Advances in Stereo Vision by J. Torreao PDF

By J. Torreao

ISBN-10: 9533078375

ISBN-13: 9789533078373

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1998). Learning metric-topological maps for indoor mobile robot navigation, Artificial Intelligence 99(1): 21–71. , Nourbakhsh, I. & Siegwart, R. (2003). Hybrid simultaneous localization and map building: a natural integration of topological and metric, Robotics and Autonomous Systems 44(1): 3–14. , Castelhano, M. S. & Henderson, J. M. (2006). , Psychol Rev 113: 766–786. , Simeon, T. & Alami, R. (2000). Incremental topological modeling using local voronoï-like graphs, Proc. of IEEE/RSJ Int. Conf.

Finally, it is obtained an environment representation that corresponds to a great extent with the real scene. The error in the dimensions of the first room (see figure 17(e)) is due to the discretization of the Hough space. This kind of errors are considered in the representation of the model as part of its uncertainty. It is important to note that this uncertainty is local to the model. Thus, as it is shown in figure 17, there is no error propagation in the creation of remaining models composing the final representation of the environment.

Regarding room parameters, potential errors in the detection process may affect only to the estimation of the room dimensions (hrk and wrk ). Thus, any variation in a room model should be associated to these parameters. However, since every wall corresponds to a segment of the room model and the uncertainty in the detection process is associated to segments and not to model dimensions, the position of every wall is individually adjusted (see 7(b)). These wall adjustments modify the dimensions of the rooms as follows: hrk ← hrk + wrk ← wrk + (2) hrk − (2) wrk (a) − (1) hrk (35) (1) wrk (36) (b) Fig.

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Advances in Stereo Vision by J. Torreao

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