S. Thrun. Robotic mapping: A survey. In G. Lakemeyer and B. Nebel, editors, Exploring Artificial Intelligence in the New Millenium. Morgan Kaufmann, 2002. Home/Search Document Details and Download
Summary Related Articles Check |
This paper is cited in the following contexts:
Thin Junction Tree Filters for Simultaneous Localization and.. - Paskin (19 citations) (Correct)
.... Simultaneous Localization and Mapping (SLAM) where a robot navigating in an unknown environment must incrementally build a map of its surroundings and localize itself within that map has attracted significant attention because it is required by many applications in mobile robotics [Thrun, 2002] . Typically the environment is idealized so that it consists of an unknown number of stationary landmarks ; for example, in a given SLAM application these landmarks may be low level visual features or structural features such as walls and corners. SLAM can then be viewed as the problem of ....
....TJTF to other SLAM filters and Section 7 concludes. A companion technical report contains proofs of all propositions as well as additional background, analysis, and experiments [Paskin, 2002] 1. 1 Related work Significant interest in the SLAM complexity problem has led to a number of approaches [Thrun, 2002] . For example, there are several submap approaches that decompose the problem into a set of small mapping problems yielding a blockdiagonal landmark covariance matrix. These techniques can achieve constant time complexity, but converge slowly because information cannot pass between the submaps. ....
[Article contains additional citation context not shown here]
S. Thrun. Robotic mapping: A survey. In G. Lakemeyer and B. Nebel, editors, Exploring Artificial Intelligence in the New Millenium. Morgan Kaufmann, 2002.
Compact Encoding of Robot-Generated 3D Maps for Efficient .. - Kaess, Arkin, Rossignac (Correct)
....are smaller and cheaper, and additionally provide texture maps for more realistic 3D models. Processing vision data, however, is usually very resource consuming and can often not be done in real time, while laser data directly yields a 3D model. The accuracy of models acquired with range finders [12] is typically higher than of those acquired with stereo vision [6] Although vision systems not only provide geometry, but also color, which may be used as texture to enhance the acquired model, the onboard processing and transmission of color information may be too expensive in mobile situations. ....
....data using the probabilistic method of expectation maximization to reduce the amount of data. Points which are not part of such a plane remain in the model, allowing for non flat surfaces with the drawback of increased complexity. An omni cam provides texture maps for realistic visualization. [12] gives a comprehensive overview of related work. There is a vast amount of literature on compression available. Our search focused on standard text based compression, lossless compression of gray scale images, and wavelets. Text based compression schemes are typically based on building a ....
[Article contains additional citation context not shown here]
S. Thrun, "Robotic Mapping: A Survey", In G. Lakemeyer and B. Nebel, editors, Exploring Artificial Intelligence in the New Millenium, 2002.
A Probabilistic Language based upon Sampling Functions - Sungwoo Park Frank Self-citation (Thrun) (Correct)
No context found.
S. Thrun. Robotic mapping: A survey. In G. Lakemeyer and B. Nebel, editors, Exploring Artificial Intelligence in the New Millenium. Morgan Kaufmann, 2002.
A Probabilistic Language based upon Sampling Functions - Sungwoo Park Frank Self-citation (Thrun) (Correct)
No context found.
S. Thrun. Robotic mapping: A survey. In G. Lakemeyer and B. Nebel, editors, Exploring Artificial Intelligence in the New Millenium. Morgan Kaufmann, 2002.
A Probabilistic Language based upon Sampling Functions - Sungwoo Park Frank (2004) Self-citation (Thrun) (Correct)
No context found.
S. Thrun. Robotic mapping: A survey. In G. Lakemeyer and B. Nebel, editors, Exploring Artificial Intelligence in the New Millenium. Morgan Kaufmann, 2002.
A Programming Language for Probabilistic Computation - Park (2005) Self-citation (Thrun) (Correct)
No context found.
S. Thrun. Robotic mapping: A survey. In G. Lakemeyer and B. Nebel, editors, Exploring Artificial Intelligence in the New Millenium. Morgan Kaufmann, 2002.
FastSLAM: An Efficient Solution to the.. - Thrun.. (2004) (2 citations) Self-citation (Thrun) (Correct)
No context found.
S. Thrun. Robotic mapping: A survey. In G. Lakemeyer and B. Nebel, editors, Exploring Artificial Intelligence in the New Millenium. Morgan Kaufmann, 2002.
A Probabilistic Language based upon Sampling Functions - Park, Pfenning, Thrun (2004) Self-citation (Thrun) (Correct)
No context found.
S. Thrun. Robotic mapping: A survey. In G. Lakemeyer and B. Nebel, editors, Exploring Artificial Intelligence in the New Millenium. Morgan Kaufmann, 2002.
FastSLAM: A Factored Solution to the Simultaneous Localization.. - Montemerlo (2003) (44 citations) Self-citation (Thrun) (Correct)
No context found.
S. Thrun. Robotic mapping: A survey. In G. Lakemeyer and B. Nebel, editors, Exploring Artificial Intelligence in the New Millenium. Morgan Kauffmann, 2002. to appear.
Scan Alignment and 3-D Surface Modeling with a Helicopter.. - Thrun, Diel, Hähnel (2003) (2 citations) Self-citation (Thrun) (Correct)
.... recent years, a number of research teams have developed robotic systems for mapping indoor [12, 20] and outdoor environments [9] Since sensing is usually confined to the immediate vicinity of the vehicle, active sensors such as sonars and laser range finders have become the technology of choice [19] albeit some notable exception using passive cameras [ 1 5] For the problem of acquiring accurate maps of outdoor terrain, ground vehicles are limited in two aspects: First, the ground has to be traversable by the vehicle itself. Many environments are cluttered with obstacles that are difficult ....
....A second extension concerns the limitation that surfaces are only sensed once. To enable the vehicle to integrate data from multiple fly overs would require a mechanism for establishing correspondence to previously mapped terrain. While a number of techniques exist that offer this capability [19] it is unclear whether they can be executed in realtime on a helicopter platform. Acknowledgments The authors gratefully acknowledge the donation of two Stayton boards by Intel. This research is sponsored by by DARPA s MARS Program (contracts N66001 01 C 6018 and NBCH10200141, which is also ....
S. Thrun. Robotic mapping: A survey. In G. Lakemeyer and B. Nebel, editors, E7)loring Artificiul Intelligence in the New Millenium. Morgan Kaufmann, 2002. to appeau
Real Time Data Association for FastSLAM - Nieto, Guivant, Nebot (2003) (2 citations) Self-citation (Thrun) (Correct)
....problem from a a probabilistic point of view. SLAM algorithms commonly compute the probability ## # # (1) where # # is the robot pose vector at time #, # is the map state vector, # is the set of observations received until time #, # are the control inputs and # # the initial position [18]. This equation describes the joint posterior density of the robot pose and map at time #, given the initial robot pose, and all the observations and control inputs up to time #. In probabilistic terms, the SLAM problem is a Markov process. This means that the state at time # # # embodies all the ....
S. Thrun, "Robotic mapping: A survey," in Exploring Artificial Intelligence in the New Millenium, G. Lakemeyer and B. Neberl, Eds. Morgan Kaufmann, 2002, to appear.
Simultaneous Mapping and Localization With Sparse.. - Thrun, Koller.. (2002) (9 citations) Self-citation (Thrun) (Correct)
.... of the update rule, we observe that Bayes rule enables us to factor the desired posterior (2) into the following product: # t , z ) p(# t = p(z t # t ) p(# t ) 12) The second step of this derivation exploited common (and obvious) independences in SLAM problems [29]. For the time being, we assume that p(# t ) is represented by b t . Those will be discussed in the next section, where robot motion will be addressed. The key question addressed in this section, thus, concerns the representation of the probability distribution p(z t # t ) and the ....
....become linked directly. To derive the update rule, we begin with a Bayesian description of robot motion. Updating a filter based on robot motion motion involves the calculation of the following posterior: # t 1 , z ) p(# t 1 Exploiting the common SLAM independences [29] leads to # t 1 , u t ) p(# t 1 The term p(# t 1 ) is the posterior at time t 1, represented by H t 1 and b t 1 . Our concern will therefore be with the remaining term p(# t # t 1 , u t ) which characterizes robot motion in probabilistic terms. Similar to the measurement ....
S. Thrun. Robotic mapping: A survey. In G. Lakemeyer and B. Neberl, editors, Exploring Artificial Intelligence in the New Millenium. Morgan Kaufmann, 2002. to appear. 20
Simultaneous Mapping and Localization With Sparse Extended.. - Thrun (2002) (9 citations) Self-citation (Thrun) (Correct)
.... of the update rule, we observe that Bayes rule enables us to factor the desired posterior (2) into the following product: # t , z ) p(# t = p(z t # t ) p(# t ) 12) The second step of this derivation exploited common (and obvious) independences in SLAM problems [26]. For the time being, we assume that p(# t ) is represented by b t . Those will be discussed in the next section, where robot motion will be addressed. The key question addressed in this section, thus, concerns the representation of the probability distribution p(z t # t ) and the ....
....become linked directly. To derive the update rule, we begin with a Bayesian description of robot motion. Updating a filter based on robot motion motion involves the calculation of the following posterior: # t 1 , z ) p(# t 1 Exploiting the common SLAM independences [26] leads to # t 1 , u t ) p(# t 1 The term p(# t 1 ) is the posterior at time t 1, represented by H t 1 and b t 1 . Our concern will therefore be with the remaining term p(# t # t 1 , u t ) which characterizes robot motion in probabilistic terms. Similar to the measurement ....
S. Thrun. Robotic mapping: A survey. In Exploring Artificial Intelligence in the New Millenium. Morgan Kaufmann, 2002.
Postrob: a behaviour-based post deliverer - Lazkano Astigarraga Martnez-Otzeta (Correct)
No context found.
Thrun, S. (2002). Robotic mapping: a survey. Technical Report CMU-CS-02-111, School of Computer Science. Carnagie Mellon University.
Laser-Based Logical Sensors for Improved Mapping and Localization - Skrzypczynski (Correct)
No context found.
S. Thrun, Robotic Mapping: A Survey, Tech. Rep., CMUCS -02-111, 2002.
The Sensor Selection Problem for Bounded Uncertainty Sensing.. - Isler, Bajcsy (2005) (1 citation) (Correct)
No context found.
S. Thrun, "Robotic mapping: A survey," in Exploring Artificial Intelligence in the New Millenium, G. Lakemeyer and B. Nebel, Eds. Morgan Kaufmann, 2002.
Adapting Proposal Distributions for Accurate, - Efficient Mobile Robot (Correct)
No context found.
S. Thrun, "Robotic mapping: A survey," in Exploring Artificial Intelligence in the New Millenium, G. Lakemeyer and B. Nebel, Eds. Morgan Kaufmann, 2002.
Topics in Probabilistic Location Estimation in.. - Kontkanen.. (2004) (Correct)
No context found.
S. Thrun. Robotic Mapping: A Survey. In Exploring Artificial Intelligence in the New Millennium, pages 1--35. Morgan Kaufmann Publishers, San Francisco, 2003.
Probabilistic Methods For Location Estimation In.. - Kontkanen.. (2004) (Correct)
No context found.
Thrun, S., 2003, Robotic mapping: A Survey, in: Exploring Artificial Intelligence in the New Millennium, Morgan Kaufmann Publishers, San Francisco, pp. 1--35.
Loop-Closing and Planarity in Topological Map-Building - Savelli, al. (2004) (Correct)
No context found.
S. Thrun, "Robotic mapping: A survey," in Exploring Artificial Intelligence in the New Millenium, G. Lakemeyer and B. Nebel, Eds. Morgan Kaufmann, 2002.
Topics In Probabilistic Location Estimation In.. - Kontkanen.. (2004) (Correct)
No context found.
S. Thrun. Robotic Mapping: A Survey. In Exploring Artificial Intelligence in the New Millennium, pages 1-- 35. Morgan Kaufmann Publishers, San Francisco, 2003.
Probabilistic Methods for Location Estimation in.. - Kontkanen.. (2004) (Correct)
No context found.
Thrun, S., 2003, Robotic mapping: A Survey, in: Exploring Artificial Intelligence in the New Millennium, Morgan Kaufmann Publishers, San Francisco, pp. 1--35.
Topological Mapping of Ambiguous Space: Combining Qualitative . . . - Savelli (2005) (Correct)
No context found.
S. Thrun. Robotic mapping: A survey. In G. Lakemeyer and B. Nebel, editors, Exploring Artificial Intelligence in the New Millenium. Morgan Kaufmann, 2002.
On Map Merging - Stefano Carpin Andreas (2005) (Correct)
No context found.
S. Thrun, Robotic mapping: A survey, in: G. Lakemeyer, B. Nebel (Eds.), Exploring Artificial Intelligence in the New Millenium, Morgan Kaufmann, 2002.
Extracting Drivable Surfaces - In Outdoor Slam (2006) (Correct)
No context found.
S. Thrun. Robotic mapping: A survey. In G. Lakemeyer and B. Nebel, editors, Exploring Artificial Intelligence in the New Millenium. Morgan Kaufmann, 2002.
Topological Mapping with Multiple Visual Manifolds - Grudic, Mulligan (2005) (Correct)
No context found.
S. Thrun. Robotic mapping: A survey. In G. Lakemeyer and B. Nebel, editors, Exploring Artificial Intelligence in the New Millenium. Morgan Kaufmann, 2002.
Steps Towards Safe Navigation in Open and Dynamic.. - Laugier, Petti.. (2005) (Correct)
No context found.
S. Thrun. Robotic mapping: A survey. In Exploring Artificial Intelligence in the New Millenium. Morgan Kaufmann, 2002.
Multi-Hierarchical Semantic Maps for Mobile Robotics - Galindo, Saffiotti.. (2005) (Correct)
No context found.
S. Thrun. Robotic mapping: A survey. In G. Lakemeyer and B. Nebel, editors, Exploring Artificial Intelligence in the New Millenium. Morgan Kaufmann, 2002.
The Normal Distributions Transform: . . . - Biber (2003) (Correct)
No context found.
S. Thrun. Robotic mapping: A survey. In G. Lakemeyer and B. Nebel, editors, ######### ######### ############ ## ### ### #########. Morgan Kaufmann, 2002.
The Sensor Selection Problem for Bounded Uncertainty Sensing.. - Isler, Bajcsy (2005) (1 citation) (Correct)
No context found.
S. Thrun, "Robotic mapping: A survey," in Exploring Artificial Intelligence in the New Millenium, G. Lakemeyer and B. Nebel, Eds. Morgan Kaufmann, 2002, to appear.
Modeling the Static and the Dynamic Parts of the.. - Montesano, Minguez.. (2005) (1 citation) (Correct)
No context found.
S. Thrun. Robotic mapping: A survey. In G. Lakemeyer and B. Nebel, editors, Exploring Artificial Intelligence in the New Millenium. Morgan Kaufmann, 2002.
A Lie Algebraic Approach for Consistent Pose Registration for.. - Agrawal (Correct)
No context found.
S. Thrun, "Robotic mapping: A survey," in Exploring Artificial Intelligence in the New Millenium, G. Lakemeyer and B. Nebel, Eds. Morgan Kaufmann, 2002.
Hierarchies of Probabilistic Models of Space for Mobile.. - Diard, Bessiere, Mazer (2003) (Correct)
No context found.
Sebastian Thrun. Robotic mapping : A survey. Technical Report CMU-CS-02-111, Carnegie Mellon University, February 2002.
Hierarchies of Probabilistic Models of Navigation: the.. - Diard, Bessiere, Mazer (2004) (Correct)
No context found.
S. Thrun, "Robotic mapping: A survey," Carnegie Mellon University, Technical Report CMU-CS-02-111, February 2002.
A Multilevel Relaxation Algorithm for Simultaneous.. - Frese, Larsson, Duckett (3 citations) (Correct)
No context found.
S. Thrun, "Robotics mapping: A survey," School of Computer Science, Carnegie Mellon University, Tech. Rep., Feb. 2002.
Algorithms for Distributed and Mobile Sensing - Isler (2004) (Correct)
No context found.
S. Thrun. Robotic mapping: A survey. In G. Lakemeyer and B. Nebel, editors, Exploring Artificial Intelligence in the New Millenium. Morgan Kaufmann, 2002. to appear.
Computational Complexities of Honey-pot Searching with.. - DasGupta, Hespanha.. (2003) (Correct)
No context found.
S. Thrun. Robotic Mapping: A Survey, in Exploring Artificial Intelligence in the New Millennium, G. Lakemeyer and B. Nebel (eds.), Morgan Kaufmann, 2002.
Towards Mapping Dynamic Environments - Denis Wolf Gaurav (2003) (Correct)
No context found.
Thrun, S., "Robotic Mapping: A Survey," In G. Lakemeyer and B. Neberl, editors, Exploring Artificial Intelligence in the New Millenium. Morgan Kaufmann, 2002.
Online Simultaneous Localization and Mapping in Dynamic.. - Wolf, al. (2004) (Correct)
No context found.
Thrun, S., "Robotic Mapping: A Survey," In G. Lakemeyer and B. Neberl, editors, Exploring Artificial Intelligence in the New Millenium. Morgan Kaufmann, 2002.
Inference in the Space of Topological Maps: An MCMC-based.. - Ranganathan, Dellaert (Correct)
No context found.
S. Thrun, "Robotic mapping: A survey," in Exploring Artificial Intelligence in the New Millenium (G. Lakemeyer and B. Nebel, eds.), Morgan Kaufmann, 2002. To appear, also available as Carnegie Mellon TR CMU-CS-02-111.
The Normal Distribution Transform: A New Approach to Laser Scan.. - Biber (2003) (12 citations) (Correct)
No context found.
S. Thrun. Robotic mapping: A survey. In G. Lakemeyer and B. Nebel, editors, ######### ######### ############ ## ### ### #########. Morgan Kaufmann, 2002.
The SDR Experience: Experiments with a Large-Scale.. - Howard, Parker, Sukhatme (2004) (1 citation) (Correct)
No context found.
S. Thrun. Robotic mapping: A survey. In G. Lakemeyer and B. Nebel, editors, Exploring ArtificialIntelligence in the New Millenium. Morgan Kaufmann, 2002.
Thin Junction Tree Filters for Simultaneous Localization and.. - Paskin (2003) (19 citations) (Correct)
No context found.
S. Thrun. Robotic mapping: A survey. In G. Lakemeyer and B. Nebel, editors, Exploring Artificial Intelligence in the New Millenium. Morgan Kaufmann, 2002.
Towards Autonomous 3D Mapping in Urban Environments - Howard, Wolf, Sukhatme (Correct)
No context found.
S. Thrun, "Robotic mapping: A survey," in Exploring Artificial Intelligence in the New Millenium, G. Lakemeyer and B. Nebel, Eds. Morgan Kaufmann, 2002.
Online articles have much greater impact More about CiteSeer.IST Add search form to your site Submit documents Feedback
CiteSeer.IST - Copyright Penn State and NEC