Localizing a Robot with Minimum Travel

Dudek, Gregory; Romanik, Kathleen; Whitesides, Sue

doi:10.1137/s0097539794279201

Cited by 59 publications

(75 citation statements)

References 11 publications

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“…If there is more than one position hypotheses, the robot should move around to determine its position with certainty. In [7], a strategy that computes an overlay arrangement of the visibility cells is used to determine the optimal movement strategy to reduce the set of position hypotheses. In that approach, a decision tree is simulated, in which each decision node is a visibility skeleton comparison that discards some position hypotheses.…”

Section: Visibility-based Tasksmentioning

confidence: 99%

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Gap Navigation Trees: Minimal Representation for Visibility-based Tasks

Tovar

Guilamo

LaValle³

2005

Springer Tracts in Advanced Robotics

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Abstract. In this paper we present our advances in a data structure, the Gap Navigation Tree (GNT), useful for solving different visibility-based robotic tasks in unknown planar environments. We present its use for optimal robot navigation in simply-connected environments, locally optimal navigation in multiply-connected environments, pursuit-evasion, and robot localization. The guiding philosophy of this work is to avoid traditional problems such as complete map building and exact localization by constructing a minimal representation based entirely on critical events in online sensor measurements made by the robot. The data structure is introduced from an information space perspective, in which the information used among the different visibility-based tasks is essentially the same, and it is up to the robot strategy to use it accordingly for the completion of the particular task. This is done through a simple sensor abstraction that reports the discontinuities in depth information of the environment from the robot's perspective (gaps), and without any kind of geometric measurements. The GNT framework was successfully implemented on a real robot platform.

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Section: Visibility-based Tasksmentioning

confidence: 99%

“…al. [7] is used. Instead of using the arrangement of visibility cells, the shortest-path trees are used for the comparisons in the movement decisions.…”

Section: Robot Localizationmentioning

confidence: 99%

Gap Navigation Trees: Minimal Representation for Visibility-based Tasks

Tovar

Guilamo

LaValle³

2005

Springer Tracts in Advanced Robotics

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“…The number of initial hypothetical locations is bounded above by the number of reflex vertices in the polygonal environment 3 . Let be the number of active hypotheses remaining ( ).…”

Section: Complexity Analysismentioning

confidence: 99%

Randomized Algorithms for Minimum Distance Localization

Rao

Dudek

Whitesides

2005

Springer Tracts in Advanced Robotics

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“…Much of the early work in this direction was in the context of object manipulation [9,20]. Other work includes information invariants [5], sensor design [8], bug algorithms for navigation [19,13], robot localization [6], POMDPs [16], and error detection and recovery [4].…”

Section: Introductionmentioning

confidence: 99%

Information spaces for mobile robots

Tovar

Yershova

O’Kane

et al. 2005

Proceedings of the Fifth International Workshop on Robot Motion and Control, 2005. RoMoCo '05.

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Planning with sensing uncertainty is central to robotics. Sensor limitations often prevent accurate state estimation of the robot. Two general approaches can be taken for solving robotics tasks given sensing uncertainty. The first approach is to estimate the state and to solve the given task using the estimate as the real state. However, estimation of the state may sometimes be harder than solving the original task. The other approach is to avoid estimation of the state, which can be achieved by defining the information space, the space of all histories of actions and sensing observations of a robot system. Considering information spaces brings better understanding of problems involving uncertainty, and also allows finding better solutions to such problems. In this paper we give a brief description of the information space framework, followed by its use in some robotic tasks.

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Localizing a Robot with Minimum Travel

Cited by 59 publications

References 11 publications

Gap Navigation Trees: Minimal Representation for Visibility-based Tasks

Gap Navigation Trees: Minimal Representation for Visibility-based Tasks

Randomized Algorithms for Minimum Distance Localization

Information spaces for mobile robots

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