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Proceedings ArticleDOI

A two level fuzzy PRM for manipulation planning

01 Jan 2000-Vol. 3, pp 1716-1721
TL;DR: An algorithm which extends the probabilistic roadmap (PRM) framework to handle manipulation planning by using a two level approach, a PRM of PRMs, made possible by the introduction of a new kind of roadmap, called the fuzzy roadmap.
Abstract: This paper presents an algorithm which extends the probabilistic roadmap (PRM) framework to handle manipulation planning. This is done by using a two level approach, a PRM of PRMs. The first level builds a manipulation graph, whose nodes represent stable placements of the manipulated objects while the edges represent transfer and transit actions. The actual motion planning for the transfer and transit paths is done by PRM planners at the second level. The approach is made possible by the introduction of a new kind of roadmap, called the fuzzy roadmap. The fuzzy roadmap contains edges which are not verified by a local planner during construction. Instead, each edge is assigned a number which represents the probability that it is feasible. Later, if the edge is part of a solution path, the edge is checked for collisions. The overall effect is that our roadmaps evolve iteratively until they contain a solution. The use of fuzzy roadmaps in both levels of our manipulation planner offers many advantages. At the first level, a fuzzy roadmap represents the manipulation graph and addresses the problem of having probabilistically complete planners at the second level. At the second level, fuzzy roadmaps drastically reduce the number of collision checks. The paper contains experimental results demonstrating the feasibility and efficiency of our scheme.

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Citations
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Proceedings ArticleDOI
24 Apr 2000
TL;DR: The overall theme of the algorithm, called Lazy PRM, is to minimize the number of collision checks performed during planning and hence minimize the running time of the planner.
Abstract: Describes an approach to probabilistic roadmap planners (PRMs). The overall theme of the algorithm, called Lazy PRM, is to minimize the number of collision checks performed during planning and hence minimize the running time of the planner. Our algorithm builds a roadmap in the configuration space, whose nodes are the user-defined initial and goal configurations and a number of randomly generated nodes. Neighboring nodes are connected by edges representing paths between the nodes. In contrast with PRMs, our planner initially assumes that all nodes and edges in the roadmap are collision-free, and searches the roadmap at hand for a shortest path between the initial and the goal node. The nodes and edges along the path are then checked for collision. If a collision with the obstacles occurs, the corresponding nodes and edges are removed from the roadmap. Our planner either finds a new shortest path, or first updates the roadmap with new nodes and edges, and then searches for a shortest path. The above process is repeated until a collision-free path is returned. Lazy PRM is tailored to efficiently answer single planning queries, but can also be used for multiple queries. Experimental results presented in the paper show that our lazy method is very efficient in practice.

874 citations


Additional excerpts

  • ...Similar ideas about lazy evaluation have been developed concurrently but independently in [ 25 ] in a planner called fizzy PRM....

    [...]

Journal ArticleDOI
TL;DR: The state of the art in motion planning is surveyed and selected planners that tackle current issues in robotics are addressed, for instance, real-life kinodynamic planning, optimal planning, replanning in dynamic environments, and planning under uncertainty are discussed.
Abstract: Motion planning is a fundamental research area in robotics. Sampling-based methods offer an efficient solution for what is otherwise a rather challenging dilemma of path planning. Consequently, these methods have been extended further away from basic robot planning into further difficult scenarios and diverse applications. A comprehensive survey of the growing body of work in sampling-based planning is given here. Simulations are executed to evaluate some of the proposed planners and highlight some of the implementation details that are often left unspecified. An emphasis is placed on contemporary research directions in this field. We address planners that tackle current issues in robotics. For instance, real-life kinodynamic planning, optimal planning, replanning in dynamic environments, and planning under uncertainty are discussed. The aim of this paper is to survey the state of the art in motion planning and to assess selected planners, examine implementation details and above all shed a light on the current challenges in motion planning and the promising approaches that will potentially overcome those problems.

602 citations


Cites background from "A two level fuzzy PRM for manipulat..."

  • ...Lazy planning algorithms have been proposed to delay collision checking until it’s needed [129]–[131]....

    [...]

Book ChapterDOI
01 Jan 2003
TL;DR: Experimental results show that this combination of techniques drastically reduces planning times, making it possible to handle difficult problems, including multi-robot problems in geometrically complex environments.
Abstract: This paper describes a new probabilistic roadmap (PRM) path planner that is: (1) single-query — instead of pre-computing a roadmap covering the entire free space, it uses the two input query configurations as seeds to explore as little space as possible; (2) bidirectional — it explores the robot’s free space by concurrently building a roadmap made of two trees rooted at the query configurations; (3) adaptive — it makes longer steps in opened areas of the free space and shorter steps in cluttered areas; and (4) lazy in checking collision — it delays collision tests along the edges of the roadmap until they are absolutely needed. Experimental results show that this combination of techniques drastically reduces planning times, making it possible to handle difficult problems, including multi-robot problems in geometrically complex environments.

332 citations


Cites methods from "A two level fuzzy PRM for manipulat..."

  • ...TEST-PATH( ) maintains a priority queue U of these segments sorted in decreasing order of 2 ˝( ui) (u i) (i = 1t o p ). A similar technique has been previously used in ( Nielsen, Kavraki, 2000 )....

    [...]

Journal ArticleDOI
TL;DR: A general manipulation planning approach capable of addressing continuous sets for modeling both the possible grasps and the stable placements of the movable object, rather than discrete sets generally assumed by the previous approaches.
Abstract: This paper deals with motion planning for robots manipulating movable objects among obstacles. We propose a general manipulation planning approach capable of addressing continuous sets for modeling both the possible grasps and the stable placements of the movable object, rather than discrete sets generally assumed by the previous approaches. The proposed algorithm relies on a topological property that characterizes the existence of solutions in the subspace of configurations where the robot grasps the object placed at a stable position. It allows us to devise a manipulation planner that captures in a probabilistic roadmap the connectivity of sub-dimensional manifolds of the composite configuration space. Experiments conducted with the planner in simulated environments demonstrate its efficacy to solve complex manipulation problems.

309 citations

Journal ArticleDOI
TL;DR: This work proposes a representation and a planning algorithm able to deal with problems integrating task planning as well as motion and manipulation planning knowledge involving several robots and objects and describes the main features of an implemented planner.
Abstract: We propose a representation and a planning algorithm able to deal with problems integrating task planning as well as motion and manipulation planning knowledge involving several robots and objects. Robot plans often include actions where the robot has to place itself in some position in order to perform some other action or to "modify" the configuration of its environment by displacing objects. Our approach aims at establishing a bridge between task planning and manipulation planning that allows a rigorous treatment of geometric preconditions and effects of robot actions in realistic environments. We show how links can be established between a symbolic description and its geometric counterpart and how they can be used in an integrated planning process that is able to deal with intricate symbolic and geometric constraints. Finally, we describe the main features of an implemented planner and discuss several examples of its use.

276 citations


Cites background from "A two level fuzzy PRM for manipulat..."

  • ...…been proposed to address problems that involve discrete (qualitative) changes and continuous motion primitives (Wilfong 1988 Alami et al. 1990 Chen and Hwang 1991 Koga and Latombe 1994 Ahuactzin et al. 1998 Nielsen and Kavraki 2000 Lingelbach 2004 Bretl 2006 Plaku et al. 2007 Saut et al. 2007)....

    [...]

References
More filters
Proceedings Article
12 May 1995
TL;DR: The authors propose a method, called Ariadne's clew algorithm, to build a global path planner based on the combination of two local planning algorithms: an explore algorithm and a search algorithm.
Abstract: The goal of the work described is to build a path planner able to drive a robot in a dynamic environment where the obstacles are moving. In order to do so, the authors propose a method, called Ariadne's clew algorithm, to build a global path planner based on the combination of two local planning algorithms: an explore algorithm and a search algorithm. The purpose of the explore algorithm is to collect information about the environment with an increasingly fine resolution by placing landmarks in the searched space. The goal of the search algorithm is to opportunistically check if the target can be easily reached from any given placed landmark. The Ariadne's clew algorithm is shown to be very fast is most cases, allowing planning in dynamic environment. It is shown to be complete, which means that it is sure to find a path when one exists. A massively parallel implementation of this algorithm is described.

145 citations

Journal ArticleDOI
01 Aug 1999
TL;DR: This paper proposes a novel and global approach to solving the point-to-point inverse kinematics problem for highly redundant manipulators using the novel notion of kinematic roadmap for a manipulator that captures the connectivity of the connected component of the free configuration space of the manipulator in a finite graph like structure.
Abstract: This paper proposes a novel and global approach to solving the point-to-point inverse kinematics problem for highly redundant manipulators. Given an initial configuration of the robot, the problem is to find a reachable configuration that corresponds to a desired position and orientation of the end-effector. Central to our approach is the novel notion of kinematic roadmap for a manipulator. The kinematic roadmap captures the connectivity of the connected component of the free configuration space of the manipulator in a finite graph like structure. The point-to-point inverse kinematics problem is then solved using this roadmap. We provide completeness results for our algorithm. Our implementation of SEARCH is an efficient closed form solution, albeit local, to inverse kinematics that exploits the serial kinematic structure of serial manipulator arms. Initial experiments with a 7-DOF manipulator have been extremely successful.

98 citations

Proceedings ArticleDOI
12 May 1992
TL;DR: The authors survey previous work in manipulation planning and relate it to this analysis, and a formal configuration space presentation of the dual-arm manipulation problem is given.
Abstract: The problem of dual-arm manipulation planning is to plan the path of two cooperating robot arms to carry a moveable object from a given initial configuration to a given goal configuration amidst obstacles. The authors survey previous work in manipulation planning and relate it to this analysis. A formal configuration space presentation of the problem is given. Three implemented planners are described. These three planners operated in a two-dimensional workspace and addressed increasingly difficult versions of the dual-arm manipulation problem. They were implemented in the C language. Execution times given were obtained by running them on a DEC 5000 workstation. >

66 citations

Journal ArticleDOI
TL;DR: This paper extends the paradigm to manipulation-planning problem, where the goal is to plan the motion of a robot so that it can move a given object from an initial configuration to a final configuration while avoiding collisions with the static obstacles and other movable objects in the environment.
Abstract: An emerging paradigm in solving the classical motion- planning problem (among static obstacles) is to capture the connectivity of the configuration space using a finite (but pos sibly large) set of...

52 citations


"A two level fuzzy PRM for manipulat..." refers background in this paper

  • ...const,ra,int,s. Ahiia.ctzin, Gupta and Mazer [ 2 ] have proposed a met(hod for nianipulation planning which is an ext,cnsion of the Adriadne’s Clew Algorithm [5] based on genetic algorithms....

    [...]

Proceedings ArticleDOI
08 May 1994
TL;DR: The authors present a systematic approach to motion planning in the presence of manipulation constraints deriving from this theory to replace a constrained problem by a convergent series of less constrained subproblems increasingly penalizing motions that do not satisfy the constraints.
Abstract: Establishes necessary and sufficient conditions under which manipulation constraints are holonomic. Then the authors present a systematic approach to motion planning in the presence of manipulation constraints deriving from this theory. Its principle is to replace a constrained problem by a convergent series of less constrained subproblems increasingly penalizing motions that do not satisfy the constraints. Each subproblem is solved using a standard path planner. The authors use the method of variational dynamic programming for solving the subproblems. The implemented planner has solved manipulation planning problems of unprecedented complexity. >

51 citations