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Topological Simultaneous Localization and Mapping (SLAM): Toward Exact Localization Without Explicit Localization
 IEEE Transactions on Robotics and Automation
, 2001
"... One of the critical components of mapping an unknown environment is the robot's ability to locate itself on a partially explored map. This becomes challenging when the robot experiences positioning error, does not have an external positioning device, nor the luxury of engineered landmarks place ..."
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Cited by 224 (10 self)
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One of the critical components of mapping an unknown environment is the robot's ability to locate itself on a partially explored map. This becomes challenging when the robot experiences positioning error, does not have an external positioning device, nor the luxury of engineered landmarks placed in its free space. This paper presents a new method for simultaneous localization and mapping that exploits the topology of the robot's free space to localize the robot on a partially constructed map. The topology of the environment is encoded in a topological map; the particular topological map used in this paper is the generalized Voronoi graph (GVG), which also encodes some metric information about the robot's environment, as well. In this paper, we present the lowlevel control laws that generate the GVG edges and nodes, thereby allowing for exploration of an unknown space. With these prescribed control laws, the GVG (or other topological map) can be viewed as an arbitrator for a hybrid control system that determines when to invoke a particular lowlevel controller from a set of controllers all working toward the highlevel capability of mobile robot exploration. The main contribution, however, is using the graph structure of the GVG, via a graph matching process, to localize the robot. Experimental results verify the described work. Index TermsExploration, localization, mapping, mobile robots, motion planning, tologoical maps, Voronoi diagrams. I.
Geometric Shortest Paths and Network Optimization
 Handbook of Computational Geometry
, 1998
"... Introduction A natural and wellstudied problem in algorithmic graph theory and network optimization is that of computing a "shortest path" between two nodes, s and t, in a graph whose edges have "weights" associated with them, and we consider the "length" of a path to ..."
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Cited by 187 (15 self)
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Introduction A natural and wellstudied problem in algorithmic graph theory and network optimization is that of computing a "shortest path" between two nodes, s and t, in a graph whose edges have "weights" associated with them, and we consider the "length" of a path to be the sum of the weights of the edges that comprise it. Efficient algorithms are well known for this problem, as briefly summarized below. The shortest path problem takes on a new dimension when considered in a geometric domain. In contrast to graphs, where the encoding of edges is explicit, a geometric instance of a shortest path problem is usually specified by giving geometric objects that implicitly encode the graph and its edge weights. Our goal in devising efficient geometric algorithms is generally to avoid explicit construction of the entire underlying graph, since the full induced graph may be very large (even exponential in the input size, or infinite). Computing an optimal
Sensor Based Motion Planning: The Hierarchical Generalized Voronoi Graph
, 1996
"... The hierarchical generalized Voronoi graph (HGVG) is a roadmap that can serve as a basis for sensor based robot motion planning. A key feature of the HGVG is its incremental construction procedure that uses only line of sight distance information. This work describes basic properties of the HGVG and ..."
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Cited by 94 (9 self)
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The hierarchical generalized Voronoi graph (HGVG) is a roadmap that can serve as a basis for sensor based robot motion planning. A key feature of the HGVG is its incremental construction procedure that uses only line of sight distance information. This work describes basic properties of the HGVG and the procedure for its incremental construction using local range sensors. Simulations and experiments verify this approach.
Adaptive evolutionary planner/navigator for mobile robots
 IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION
, 1997
"... Based on evolutionary computation (EC) concepts, we developed an adaptive Evolutionary Planner/Navigator �EP/N � as a novel approach to path planning and navigation. The EP/N is characterized by generality, flexibility � and adaptability. It unifies offline planning and on�line planning/navigation p ..."
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Cited by 83 (8 self)
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Based on evolutionary computation (EC) concepts, we developed an adaptive Evolutionary Planner/Navigator �EP/N � as a novel approach to path planning and navigation. The EP/N is characterized by generality, flexibility � and adaptability. It unifies offline planning and on�line planning/navigation processes in the same general and flexible evolutionary algorithm which (1) accommodates different optimization criteria and changes in these criteria, (2) incorporates various types of problem�specific domain knowledge, (3) enables good trade�offs among near�optimality of paths � high planning efficiency � and effective handling of unknown obstacles. More importantly � the EP/N can selftune its performance for different task environments and changes in such environments � mostly through adapting probabilities of its operators and adjusting paths constantly even during a robot�s motion towards the goal.
Sensor Based Planning, Part I: The Generalized Voronoi Graph
 IN PROC. IEEE INT. CONF. ON ROBOTICS AND AUTOMATION
, 1995
"... This paper introduces a 1dimensional network of curves termed the Generalized Voronoi Graph (GVG) and its extension, the Hierarchical Generalized Voronoi Graph (HGVG), which can be used as a basis for a roadmap or retractlike structure. The GVG and HGVG provide a basis for sensor based path plann ..."
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Cited by 60 (19 self)
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This paper introduces a 1dimensional network of curves termed the Generalized Voronoi Graph (GVG) and its extension, the Hierarchical Generalized Voronoi Graph (HGVG), which can be used as a basis for a roadmap or retractlike structure. The GVG and HGVG provide a basis for sensor based path planning in an unknown static environment. In this paper, the GVG and HGVG are defined and some of their properties are exploited to show their utility for motion planning. A companion paper describes how to use the GVG and HGVG for the purposes of sensor based planning.
SensorBased Exploration: The Hierarchical Generalized Voronoi Graph
, 2000
"... The hierarchical generalized Voronoi graph (HGVG) is a new roadmap developed for sensorbased exploration in unknown environments. This paper defines the HGVG structure: a robot can plan a path between two locations in its work space or configuration space by simply planning a path onto the HGVG, th ..."
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Cited by 60 (3 self)
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The hierarchical generalized Voronoi graph (HGVG) is a new roadmap developed for sensorbased exploration in unknown environments. This paper defines the HGVG structure: a robot can plan a path between two locations in its work space or configuration space by simply planning a path onto the HGVG, then along the HGVG, and finally from the HGVG to the goal. Since the bulk of the path planning occurs on the onedimensional HGVG, motion planning in arbitrary dimensioned spaces is virtually reduced to a onedimensional search problem. A bulk of this paper is dedicated to ensuring the HGVG is sufficient for motion planning by demonstrating the HGVG (with its links) is an arcwise connected structure. All of the proofs in this paper that lead toward the connectivity result focus on a large subset of spaces in R&sup3;, but wherever possible, results are derived in R^m. In fact, under a strict set of conditions, the HGVG (the GVG by itself) is indeed connected, and hence sufficient for motion planning. The chief advantage of the HGVG is that it possesses an incremental construction procedure, described in a companion paper, that constructs the HGVG using only lineofsight sensor data. Once the robot constructs the HGVG, it has effectively explored the environment, because it can then use the HGVG to plan a path between two arbitrary configurations.
Locomotion Versatility through Selfreconfiguration
 Robotics and Autonomous Systems
, 1998
"... We discuss a robotic module called a Molecule. Molecules can be the basis for building selfreconfiguring robots. They support multiple modalities of locomotion and manipulation. We describe the design, functionality, and control of the Molecule. We show how a set of Molecules can aggregate as activ ..."
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Cited by 56 (31 self)
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We discuss a robotic module called a Molecule. Molecules can be the basis for building selfreconfiguring robots. They support multiple modalities of locomotion and manipulation. We describe the design, functionality, and control of the Molecule. We show how a set of Molecules can aggregate as active threedimensional structures that can move and change shape. Finally, we discuss global motion algorithms for Molecular structures.
Walking an unknown street with bounded detour. Computational geometry: theory and applications
 in The 32nd Symposium on Foundations of Computer Science
, 1992
"... A polygon with two distinguished vertices, s and g, is called a street iff the two boundary chains from s to g are mutually weakly visible. For a mobile robot with onboard vision system we describe a strategy for finding a short path from s to g in a street not known in advance, and prove that the ..."
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Cited by 51 (7 self)
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A polygon with two distinguished vertices, s and g, is called a street iff the two boundary chains from s to g are mutually weakly visible. For a mobile robot with onboard vision system we describe a strategy for finding a short path from s to g in a street not known in advance, and prove that the length of the path created does not exceed 1 + 2. times the length of the shortest path from s to g. Experiments suggest that our strategy is much better than this, as no ratio bigger than 1.8 has yet been observed. This is complemented by a lower bound of 1.41 for the relative detour each strategy can be forced to generate. 1
Visibilitybased pursuitevasion in an unknown planar environment
 International Journal of Robotics Research
, 2004
"... We address an online version of the visibilitybased pursuitevasion problem. We take a minimalist approach in modeling the capabilities of a pursuer robot. A point pursuer moves in an unknown, simplyconnected, piecewisesmooth planar environment, and is given the task of locating any unpredictable ..."
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Cited by 49 (6 self)
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We address an online version of the visibilitybased pursuitevasion problem. We take a minimalist approach in modeling the capabilities of a pursuer robot. A point pursuer moves in an unknown, simplyconnected, piecewisesmooth planar environment, and is given the task of locating any unpredictable, moving evaders that have unbounded speed. The evaders are assumed to be points that move continuously. To solve the problem, the pursuer must for each target have an unobstructed view of it at some time during execution. The pursuer is equipped with a range sensor that measures the direction of depth discontinuities, but cannot provide precise depth measurements. All pursuer control is specified either in terms of this sensor or wallfollowing movements. The pursuer does not have localization capability or perfect control. We present a complete algorithm that enables the limited pursuer to clear the same environments that a pursuer with a complete map, perfect localization, and perfect control can clear (under certain general position assumptions). Theoretical guarantees that the evaders will be found are provided. The resulting algorithm to compute this strategy has been implemented in simulation. Results are shown for several examples. The approach is efficient and simple enough to be useful towards the development of real robot systems that perform visual searching. 1