## An Atlas Framework for Scalable Mapping (2003)

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Venue: | in IEEE International Conference on Robotics and Automation |

Citations: | 156 - 18 self |

### BibTeX

@INPROCEEDINGS{Bosse03anatlas,

author = {Michael Bosse and Paul Newman and John Leonard and Martin Soika and Wendelin Feiten and Seth Teller},

title = {An Atlas Framework for Scalable Mapping},

booktitle = {in IEEE International Conference on Robotics and Automation},

year = {2003},

pages = {1899--1906}

}

### Years of Citing Articles

### OpenURL

### Abstract

This paper describes Atlas, a hybrid metrical /topological approach to SLAM that achieves efficient mapping of large-scale environments. The representation is a graph of coordinate frames, with each vertex in the graph representing a local frame, and each edge representing the transformation between adjacent frames. In each frame, we build a map that captures the local environment and the current robot pose along with the uncertainties of each. Each map's uncertainties are modeled with respect to its own frame. Probabilities of entities with respect to arbitrary frames are generated by following a path formed by the edges between adjacent frames, computed via Dijkstra's shortest path algorithm. Loop closing is achieved via an efficient map matching algorithm. We demonstrate the technique running in real-time in a large indoor structured environment (2.2 km path length) with multiple nested loops using laser or ultrasonic ranging sensors.

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Citation Context ...ing data from the same experiment but using the Polaroid ultrasonic rangers instead of the laser scanner. The local navigation method used is a combination of Delayed Decision Making [LRNB02], RANSAC =-=[FB80]-=- and wide beam sonar interpretation [LDW92]. The key idea of this approach is to incorporate temporal as well as spatial correlations in the stochastic mapping process. This enables map features to be... |

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Citation Context ...tion and mapping (SLAM) problem. A variety of approaches have been proposed for representing the uncertainty inherent to sensor data and robot motion, including topological [9], particle filter [16], =-=[12]-=-, and feature-based [14] models. Several highly successful SLAM approaches have been developed based on the combination of laser scan matching with Bayesian state estimation [7], [16]. These methods, ... |

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Citation Context ...tures) of the Kalman filter SLAM solution. Efficient strategies for SLAM with feature-based representations and Gaussian representation of error include postponement [2], decoupled stochastic mapping =-=[10]-=-, the compressed filter [6], sequential map joining [15], the constrained local submap filter [18], and sparse extended information filters [17]. Each of these methods employs a single, globally refer... |

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Citation Context ...entations and Gaussian representation of error include postponement [2], decoupled stochastic mapping [10], the compressed filter [6], sequential map joining [15], the constrained local submap filter =-=[18]-=-, and sparse extended information filters [17]. Each of these methods employs a single, globally referenced coordinate frame for state estimation. The Kalman filter can fail badly, however, in situati... |

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Citation Context ...ent began. Figure 7(b) shows results using data from the same experiment but using the Polaroid ultrasonic rangers instead of the laser scanner. The local navigation method used is described fully in =-=[11]-=-. Additional results, including concurrent processing of both laser 140 120 12 45 11 13 14 20 46 44 15 21 10 43 16 22 19 1723 31 30 29 28 24 18 2532 26 27 33 100 9 842 47 48 34 80 60 41 7 95 6 540 49 ... |

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Citation Context ...vide global results. An alternative to the use of local linearization would be to adopt a fully nonlinear formulation of the SLAM problem, such as FastSLAM [12] or SLAM using a sum of Gaussians model =-=[5]-=-. The computational requirements of these methods, however, remain poorly understood in large cyclic environments. In future research, it may be possible to implement Atlas using one of these techniqu... |

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Citation Context ... shown below in Figure 6(b) in Section V provides a dramatic illustration of this type of situation. One of the appealing aspects of a hybrid metrical/topological approach to mapping and localization =-=[1]-=-, [9] is that uncertain state estimates do not need to be referenced to a single global reference frame. This is the strategy advocated in this paper. With Atlas, we obtain the best of both global and... |

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Citation Context ... include postponement [2], decoupled stochastic mapping [10], the compressed filter [6], sequential map joining [15], the constrained local submap filter [18], and sparse extended information filters =-=[17]-=-. Each of these methods employs a single, globally referenced coordinate frame for state estimation. The Kalman filter can fail badly, however, in situations with large angular errors and significant ... |

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Citation Context ...vide global results. An alternative to the use of local linearization would be to adopt a fully nonlinear formulation of the SLAM problem, such as FastSLAM [12] or SLAM using a sum of Gaussians model =-=[5]-=-. The computational requirements of these methods, however, remain poorly understood in large cyclic environments. In future research, it may be possible to implement Atlas using one of these techniqu... |

1 | T j i � = ⎡ ⎣ = ⊖T j ⎤ ⎦ −ci −si sixi − ciyi si −ci cixi + siyi 0 - J⊖ |

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1 |
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Citation Context ... enough to prevent the recognition of an already mapped region — i.e., loop closing is hard [Thr01]. • We expect to encounter featureless regions in which navigation must rely on dead reckoning al=-=one [New02]-=-. Building a single monolithic map results in an un-mangaged growth of complexity and computational burden. This in combination with the fact that spatially distant features can be decoupled has led s... |