Potential-based modeling of three-dimensional workspace for obstacle avoidance

Chuang, J.-H.

doi:10.1109/robot.1993.291927

Cited by 20 publications

(30 citation statements)

References 8 publications

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“…The reader is referred to [3,4] for more about potential fields as well as some of the detailed derivations of formulas involved in our subsequent discussion.…”

Section: Force-directed Methods Using Potential Fieldsmentioning

confidence: 99%

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Drawing Graphs with Nonuniform Nodes Using Potential Fields

2004

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Abstract.A potential field approach, coupled with force-directed methods, is proposed in this paper for drawing graphs with nonuniform nodes in 2-D and 3-D. In our framework, nonuniform nodes are uniformly or nonuniformly charged, while edges are modelled by springs. Using certain techniques developed in the field of potential-based path planning, we are able to find analytically tractable procedures for computing the repulsive force and torque of a node in the potential field induced by the remaining nodes. Our experimental results suggest this new approach to be promising, as drawings of good quality for a variety of graphs in 2-D and 3-D can be produced efficiently.

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“…The reader is referred to [3,4] for more about potential fields as well as some of the detailed derivations of formulas involved in our subsequent discussion.…”

Section: Force-directed Methods Using Potential Fieldsmentioning

confidence: 99%

“…which can be evaluated analytically (4). Note that by letting α = 0 (resp., α = β = 0 and γ = 1), the above equation characterizes the linear (resp., Newtonian) potential field.…”

Section: Force-directed Methods Using Potential Fieldsmentioning

confidence: 99%

Drawing Graphs with Nonuniform Nodes Using Potential Fields

2004

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“…Robot Path Planning Related to the vertex path problem is the robotic path planning problem of computing paths for robot seeds to navigate through an environment filled with obstacles represented by polygonal shapes. Chuang [4] assigns each obstacle a potential function by defining a scalar value that drops exponentially as the distance to the obstacle grows. The summation of these functions over all obstacles in the environment defines a potential field.…”

Section: Related Workmentioning

confidence: 99%

Surface Creation and Curve Deformations Between Two Complex Closed Spatial Spline Curves

Daniels

Cohen

2006

Geometric Modeling and Processing - GMP 2006

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Abstract. This paper presents an algorithm to generate a smooth surface between two closed spatial spline curves. With the assumption that the two input curves can be projected to a single plane so that the projections do not have any mutual or self intersections, and so that one projection completely encloses the other. We describe an algorithm that generates a temporal deformation between the input curves, one which can be thought of as sweeping a surface. Instead of addressing feature matching, as many planar curve deformation algorithms do, the deformation method described generates intermediate curves that behave like wavefronts as they evolve from the shape of one boundary curve to a medial type curve, and then gradually take on the characteristics of the second boundary curve. This is achieved in a manner that assures there will be neither singularities in the parameterization nor self-intersections in the projected surface.

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“…These approaches have been widely applied to path planning of a mobile robot and a manipulator (Borenstein and Koren, 1989;Chuang, 1998;Chuang and Ahuja, 1998;Chuang et al, 2000;Guldner and Utkin, 1995;Haddad et al, 1998;Hwang and Ahuja, 1992;Tsai et al, 2001;Vadakkepat, 2001;Veelaert and Bogaerts, 1999). The applications of artificial potential field for obstacle avoidance was first developed by Khatib (Khatib, 1985;Khatib, 1986).…”

Section: Itroductionmentioning

confidence: 99%

Real-Time Path Planning in Unknown Environments Using a Virtual Hill

Park

Lee

2005

IFAC Proceedings Volumes

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The artificial potential field based path planning has been most wisely used for local path planning because it provides simple and efficient motion planners for practical purposes. However, this approach has a local minimum problem which can trap a robot before reaching its goal. The local minimum problem is sometimes inevitable when a mobile robot moves in unknown environments, because the robot cannot predict local minima before it detects obstacles forming the local minima. The avoidance of local minima has been an active research topic in the potential field based path planning. In this study, we propose a new concept using a virtual hill to escape local minima that occur in local path planning for a mobile robot. A virtual hill is located around local minimum to repel a robot from local minimum. Copyright © 2005 IFAC Keywords: mobile robot, path planning, artificial potential field, virtual hill, extra potential, navigation. ITRODUCTIONArtificial potential field methods provide simple and effective motion planners for practical purposes (Lee and Park, 1991). These approaches have been widely applied to path planning of a mobile robot and a manipulator (Borenstein and Koren, 1989;Chuang, 1998;Chuang and Ahuja, 1998;Chuang et al., 2000;Guldner and Utkin, 1995;Haddad et al., 1998;Hwang and Ahuja, 1992;Tsai et al, 2001;Vadakkepat, 2001;Veelaert and Bogaerts, 1999). The applications of artificial potential field for obstacle avoidance was first developed by Khatib (Khatib, 1985;Khatib, 1986). This approach uses two types of potential, which are a repulsive potential field to force a robot away from obstacles or forbidden regions and an attractive potential field to drive the robot to its goal. The robot moves under the action of the artificial force which is proportional to the negative gradient of artificial potential. The robot is driven from the positions with the higher potential to that with the lower potential.However, the path planning by the artificial potential field approach has a major problem, a local minimum problem, which can trap a robot before reaching its goal. The local minimum problem is sometimes unavoidable in local path planning, because the robot can detect only local information on obstacles. In other words, the robot cannot predict local minima before experiencing the environment. An avoidance of a local minimum has been an active research topic in potential field based path planning (Chang, 1996;Cho and Kwon, 1996;Connolly et al., 1990; Connolly, 1992;Janabi-Sharifi and Vinke, 1993;Kim and Khosla, 1992; Lee and Park, 1991;McFetridge and Yousef-Ibrahim, 1998;Park and Lee, 2003; Rimom and Koditschek, 1992;Volpe and Khosla, 1990). However, the previous solutions were limited to simple formations of obstacles or available for path planning in known environments.

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Potential-based modeling of three-dimensional workspace for obstacle avoidance

Cited by 20 publications

References 8 publications

Drawing Graphs with Nonuniform Nodes Using Potential Fields

Drawing Graphs with Nonuniform Nodes Using Potential Fields

Surface Creation and Curve Deformations Between Two Complex Closed Spatial Spline Curves

Real-Time Path Planning in Unknown Environments Using a Virtual Hill

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