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60
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.
Tracking Targets using Multiple Robots: The Effect of Environment Occlusion
- Autonomous Robots
, 2002
"... This paper addresses the problem of tracking multiple targets using a network of communicating robots and stationary sensors. We introduce a Region-based Approach which controls robot deployment at two levels. A coarse deployment controller distributes robots across regions using a topological map w ..."
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Cited by 72 (3 self)
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This paper addresses the problem of tracking multiple targets using a network of communicating robots and stationary sensors. We introduce a Region-based Approach which controls robot deployment at two levels. A coarse deployment controller distributes robots across regions using a topological map which maintains urgency estimates for each region, and a target-following controller attempts to maximize the number of tracked targets within a region. A behavior-based system is presented implementing the Region-Based Approach, which is fully distributed and scalable. We compared the Region-based Approach to a ‘naive ’ local-following strategy in three environments with varying degree of occlusion. The experimental results showed that the Region-based Approach performs better than the naive strategy when the environment has significant occlusion. Second, we performed experiments (the environment was held constant) in which two techniques for computing urgency estimates were compared. Last, different combinations of mobile sensors and stationary sensors were compared in a given environment. Keywords: Multi-target tracking, mobile robotics, embedded sensors
Visibility-based pursuit-evasion in an unknown planar environment
- International Journal of Robotics Research
, 2004
"... We address an on-line version of the visibility-based pursuit-evasion problem. We take a minimalist approach in modeling the capabilities of a pursuer robot. A point pursuer moves in an unknown, simplyconnected, piecewise-smooth 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 on-line version of the visibility-based pursuit-evasion problem. We take a minimalist approach in modeling the capabilities of a pursuer robot. A point pursuer moves in an unknown, simplyconnected, piecewise-smooth 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 wall-following 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
Distance-Optimal Navigation in an Unknown Environment without Sensing Distances
- IEEE TRANSACTIONS ON ROBOTICS
"... This paper considers what can be accomplished using a mobile robot that has limited sensing. For navigation and mapping, the robot has only one sensor, which tracks the directions of depth discontinuities. There are no coordinates, and the robot is given a motion primitive that allows it to move t ..."
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Cited by 43 (17 self)
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This paper considers what can be accomplished using a mobile robot that has limited sensing. For navigation and mapping, the robot has only one sensor, which tracks the directions of depth discontinuities. There are no coordinates, and the robot is given a motion primitive that allows it to move toward discontinuities. The robot is incapable of performing localization or measuring any distances or angles. Nevertheless, when dropped into an unknown planar environment, the robot builds a data structure, called the Gap Navigation Tree, which enables it to navigate optimally in terms of Euclidean distance traveled. In a sense, the robot is able to learn the critical information contained in the classical shortest-path roadmap, although surprisingly it is unable to extract metric information. We prove these results for the case of a point robot placed into a simply connected, piecewise-analytic planar environment. The case of multiply connected environments is also addressed, in which it is shown that further sensing assumptions are needed. Due to the limited sensor given to the robot, globally optimal navigation is impossible; however, our approach achieves locally optimal (within a homotopy class) navigation, which is the best that is theoretically possible under this robot model.
Interactive motion planning using hardware-accelerated computation of generalized Voronoi diagrams
- IN IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION
, 2000
"... We present techniques for fast motion planning by using discrete approximations of generalized Voronoi diagrams, computed with graphics hardware. Approaches based on this diagram computation are applicable to both static and dynamic environments of fairly high complexity. We compute a discrete Voron ..."
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Cited by 30 (1 self)
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We present techniques for fast motion planning by using discrete approximations of generalized Voronoi diagrams, computed with graphics hardware. Approaches based on this diagram computation are applicable to both static and dynamic environments of fairly high complexity. We compute a discrete Voronoi diagram by rendering a three-dimensional distance mesh for each Voronoi site. The sites can be points, line segments, polygons, polyhedra, curves and surfaces. The computation of the generalized Voronoi diagram provides fast proximity query toolkits for motion planning. The tools provide the distance to the nearest obstacle stored in the Z-bu er, as well as the Voronoi boundaries, Voronoi vertices and weighted Voronoi graphs extracted from the frame bu er using continuation methods. We have implemented these algorithms and demonstrated their performance for path planning in a complex dynamic environment composed ofmorethan 140,000 polygons.
Coordinated Multi-Robot Exploration using a Segmentation of the Environment
"... Abstract — This paper addresses the problem of exploring an unknown environment with a team of mobile robots. The key issue in coordinated multi-robot exploration is how to assign target locations to the individual robots such that the overall mission time is minimized. In this paper, we propose a n ..."
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Cited by 29 (2 self)
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Abstract — This paper addresses the problem of exploring an unknown environment with a team of mobile robots. The key issue in coordinated multi-robot exploration is how to assign target locations to the individual robots such that the overall mission time is minimized. In this paper, we propose a novel approach to distribute the robots over the environment that takes into account the structure of the environment. To achieve this, it partitions the space into segments, for example, corresponding to individual rooms. Instead of only considering frontiers between unknown and explored areas as target locations, we send the robots to the individual segments with the task to explore the corresponding area. Our approach has been implemented and tested in simulation as well as in real world experiments. The experiments demonstrate that the overall exploration time can be significantly reduced by considering our segmentation method. I.
A Region-based Approach for Cooperative Multi-Target Tracking in a Structured Environment
, 2002
"... This paper addresses the problem of tracking multiple anonymous targets using a network of communicating robots and stationary sensors. We introduce a regionbased approach which controls robot deployment at two levels. A coarse deployment controller distributes robots across regions using a topologi ..."
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Cited by 26 (3 self)
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This paper addresses the problem of tracking multiple anonymous targets using a network of communicating robots and stationary sensors. We introduce a regionbased approach which controls robot deployment at two levels. A coarse deployment controller distributes robots across regions using a topological map and density estimates, and a target-following controller attempts to maximize the number of tracked targets within a region. A behavior-based system is presented implementing the region-based approach. Intensive simulations were performed to investigate the correlation between our approach and the degree of occlusion in the environment. The region-based approach shows better performance than a `naive' local-following strategy when the environment has significant occlusion. We performed real-robot experiments to validate the system. These experiments open up a new line of research, which suggests that an optimal ratio of robots to stationary sensors may exist for a given environment with certain occlusion characteristics. 1
Sensor-Based Exploration: Incremental Construction of the Hierarchical Generalized Voronoi Graph
, 2000
"... This paper prescribes an incremental procedure to construct roadmaps of unknown environments. Recall that a roadmap is a geometric structure that a robot uses to plan a path between two points in an environment. If the robot knows the roadmap, then it knows the environment. Likewise, if the robot co ..."
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Cited by 21 (2 self)
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This paper prescribes an incremental procedure to construct roadmaps of unknown environments. Recall that a roadmap is a geometric structure that a robot uses to plan a path between two points in an environment. If the robot knows the roadmap, then it knows the environment. Likewise, if the robot constructs the roadmap, then it has effectively explored the environment. This paper focuses on the hierarchical generalized Voronoi graph (HGVG), detailed in the companion paper in this issue. The incremental construction procedure of the HGVG requires only local distance sensor measurements, and therefore the method can be used as a basis for sensor-based planning algorithms. Simulations and experiments using a mobile robot with ultrasonic sensors verify this approach. 1.
Extracting surveillance graphs from robot maps
- In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems
, 2008
"... Abstract — GRAPH-CLEAR is a recently introduced theo-retical framework to model surveillance tasks accomplished by multiple robots patrolling complex indoor environments. In this paper we provide a first step to close the loop between its graph-based theoretical formulation and practical scenarios. ..."
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Cited by 18 (7 self)
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Abstract — GRAPH-CLEAR is a recently introduced theo-retical framework to model surveillance tasks accomplished by multiple robots patrolling complex indoor environments. In this paper we provide a first step to close the loop between its graph-based theoretical formulation and practical scenarios. We show how it is possible to algorithmically extract suitable so-called surveillance graphs from occupancy grid maps. We also identify local graph modification operators, called contractions, that alter the graph being extracted so that the original surveillance problem can be solved using less robots. The algorithm we present is based on the Generalized Voronoi Diagram, a structure that can be simply computed using watershed like algorithms. Our algorithm is evaluated by processing maps produced by mobile robots exploring indoor environments. It turns out that the proposed algorithm is fast, robust to noise, and opportunistically modifies the graph so that less expensive strategies can be computed. I.
Sensor Based Planning: A Control Law for Generating the Generalized Voronoi Graph
- In Submitted to Proc. IEEE Int. Advanced Robotics
, 1996
"... Abstract We introduce a new control law for robots that explore unknown environments and con guration spaces. Unlike numerical continuation methods, which produce a jagged path because of the predictor-corrector approach, the control law, introduced inthispaper, performs sensor based planning by dir ..."
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Cited by 18 (4 self)
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Abstract We introduce a new control law for robots that explore unknown environments and con guration spaces. Unlike numerical continuation methods, which produce a jagged path because of the predictor-corrector approach, the control law, introduced inthispaper, performs sensor based planning by directing the head of a robot to follow continuously a roadmap. Recall that a roadmap is a one-dimensional representation of a robot's environment. Once therobot exhaustively traces out the roadmap using this control law, it has in essence explored an environment. Experiments on a mobile robot validate the control law. 1
