Position referencing and consistent world modeling for mobile robots
25 Mar 1985-Vol. 2, pp 138-145
TL;DR: The approach proposed in this paper relies on the use of a multisensory system, favo ring of the data collected by the more accurate sensor in a given situation, averaging of different but consistent measurements of the same entity weighted with their associated uncertainties.
Abstract: In order to understand its environment, a mobile robot should be able to model consistently this environment, and to locate itself correctly. One major difficulty to be solved is the inaccuracies introduced by the sensors. The approach proposed in this paper to cope with this problem relies on 1) defining general principles to deal with uncertainties : the use of a multisensory system, favo ring of the data collected by the more accurate sensor in a given situation, averaging of different but consistent measurements of the same entity weighted with their associated uncertainties, and 2) a methodology enabling a mobile robot to define its own reference landmarks while exploring its environment. These ideas are presented together with an example of their application on the mobile robot HILARE.
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TL;DR: This paper describes the simultaneous localization and mapping (SLAM) problem and the essential methods for solving the SLAM problem and summarizes key implementations and demonstrations of the method.
Abstract: This paper describes the simultaneous localization and mapping (SLAM) problem and the essential methods for solving the SLAM problem and summarizes key implementations and demonstrations of the method. While there are still many practical issues to overcome, especially in more complex outdoor environments, the general SLAM method is now a well understood and established part of robotics. Another part of the tutorial summarized more recent works in addressing some of the remaining issues in SLAM, including computation, feature representation, and data association
3,760 citations
Cites background from "Position referencing and consistent..."
...The formulation section introduces the structure the SLAM problem in now standard Bayesian form, and explains the evolution of the SLAM process....
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01 Jun 2001
TL;DR: The paper proves that a solution to the SLAM problem is indeed possible and discusses a number of key issues raised by the solution including suboptimal map-building algorithms and map management.
Abstract: The simultaneous localization and map building (SLAM) problem asks if it is possible for an autonomous vehicle to start in an unknown location in an unknown environment and then to incrementally build a map of this environment while simultaneously using this map to compute absolute vehicle location. Starting from estimation-theoretic foundations of this problem, the paper proves that a solution to the SLAM problem is indeed possible. The underlying structure of the SLAM problem is first elucidated. A proof that the estimated map converges monotonically to a relative map with zero uncertainty is then developed. It is then shown that the absolute accuracy of the map and the vehicle location reach a lower bound defined only by the initial vehicle uncertainty. Together, these results show that it is possible for an autonomous vehicle to start in an unknown location in an unknown environment and, using relative observations only, incrementally build a perfect map of the world and to compute simultaneously a bounded estimate of vehicle location. The paper also describes a substantial implementation of the SLAM algorithm on a vehicle operating in an outdoor environment using millimeter-wave radar to provide relative map observations. This implementation is used to demonstrate how some key issues such as map management and data association can be handled in a practical environment. The results obtained are cross-compared with absolute locations of the map landmarks obtained by surveying. In conclusion, the paper discusses a number of key issues raised by the solution to the SLAM problem including suboptimal map-building algorithms and map management.
2,834 citations
Cites methods from "Position referencing and consistent..."
...At the same time Ayache and Faugeras [14] and Chatila and Laumond [15] were undertaking early work in visual navigation of mobile robots using Kalman filter-type algorithms....
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...[15] R. Chatila and J-P Laumond, “Position referencing and consistant world modeling for mobile robots,” inProc....
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Book•
01 Jan 2003TL;DR: This article provides a comprehensive introduction into the field of robotic mapping, with a focus on indoor mapping, and describes and compares various probabilistic techniques, as they are presently being applied to a vast array of mobile robot mapping problems.
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 detailed, along with an extensive list of open research problems.
1,584 citations
Cites background or methods from "Position referencing and consistent..."
...In mobile robotics, the idea of representing maps by simple geometric shapes can be traced back to a paper by Chatila and Laumond [15], who proposed to represent 2D maps by collection of lines rather than grids....
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...An alternative metric mapping algorithm was proposed by Chatila and Laumond [15], using sets of polyhedra to describe the geometry of environments....
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TL;DR: The problem of consistent registration of multiple frames of measurements (range scans), together with therelated issues of representation and manipulation of spatialuncertainties are studied, to maintain all the local frames of data as well as the relative spatial relationships between localframes.
Abstract: A robot exploring an unknown environment may need to build a world model from sensor measurements. In order to integrate all the frames of sensor data, it is essential to align the data properly. An incremental approach has been typically used in the past, in which each local frame of data is aligned to a cumulative global model, and then merged to the model. Because different parts of the model are updated independently while there are errors in the registration, such an approach may result in an inconsistent model.
In this paper, we study the problem of consistent registration of multiple frames of measurements (range scans), together with the related issues of representation and manipulation of spatial uncertainties. Our approach is to maintain all the local frames of data as well as the relative spatial relationships between local frames. These spatial relationships are modeled as random variables and are derived from matching pairwise scans or from odometry. Then we formulate a procedure based on the maximum likelihood criterion to optimally combine all the spatial relations. Consistency is achieved by using all the spatial relations as constraints to solve for the data frame poses simultaneously. Experiments with both simulated and real data will be presented.
1,452 citations
Cites background from "Position referencing and consistent..."
...The first project that systematically studied the consistency issue in dynamic world modeling is the HILARE project (Chatila and Laumond, 1985)....
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01 Jan 1987
TL;DR: The method presented can be generalized to six degrees offreedom and provides a practical means of mating the relationships among objects, as well as estimating the uncertainty associated with the relationships.
1,421 citations
References
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Proceedings Article•
20 Aug 1979TL;DR: The current state of HILARE: a modular progressively-built mobile robot aimed at general robotics research is described, which comprises of local mini and micro processors coupled with a remote time-shared system acting as a consulting facility.
Abstract: This paper describes the current state of HILARE: a modular progressively-built mobile robot aimed at general robotics research. The computer organization comprises of local mini and micro processors coupled with a remote time-shared system acting as a consulting facility. A multi-level decision-making system is presented with world models, inference rules, and algorithms particular to each level. The navigation planner uses a geometric model wherein 2-space is partitioned into polygonal areas based on perceptual and/or initial information. A cost function is proposed which provides support for optimal or E-optimal path finding.
139 citations
Proceedings Article•
01 Jul 1982
93 citations
Proceedings Article•
08 Aug 1983
TL;DR: The mathematical structuring tool used is the decomposition of a graph into its k-connected components, which allows the robot to improve navigation procedures and to recognize some concepts, such as a door, a room, or a corridor.
Abstract: We present here a method for providing a mobile robot with learning capabilities. The method is based on a model of the environment with several hierarchical levels organized by degree of abstraction. The mathematical structuring tool used is the decomposition of a graph into its k-connected components (k=2 and k=3). This structure allows the robot to improve navigation procedures and to recognize some concepts, such as a door, a room, or a corridor.
46 citations