## Robotic Mapping: A Survey (2002)

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Venue: | Exploring Artificial Intelligence in the New Millenium |

Citations: | 305 - 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.

### Citations

8919 | Maximum Likelihood from Incomplete Data via the EM-Alogrithm
- Dempster, Laird, et al.
- 1977
(Show Context)
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... |

4567 | A tutorial on hidden Markov models and selected applications in speech recognition
- Rabiner
- 1989
(Show Context)
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... |

4143 |
Artificial Intelligence: A Modern Approach, Pearson Education, 2nd edition
- Russell, Norvig
- 1995
(Show Context)
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... |

2432 |
A New approach to linear filtering and prediction problems. Trans
- Kalman
- 1960
(Show Context)
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... |

1059 |
The EM Algorithm and Extensions
- McLachlan, Krishnan
- 1997
(Show Context)
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... |

970 |
Sequential Monte Carlo Methods in Practice
- Doucet, Frietas, et al.
- 2001
(Show Context)
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... |

952 | Modeling and rendering architecture from photographs: a hybrid geometry- and image-based approach
- Debevec, Taylor, et al.
- 1996
(Show Context)
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,... |

892 | Planning and acting in partially observable stochastic domains
- Kaelbing, Littman, et al.
- 1995
(Show Context)
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... |

771 |
Tracking and data association
- Bar-Shalom, Fortmann
- 1988
(Show Context)
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... |

759 | An introduction to the Kalman Filter
- Welch, Bishop
- 2004
(Show Context)
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... |

667 | Monte carlo localization for mobile robots
- Dellaert, Fox, et al.
- 1999
(Show Context)
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... |

559 | Filtering via simulation: auxiliary particle filters
- Pitt, Shepherd
- 1999
(Show Context)
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... |

502 | Sequential Monte Carlo methods for dynamic systems
- Liu, Chen
- 1998
(Show Context)
Citation Context |

487 | A new extension of the Kalman filter to nonlinear systems
- Julier, Uhlmann
- 1997
(Show Context)
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... |

475 | FastSLAM: A factored solution to simultaneous localization and mapping
- Montemerlo, Thrun, et al.
- 2002
(Show Context)
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.... |

459 | Globally consistent range scan alignment for environment mapping. Autonomous Robots 4:333–349
- Lu, Milios
- 1997
(Show Context)
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... |

430 | A probabilistic approach to concurrent mapping and localization for mobile robots. Machine Learning/Autonomous Robots joint issue
- Thrun, Burgard, et al.
- 1998
(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 ... |

429 | A robot exploration and mapping strategy based on a semantic hierarchy of spatial representations
- Kuipers, Byun
- 1991
(Show Context)
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... |

413 |
Estimating uncertain spatial relationships in robotics
- Smith, Self, et al.
- 1988
(Show Context)
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... |

380 | The vector field histogram—fast obstacle avoidance for mobile robots
- Borenstein, Koren
- 1991
(Show Context)
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... |

360 |
Sensor fusion in certainty grids for mobile robots
- Moravec
- 1988
(Show Context)
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... |

350 |
The optimal control of partially observable markov decision processes over the infinite horizon : Discounted cost. Operations Research 12:282–304
- Sondik
- 1978
(Show Context)
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... |

321 |
On the representation and estimation of spatial uncertainty
- Smith, Cheeseman
- 1987
(Show Context)
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... |

308 |
Sonar-based real-world mapping and navigation
- Elfes
- 1987
(Show Context)
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... |

308 | Markov Localization for Mobile Robots in Dynamic Environments
- Fox, Burgard, et al.
- 1999
(Show Context)
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... |

304 | Incremental mapping of large cyclic environments
- Gutmann, Konolige
- 2000
(Show Context)
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... |

286 | Experiences with a Interactive Museum Tour-Guide Robot.” Artificial Intelligence 00(1-53
- Burgard, Cremers, et al.
- 1999
(Show Context)
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... |

277 | D.: A Real-Time Algorithm for Mobile Robot Mapping With Applications to Multi-robot and 3D
- Thrun, Burgard, et al.
- 2000
(Show Context)
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... |

267 | Rao-Blackwellised particle filtering for dynamic Bayesian networks
- Doucet, Freitas, et al.
- 2000
(Show Context)
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... |

260 |
Stochastic Models, Estimation, and Control, Volume 1
- Maybeck
- 1979
(Show Context)
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... |

231 | Collaborative Multi-Robot Exploration
- Burgard
- 2000
(Show Context)
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 ... |

204 |
A survey of partially observable Markov decision processes: Theory, models, and algorithms
- Monahan
- 1982
(Show Context)
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... |

202 | A probabilistic online mapping algorithm for teams of mobile robots
- Thrun
- 2001
(Show Context)
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... |

193 | A Probabilistic Approach to Collaborative Multirobotic
- Fox
(Show Context)
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... |

192 | Optimization of the simultaneous localization and map-building algorithm for real-time implementation
- Guivant, Nebot
- 2001
(Show Context)
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 ... |

189 |
Position referencing and consistent world modeling for mobile robots
- Chatila, Laumond
- 1985
(Show Context)
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, ... |

189 |
Dynamic map building for an autonomous mobile robot
- Leonard, Durrant-Whyte, et al.
- 1992
(Show Context)
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 ... |

188 | A survey of algorithmic methods for partially observed Markov decision processes - Lovejoy - 1991 |

161 | Probabilistic algorithms and the interactive museum tour-guide robot minerva
- Thrun, Beetz, et al.
(Show Context)
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... |

158 |
Topological mapping for mobile robots using a combination of sonar and vision sensing
- Kortenkamp, Weymouth
- 1994
(Show Context)
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... |

148 | A computationally efficient method for large-scale concurrent mapping and localization
- Leonard, Feder
- 1999
(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 ... |

147 |
Occupancy Grids: A probabilistic framework for robot perception and navigation
- Elfes
- 1989
(Show Context)
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... |

144 | Coordination for multi-robot exploration and mapping
- Simmons, Apfelbaum, et al.
- 2000
(Show Context)
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 ... |

143 | Reinforcement learning in the multirobot domain
- Mataric
- 1996
(Show Context)
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 ... |

139 | A distributed model for mobile robot environment-learning and navigation - Matarić - 1990 |

137 | Learning topological maps with weak local odometric information
- Shatkay, Kaelbling
- 1997
(Show Context)
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... |

133 | The SP map: A probabilistic framework for simultaneous localization and map building
- Castellanos, Montiel, et al.
- 1999
(Show Context)
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... |

132 | Tracking Multiple Moving Targets with a Mobile Robot using Particle Filters and Statistical Data Association
- Schulz, Burgard, et al.
- 2001
(Show Context)
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... |

128 |
Tardós, Mobile Robot Localization and Map Building: A Multisensor Fusion Approach
- Castellanos, D
- 1999
(Show Context)
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 ... |

113 | The Mobile Robot RHINO
- Buhmann, Burgard, et al.
- 1995
(Show Context)
Citation Context |