## Robotic Mapping: A Survey (2002)

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Venue: | Exploring Artificial Intelligence in the New Millenium |

Citations: | 288 - 9 self |

### BibTeX

@INPROCEEDINGS{Thrun02roboticmapping:,

author = {Sebastian Thrun},

title = {Robotic Mapping: A Survey},

booktitle = {Exploring Artificial Intelligence in the New Millenium},

year = {2002},

publisher = {Morgan Kaufmann}

}

### Years of Citing Articles

### OpenURL

### Abstract

This article provides a comprehensive introduction into the field of robotic mapping, with a focus on indoor mapping. It describes and compares various probabilistic techniques, as they are presently being applied to a vast array of mobile robot mapping problems. The history of robotic mapping is also described, along with an extensive list of open research problems.

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Citation Context ... exist that represent environments by large numbers of raw range measurements [60]. An alternative family of algorithms [23, 86, 87, 97, 101] is based on Dempster’s expectation maximization algorith=-=m [24, 65]-=-. These approaches specifically address the correspondence problem in mapping, which is the problem of determining whether sensor measurement recorded at different points in time correspond to the sam... |

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Citation Context ... In the field of robot mapping, the single dominating scheme for integrating such temporal data is known as Bayes filter [45], which is highly related to Kalman filters [49, 64], hidden Markov models =-=[78]-=-, dynamic Bayes networks [82], and partially observable Markov decision processes [48, 59, 66, 93]. The Bayes filter extends Bayes rule to temporal estimation problems. It is a recursive estimator for... |

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Citation Context ...g, the single dominating scheme for integrating such temporal data is known as Bayes filter [45], which is highly related to Kalman filters [49, 64], hidden Markov models [78], dynamic Bayes networks =-=[82]-=-, and partially observable Markov decision processes [48, 59, 66, 93]. The Bayes filter extends Bayes rule to temporal estimation problems. It is a recursive estimator for computing a sequence of post... |

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Citation Context ...eflect the actual robot motion. In the field of robot mapping, the single dominating scheme for integrating such temporal data is known as Bayes filter [45], which is highly related to Kalman filters =-=[49, 64]-=-, hidden Markov models [78], dynamic Bayes networks [82], and partially observable Markov decision processes [48, 59, 66, 93]. The Bayes filter extends Bayes rule to temporal estimation problems. It i... |

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Citation Context ... exist that represent environments by large numbers of raw range measurements [60]. An alternative family of algorithms [23, 86, 87, 97, 101] is based on Dempster’s expectation maximization algorith=-=m [24, 65]-=-. These approaches specifically address the correspondence problem in mapping, which is the problem of determining whether sensor measurement recorded at different points in time correspond to the sam... |

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Citation Context ...ows a sequence of map estimation steps using this approach, for the same data that were used to generate Figure 6. The pose posterior estimate p(st | z t , u t ) is implemented using particle filters =-=[22, 28, 57, 77]-=-, which is a version of the Bayes filter that represents posteriors by samples. The samples can be seen in all three diagrams in Figure 7. When the robot traverses a cyclic environment, it uses the sa... |

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Citation Context ...], of furniture and other objects that move [6, 83]. Many of these technique have counterparts in the computer vision and photogrammetry literature—-a connection that is still somewhat underexploite=-=d [1, 3, 5, 16, 21, 43, 88]. -=-Robot exploration in the context of mapping has also been studied extensively. Today’s approaches are usually greedy, that is, they chose control by greedily maximizing information gain [12, 17, 89,... |

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Citation Context ...ion. The effect is an increase in the location uncertainty of each landmark over time, which subsequently may be counteracted by sensing. Such algorithms are popular in the target tracking literature =-=[4, 68, 85]-=-. Similarly, occupancy grid maps may accommodate certain types of motions, by decaying occupancy over time as discussed in [106]. Extensions of occupancy grids exist that can detect frequently-changin... |

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Citation Context ...mate shows that dependencies are local, an effect that is exploited by some algorithms that build local maps. in Equation (7) can be calculated conveniently using the standard Kalman filter equations =-=[49, 64, 103]: µ ′ t−1 = µt−1 + But Σ ′ t−1 = Σt��-=-�1 + Σcontrol Kt = Σ ′ t−1C T (CΣ ′ t−1C T + Σmeasure) −1 µt = µ ′ t−1 + Kt(o − Cµ ′ t−1) Σt = (I − KtC)Σ ′ t−1 (12) As the reader may verify, these equations are eq... |

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Citation Context ...ows a sequence of map estimation steps using this approach, for the same data that were used to generate Figure 6. The pose posterior estimate p(st | z t , u t ) is implemented using particle filters =-=[22, 28, 57, 77]-=-, which is a version of the Bayes filter that represents posteriors by samples. The samples can be seen in all three diagrams in Figure 7. When the robot traverses a cyclic environment, it uses the sa... |

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Citation Context ...ows a sequence of map estimation steps using this approach, for the same data that were used to generate Figure 6. The pose posterior estimate p(st | z t , u t ) is implemented using particle filters =-=[22, 28, 57, 77]-=-, which is a version of the Bayes filter that represents posteriors by samples. The samples can be seen in all three diagrams in Figure 7. When the robot traverses a cyclic environment, it uses the sa... |

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448 | FastSLAM: A Factored Solution to the Simultaneous Localization
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Citation Context ...as led to a range of extensions that can handle larger number of features, by decomposing the problem into multiple smaller ones [56, 38]. Some techniques, such as the FastSLAM algorithm described in =-=[67]-=-, promise a reduction to O(log K) complexity for certain situation, by using non-classical statistical sampling techniques for robot path estimation [29, 71] along with efficient tree representations.... |

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Citation Context ...ng maps usually describe the location of landmarks, or significant features in the environment, although recent extensions exist that represent environments by large numbers of raw range measurements =-=[60]. -=-An alternative family of algorithms [23, 86, 87, 97, 101] is based on Dempster’s expectation maximization algorithm [24, 65]. These approaches specifically address the correspondence problem in mapp... |

426 | New Extension of the Kalman Filter to Nonlinear Systems
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Citation Context ...earities, Kalman filters approximate the robot motion model using a linear function obtained via Taylor series expansion. The resulting Kalman filter is known as extended Kalman filter [64] (see also =-=[47]-=-), and single motion commands are often approximated by a series of much smaller motion segments, to account for nonlinearities. For most robotic vehicles, such an approximation works well. The result... |

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Citation Context ...ping algorithm was proposed by Chatila and Laumond [15], using sets of polyhedra to describe the geometry of environments. Examples of topological approaches include the work by Matarić [62], Kuipers=-= [53]-=- and many others [17, 18, 34, 52, 76, 87, 86, 102, 105, 108]. Topological maps represent environments as a list of significant places that are connected via arcs. Arcs are usually annotated with infor... |

403 | A probabilistic approach to concurrent mapping and localization for mobile robots
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Citation Context ...o its growing map. Since then, robotic mapping has commonly been referred to as SLAM or CML, which is short for simultaneous localization and mapping [25, 30], and concurrent mapping and localization =-=[56, 101]-=-, respectively. One family of probabilistic approaches employ Kalman filters to estimate the map and the robot location [14, 20, 27, 38, 55, 73, 104]. The resulting maps usually describe the location ... |

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Citation Context ...nt approaches to date generate world-centric maps. Since the 1990s, the field of robot mapping has been dominated by probabilistic techniques. A series of seminal papers by Smith, Self, and Cheeseman =-=[91, 92]-=- introduced a powerful statistical framework for simultaneously solving the mapping problem and the induced problem of localizing the robot relative to its growing map. Since then, robotic mapping has... |

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Citation Context ... environment, whereas topological maps describe the connectivity of different places. An early representative of the former approach was Elfes and Moravec’s important occupancy grid mapping algorith=-=m [31, 32, 69]-=-, which represents maps by fine-grained grids that model the occupied and free space of the environment. This approach has been used in a great number of robotic systems, such as [8, 9, 10, 42, 83, 98... |

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Citation Context ...oral data is known as Bayes filter [45], which is highly related to Kalman filters [49, 64], hidden Markov models [78], dynamic Bayes networks [82], and partially observable Markov decision processes =-=[48, 59, 66, 93]-=-. The Bayes filter extends Bayes rule to temporal estimation problems. It is a recursive estimator for computing a sequence of posterior probability distributions over quantities that cannot be observ... |

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Citation Context ...lgorithm [31, 32, 69], which represents maps by fine-grained grids that model the occupied and free space of the environment. This approach has been used in a great number of robotic systems, such as =-=[8, 9, 10, 42, 83, 98, 106, 107]-=-. An alternative metric mapping algorithm was proposed by Chatila and Laumond [15], using sets of polyhedra to describe the geometry of environments. Examples of topological approaches include the wor... |

302 |
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Citation Context ...nt approaches to date generate world-centric maps. Since the 1990s, the field of robot mapping has been dominated by probabilistic techniques. A series of seminal papers by Smith, Self, and Cheeseman =-=[91, 92]-=- introduced a powerful statistical framework for simultaneously solving the mapping problem and the induced problem of localizing the robot relative to its growing map. Since then, robotic mapping has... |

289 |
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Citation Context ... environment, whereas topological maps describe the connectivity of different places. An early representative of the former approach was Elfes and Moravec’s important occupancy grid mapping algorith=-=m [31, 32, 69]-=-, which represents maps by fine-grained grids that model the occupied and free space of the environment. This approach has been used in a great number of robotic systems, such as [8, 9, 10, 42, 83, 98... |

283 | Markov localization for mobile robots in dynamic environments
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Citation Context ...a map would be quite simple. Conversely, if we already had a map of the environment, there exist computationally elegant and efficient algorithms for determining the robot’s pose at any point in tim=-=e [7, 36]-=-. In combination, however, the problem is much harder. Today, mapping is largely considered the most difficult perceptual problem in robotics. Progress in robot mapping is bound to impact a much broad... |

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Citation Context ... to solve hard correspondence problems. (d) Occupancy grid map built on top of the outcome of the EM mapping algorithm. the correspondence problem. Such large loops are known to be challenging to map =-=[40]-=-. Figure 5c shows the result of applying EM to this data set. The resulting map and path is topologically correct. To illustrate the accuracy of the map, Figures 5b and d show occupancy grid maps buil... |

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Citation Context ...lgorithm [31, 32, 69], which represents maps by fine-grained grids that model the occupied and free space of the environment. This approach has been used in a great number of robotic systems, such as =-=[8, 9, 10, 42, 83, 98, 106, 107]-=-. An alternative metric mapping algorithm was proposed by Chatila and Laumond [15], using sets of polyhedra to describe the geometry of environments. Examples of topological approaches include the wor... |

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Citation Context ...robot poses are on the left as marked by the letters A, B, and C. mapping, short of the full posterior over maps and poses maintained by Kalman filters. A good example are the algorithms described in =-=[40, 97, 100]-=-. Both of these algorithms use the incremental maximum likelihood approach to build maps, but in addition maintain a posterior distribution over robot poses st. This distribution is calculated using t... |

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Citation Context ...s, such as the FastSLAM algorithm described in [67], promise a reduction to O(log K) complexity for certain situation, by using non-classical statistical sampling techniques for robot path estimation =-=[29, 71]-=- along with efficient tree representations. In practice, the number of features is not known a priori. State-of-the-art implementations often grow this list dynamically. To do so, they maintain a list... |

233 |
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Citation Context ...eflect the actual robot motion. In the field of robot mapping, the single dominating scheme for integrating such temporal data is known as Bayes filter [45], which is highly related to Kalman filters =-=[49, 64]-=-, hidden Markov models [78], dynamic Bayes networks [82], and partially observable Markov decision processes [48, 59, 66, 93]. The Bayes filter extends Bayes rule to temporal estimation problems. It i... |

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Citation Context ... 21, 43, 88]. Robot exploration in the context of mapping has also been studied extensively. Today’s approaches are usually greedy, that is, they chose control by greedily maximizing information gai=-=n [12, 17, 89, 105]-=-, sometimes under consideration of safety constraints [37]. However, the topic of robot exploration is beyond the scope of this article, hence will not be addressed any further. 3 The Robotic Mapping ... |

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Citation Context ...oral data is known as Bayes filter [45], which is highly related to Kalman filters [49, 64], hidden Markov models [78], dynamic Bayes networks [82], and partially observable Markov decision processes =-=[48, 59, 66, 93]-=-. The Bayes filter extends Bayes rule to temporal estimation problems. It is a recursive estimator for computing a sequence of posterior probability distributions over quantities that cannot be observ... |

190 | An probabilistic online mapping algorithm for teams of mobile robots,” Int
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Citation Context ...andmarks, or significant features in the environment, although recent extensions exist that represent environments by large numbers of raw range measurements [60]. An alternative family of algorithms =-=[23, 86, 87, 97, 101] i-=-s based on Dempster’s expectation maximization algorithm [24, 65]. These approaches specifically address the correspondence problem in mapping, which is the problem of determining whether sensor mea... |

183 | Optimization of the simultaneous localization and map building algorithm for real time implementation, in
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Citation Context ...lization and mapping [25, 30], and concurrent mapping and localization [56, 101], respectively. One family of probabilistic approaches employ Kalman filters to estimate the map and the robot location =-=[14, 20, 27, 38, 55, 73, 104]-=-. The resulting maps usually describe the location of landmarks, or significant features in the environment, although recent extensions exist that represent environments by large numbers of raw range ... |

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Citation Context ...lization and mapping [25, 30], and concurrent mapping and localization [56, 101], respectively. One family of probabilistic approaches employ Kalman filters to estimate the map and the robot location =-=[14, 20, 27, 38, 55, 73, 104]-=-. The resulting maps usually describe the location of landmarks, or significant features in the environment, although recent extensions exist that represent environments by large numbers of raw range ... |

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Citation Context ...quired locally by the robots may be unknown. This makes it challenging to estimate the relative location of the robots as they acquire local map information. Moreover, if robots can detect each other =-=[35]-=-, complex correspondence problems may arise related to the identification of individual robots. Another dimension worth exploring is the topic of unstructured environments. Most examples in this surve... |

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Citation Context ...he environment. This approach has been used in a great number of robotic systems, such as [8, 9, 10, 42, 83, 98, 106, 107]. An alternative metric mapping algorithm was proposed by Chatila and Laumond =-=[15],-=- using sets of polyhedra to describe the geometry of environments. Examples of topological approaches include the work by Matarić [62], Kuipers [53] and many others [17, 18, 34, 52, 76, 87, 86, 102, ... |

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Citation Context ...lgorithm [31, 32, 69], which represents maps by fine-grained grids that model the occupied and free space of the environment. This approach has been used in a great number of robotic systems, such as =-=[8, 9, 10, 42, 83, 98, 106, 107]-=-. An alternative metric mapping algorithm was proposed by Chatila and Laumond [15], using sets of polyhedra to describe the geometry of environments. Examples of topological approaches include the wor... |

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Citation Context ...oposed by Chatila and Laumond [15], using sets of polyhedra to describe the geometry of environments. Examples of topological approaches include the work by Matarić [62], Kuipers [53] and many others=-= [17, 18, 34, 52, 76, 87, 86, 102, 105, 108]-=-. Topological maps represent environments as a list of significant places that are connected via arcs. Arcs are usually annotated with information on how to navigate from one place to another. However... |

144 | A computationally efficient method for large-scale concurrent mapping and localization
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(Show Context)
Citation Context ...o its growing map. Since then, robotic mapping has commonly been referred to as SLAM or CML, which is short for simultaneous localization and mapping [25, 30], and concurrent mapping and localization =-=[56, 101]-=-, respectively. One family of probabilistic approaches employ Kalman filters to estimate the map and the robot location [14, 20, 27, 38, 55, 73, 104]. The resulting maps usually describe the location ... |

140 |
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Citation Context ... environment, whereas topological maps describe the connectivity of different places. An early representative of the former approach was Elfes and Moravec’s important occupancy grid mapping algorith=-=m [31, 32, 69]-=-, which represents maps by fine-grained grids that model the occupied and free space of the environment. This approach has been used in a great number of robotic systems, such as [8, 9, 10, 42, 83, 98... |

136 | Reinforcement learning in the multi-robot domain
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Citation Context ...and are subjects to local maxima. This article placed considerably little emphasis on multi-robot collaboration during mapping. Clearly, many envisioned operational scenarios involved teams of robots =-=[63, 74, 90]-=-, and using multiple collaborative robot for building maps is clearly a worthwhile research goal. Existing techniques work well if the relative starting positions of all robots are known [12, 89], as ... |

134 | Coordination for multi-robot exploration and mapping
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Citation Context ... 21, 43, 88]. Robot exploration in the context of mapping has also been studied extensively. Today’s approaches are usually greedy, that is, they chose control by greedily maximizing information gai=-=n [12, 17, 89, 105]-=-, sometimes under consideration of safety constraints [37]. However, the topic of robot exploration is beyond the scope of this article, hence will not be addressed any further. 3 The Robotic Mapping ... |

133 | Learning topological maps with weak local odometric information
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Citation Context ...oposed by Chatila and Laumond [15], using sets of polyhedra to describe the geometry of environments. Examples of topological approaches include the work by Matarić [62], Kuipers [53] and many others=-= [17, 18, 34, 52, 76, 87, 86, 102, 105, 108]-=-. Topological maps represent environments as a list of significant places that are connected via arcs. Arcs are usually annotated with information on how to navigate from one place to another. However... |

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Citation Context ...ion. The effect is an increase in the location uncertainty of each landmark over time, which subsequently may be counteracted by sensing. Such algorithms are popular in the target tracking literature =-=[4, 68, 85]-=-. Similarly, occupancy grid maps may accommodate certain types of motions, by decaying occupancy over time as discussed in [106]. Extensions of occupancy grids exist that can detect frequently-changin... |

121 | The SPmap: A probabilistic framework for simultaneous localization and mapping
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Citation Context ...2], who in 1985 through 1990 proposed a mathematical formulation of the approach that is still in widespread use today. In the following years, a number of researchers developed this approach further =-=[13, 14, 30, 26, 27, 56, 73]-=-, most notably a group of researchers located at the University of Sydney in Australia. In the literature, Kalman filter-based mapping algorithms are often referred to as SLAM algorithms, where SLAM s... |

120 |
Mobile Robot Localization and Map Building. A Multisensor Fusion Approach
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Citation Context ...lization and mapping [25, 30], and concurrent mapping and localization [56, 101], respectively. One family of probabilistic approaches employ Kalman filters to estimate the map and the robot location =-=[14, 20, 27, 38, 55, 73, 104]-=-. The resulting maps usually describe the location of landmarks, or significant features in the environment, although recent extensions exist that represent environments by large numbers of raw range ... |

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