The visit problem: visibility graph-based solution

Rao, Nageswara S. V.; Iyengar, S. S.; deSaussure, G.

doi:10.1109/robot.1988.12303

Cited by 30 publications

(15 citation statements)

References 8 publications

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“…The navigation algorithm is described as follows: Note that it is important to remove visited vertices from the list (L) before selecting the next subgoal. The above technique has been applied previously [15][16][17][18], dropping visited vertices, for collision-free paths, which can prevent the navigation algorithm from falling into local infinite iteration during. For example, the local infinite iteration is illustrated in Figure 6 where R is located at p 1 (or p 2 ), and ∠1 > ∠2, ∠4 > ∠3.…”

Section: Navigation Algorithmmentioning

confidence: 99%

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On‐line algorithm for optimal 3D path planning

Hun

Chen

Hwang

2012

Comp Applic In Engineering

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ABSTRACT:The issues of automatic car operation aiming at in an unknown complex terrain are the most effective path planning and the obstacles avoiding in this complex terrain. For that, an on-line algorithm for guiding a mobile object in an unexplored terrain filled with convex polygonal obstacles is presented. The mobile object was taken as a point-size auto equipped with a sensor system, which is used to detect previously all visible parts of the obstacles surrounding it. Both the visibility and the tangent graph were modified and used in this algorithm to construct the basic concept. At each stage, the next subgoal was selected from local information provided by the sensor. Furthermore, in order to expand the algorithm to handle nonconvex polygonal obstacles and mazes, it was modified by adding backtracking and by removing visited vertices. The algorithm was implemented in MATLAB language, and several numerical examples are shown to evaluate its feasibility. Moreover, the convergence of the algorithm was examined using the visibility graph, and the performance of the algorithm was evaluated by simply comparing with other algorithms for both the length of the path and the traveling time from the initial point to the target point.

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Section: Navigation Algorithmmentioning

confidence: 99%

“…However, in actuality there are a great number of obstacles whose shapes are nonconvex. In this section, the navigation algorithm is modified by adding a backtracking technique [14][15][16] for dealing with nonconvex polygonal obstacles and mazes.…”

Section: Modified Navigation Algorithmmentioning

confidence: 99%

On‐line algorithm for optimal 3D path planning

Hun

Chen

Hwang

2012

Comp Applic In Engineering

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“…An application-specific integrated circuit (ASIC) was designed and implemented for the proposed algorithm and, thus, execution speed for the construction of the Voronoi diagram is very high. This is considered to be a significant advantage, since an efficient and fast static motion planner is a vital ingredient of a dynamic motion planner in partially known environments [4], in path planning of multiple robots with conflicting/common objectives, where robots of higher precedence are regarded as moving obstacles for robots of lower precedence [5], [6], and in time-varying environments, where robot motions have to be planned from the predicted motions of obstacles and replanning is needed if obstacle motion deviates from prediction [7], [8]. A Voronoi planner of the type proposed in this paper is particularly required in the case where many motion planning problems, with different start and goal configurations within the same environment, are to be solved.…”

Section: Previous Workmentioning

confidence: 99%

“…The Von-Neumann neighborhood of a cell is defined as the set that contains the cell itself and all neighbors of that cell that lie a unit distance away from it on the 2-D grid. The rule of CA operation over the local neighborhood is given as follows: (4) where indexes define the coordinates of a cell on the Cartesian grid, is the output of a cell on time step and operation is the logical OR operation. The main difference of the CA architecture proposed in this paper, relative to the binary CA proposed in [21] and [23], is that the cells can assume a finite range of values that are not constrained to the binary set.…”

Section: A Definition Of Cellular Automatamentioning

confidence: 99%

Collision-free path planning for a diamond-shaped robot using two-dimensional cellular automata

Tzionas

Thanailakis

Tsalides

1997

IEEE Trans. Robot. Automat.

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This paper presents a new parallel algorithm for collision-free path planning of a diamond-shaped robot among arbitrarily shaped obstacles, which are represented as a discrete image, and its implementation in VLSI. The proposed algorithm is based on a retraction of free space onto the Voronoi diagram, which is constructed through the time evolution of cellular automata, after an initial phase during which the boundaries of obstacles are identified and coded with respect to their orientation. The proposed algorithm is both space and time efficient, since it does not require the modeling of objects or distance and intersection calculations. Additionally, the proposed twodimensional multistate cellular automaton architecture achieves high frequency of operation and it is particularly suited for VLSI implementation due to its inherent parallelism, structural locality, regularity, and modularity.

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“…Several approaches have been used to plan paths for mobile robots. The visibility graph is used when the shortest path is desired [LoWe79,RaIS88,FuSa90]. The paths in the visibility graph touch the corners of obstacles to minimize the path lengths.…”

Section: Introductionmentioning

confidence: 99%

Practical path planning among movable obstacles

Chen

Hwang

Proceedings. 1991 IEEE International Conference on Robotics and Automation

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Path planning among movable obstacles is a practical problem that is in need of a solution. In this paper, we present an efficient heuristic algorithm that uses a generate-and-test paradigm: a "good" candidate path is hypothesized by a global planner and subsequently verified by a local planner. In the process of formalizing the problem, we also present a technique for modeling object interactions through contact. Our algorithm has been tested on a variety of examples, and was able to generate solutions within 10 seconds.

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The visit problem: visibility graph-based solution

Cited by 30 publications

References 8 publications

On‐line algorithm for optimal 3D path planning

On‐line algorithm for optimal 3D path planning

Collision-free path planning for a diamond-shaped robot using two-dimensional cellular automata

Practical path planning among movable obstacles

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