RGB-D versus omnidirectional visual SLAM in humanoid robot positioning
Résumé
Visual Simultaneous Localization and Mapping (V-SLAM) with an color plus Depth (RGB-D) camera is the gold standard to help correcting humanoid robots’ drift while walking toward a goal pose indoors. But, the bounded range and Field of View (FoV) of these cameras constrain the use cases for humanoids to few changes in the environment. At the same time, compact omnidirectional cameras capable of a 360° FoV are spreading quickly at low cost, offering more possibilities to the V-SLAM system to observe reliable features whichever the robot orientation. Thus, this paper investigates the V-SLAM with a 360° camera versus an RGB-D one in the humanoid head for correcting the walking drift of a baseline walking controller over several meters. The Baseline Biped Positioning hence made is evaluated regarding final pose accuracy improvement and robustness to environmental changes by leveraging multiple sets of real experiments on a 1.8 m tall humanoid robot.
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