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76
The Spatial Semantic Hierarchy
- Artificial Intelligence
, 2000
"... The Spatial Semantic Hierarchy is a model of knowledge of large-scale space consisting of multiple interacting representations, both qualitative and quantitative. The SSH is inspired by the properties of the human cognitive map, and is intended to serve both as a model of the human cognitive map and ..."
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Cited by 339 (35 self)
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The Spatial Semantic Hierarchy is a model of knowledge of large-scale space consisting of multiple interacting representations, both qualitative and quantitative. The SSH is inspired by the properties of the human cognitive map, and is intended to serve both as a model of the human cognitive map and as a method for robot exploration and map-building. The multiple levels of the SSH express states of partial knowledge, and thus enable the human or robotic agent to deal robustly with uncertainty during both learning and problem-solving. The control level represents useful patterns of sensorimotor interaction with the world in the form of trajectory-following and hill-climbing control laws leading to locally distinctive states. Local geometric maps in local frames of reference can be constructed at the control level to serve as observers for control laws in particular neighborhoods. The causal level abstracts continuous behavior among distinctive states into a discrete model ...
Incremental mapping of large cyclic environments
- In Computational Intelligence in Robotics and Automation
, 1999
"... Mobile robots can use geometric or topological maps of their environment to navigate reliably. Automatic creation of such maps is still an unrealized goal, especially in environments that have large cyclical structures. Drawing on recent techniques of global registration and correlation, we present ..."
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Cited by 332 (19 self)
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Mobile robots can use geometric or topological maps of their environment to navigate reliably. Automatic creation of such maps is still an unrealized goal, especially in environments that have large cyclical structures. Drawing on recent techniques of global registration and correlation, we present a method, called Local Registration and Global Correlation (LRGC), for reliable reconstruction of consistent global maps from dense range data. The method is attractive because it is incremental, producing an updated map with every new sensor input; and runs in constant time independent of the size of the map (except when closing large cycles). A real-time implementation and results are presented for several indoor environments. 1.
Experiences with an Interactive Museum Tour-Guide Robot
, 1998
"... This article describes the software architecture of an autonomous, interactive tour-guide robot. It presents a modular and distributed software architecture, which integrates localization, mapping, collision avoidance, planning, and various modules concerned with user interaction and Web-based telep ..."
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Cited by 329 (72 self)
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This article describes the software architecture of an autonomous, interactive tour-guide robot. It presents a modular and distributed software architecture, which integrates localization, mapping, collision avoidance, planning, and various modules concerned with user interaction and Web-based telepresence. At its heart, the software approach relies on probabilistic computation, on-line learning, and any-time algorithms. It enables robots to operate safely, reliably, and at high speeds in highly dynamic environments, and does not require any modifications of the environment to aid the robot's operation. Special emphasis is placed on the design of interactive capabilities that appeal to people's intuition. The interface provides new means for human-robot interaction with crowds of people in public places, and it also provides people all around the world with the ability to establish a "virtual telepresence" using the Web. To illustrate our approach, results are reported obtained in mid-...
The interactive museum tour-guide robot
, 1998
"... This paper describes the software architecture of an autonomous tour-guide/tutor robot. This robot was recently deployed in the “Deutsches Museum Bonn, ” were it guided hundreds of visitors through the museum during a six-day deployment period. The robot’s control software integrates low-level proba ..."
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Cited by 225 (32 self)
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This paper describes the software architecture of an autonomous tour-guide/tutor robot. This robot was recently deployed in the “Deutsches Museum Bonn, ” were it guided hundreds of visitors through the museum during a six-day deployment period. The robot’s control software integrates low-level probabilistic reasoning with high-level problem solving embedded in first order logic. A collection of software innovations, described in this paper, enabled the robot to navigate at high speeds through dense crowds, while reliably avoiding collisions with obstacles—some of which could not even be perceived. Also described in this paper is a user interface tailored towards non-expert users, which was essential for the robot’s success in the museum. Based on these experiences, this paper argues that time is ripe for the development of AI-based commercial service robots that assist people in everyday life.
Practical robust localization over large-scale 802.11 wireless networks
- in Proceedings of the 10th Annual International Conference on Mobile Computing and Networking (MOBICOM
"... We demonstrate a system built using probabilistic techniques that allows for remarkably accurate localization across our entire office building using nothing more than the built-in signal intensity meter supplied by standard 802.11 cards. While prior systems have required significant investments of ..."
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Cited by 189 (2 self)
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We demonstrate a system built using probabilistic techniques that allows for remarkably accurate localization across our entire office building using nothing more than the built-in signal intensity meter supplied by standard 802.11 cards. While prior systems have required significant investments of human labor to build a detailed signal map, we can train our system by spending less than one minute per office or region, walking around with a laptop and recording the observed signal intensities of our building’s unmodified base stations. We actually collected over two minutes of data per office or region, about 28 man-hours of effort. Using less than half of this data to train the localizer, we can localize a user to the precise, correct location in over 95 % of our attempts, across the entire building. Even in the most pathological cases, we almost never localize a user any more distant than to the neighboring office. A user can obtain this level of accuracy with only two or three signal intensity measurements, allowing for a high frame rate of localization results. Furthermore, with a brief calibration period, our system can be adapted to work with previously unknown user hardware. We present results demonstrating the robustness of our system against a variety of untrained time-varying phenomena, including the presence or absence of people in the building across the day. Our system is sufficiently robust to enable a variety of locationaware applications without requiring special-purpose hardware or complicated training and calibration procedures.
Hybrid simultaneous localization and map building: a natural integration of topological and metric
, 2003
"... In this paper the metric and topological paradigms are integrated in a hybrid system for both localization and map building. A global topological map connects local metric maps, allowing a compact environment model, which does not require global metric consistency and permits both precision and robu ..."
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Cited by 86 (5 self)
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In this paper the metric and topological paradigms are integrated in a hybrid system for both localization and map building. A global topological map connects local metric maps, allowing a compact environment model, which does not require global metric consistency and permits both precision and robustness. Furthermore, the approach handles loops in the environment during automatic mapping by means of the information of the multimodal topological localization. The system uses a 360◦ laser scanner to extract corners and openings for the topological approach and lines for the metric method. This hybrid approach has been tested in a 50 m × 25 m portion of the institute building with the fully autonomous robot Donald Duck. Experiments are of four types: maps created by a complete exploration of the environment are compared to estimate their quality; test missions are randomly generated in order to evaluate the efficiency of the approach for both the localization and relocation; the fourth type of experiments shows the practicability of the approach for closing the loop.
Towards a General Theory of Topological Maps
- Artificial Intelligence
, 2002
"... We present a general theory of topological maps whereby sensory input, topological and local metrical information are combined to define the topological maps explaining such information. Topological maps correspond to the minimal models of an axiomatic theory describing the relationships between ..."
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Cited by 84 (9 self)
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We present a general theory of topological maps whereby sensory input, topological and local metrical information are combined to define the topological maps explaining such information. Topological maps correspond to the minimal models of an axiomatic theory describing the relationships between the different sources of information explained by a map. We use a circumscriptive theory to specify the minimal models associated with this representation.
Map-based navigation in mobile robots. -- I. A review of localization strategies
, 2003
"... For a robot, an animal, and even for man, to be able to use an internal representation of the spatial layout of its environment to position itself is a very complex task, which raises numerous issues of perception, categorization and motor control that must all be solved in an integrated manner to p ..."
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Cited by 45 (12 self)
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For a robot, an animal, and even for man, to be able to use an internal representation of the spatial layout of its environment to position itself is a very complex task, which raises numerous issues of perception, categorization and motor control that must all be solved in an integrated manner to promote survival. This point is illustrated here, within the framework of a review of localization strategies in mobile robots. The allothetic and idiothetic sensors that may be used by these robots to build internal representations of their environment, and the maps in which these representations may be instantiated, are first described. Then map-based navigation systems are categorized according to a 3-level hierarchy of localization strategies, which respectively call upon direct position inference, single-hypothesis tracking, and multiple-hypothesis tracking. The advantages and drawbacks of these strategies, notably with respect to the limitations of the sensors on which they rely, are discussed throughout the text.
Map merging for distributed robot navigation
- In Intl. Conf. on Intelligent Robots and Systems
, 2003
"... A set of robots mapping an area can potentially combine their information to produce a distributed map more efficiently than a single robot alone. We describe a general framework for distributed map building in the presence of uncertain communication. Within this framework, we then present a technic ..."
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Cited by 39 (0 self)
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A set of robots mapping an area can potentially combine their information to produce a distributed map more efficiently than a single robot alone. We describe a general framework for distributed map building in the presence of uncertain communication. Within this framework, we then present a technical solution to the key decision problem of determining relative location within partial maps. 1
