, guarantee
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