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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
21 May 2001
TL;DR: An approach for building and querying probabilistic roadmaps, which postpones some of the validation checks to the query phase, yields more efficient solutions to many problems, and shows remarkable flexibility when adapting to different query requirements.
Abstract: We propose an approach for building and querying probabilistic roadmaps. In the roadmap construction stage, we build coarse roadmaps by performing only an approximate validation of the roadmap nodes and/or edges. In the query stage, the roadmap is validated and refined only in the area of interest for the query, and moreover is customized in accordance with any specified query preferences. This approach, which postpones some of the validation checks (e.g., collision checks) to the query phase, yields more efficient solutions to many problems. An important benefit of our approach is that it gives one the ability to customize the same roadmap in accordance with multiple, variable, query preferences. For example our approach enables one to find a path which maintains a particular clearance, or makes at most some specified number of sharp turns. Our preliminary results on problems drawn from diverse application domains show that this new approach dramatically improves performance, and shows remarkable flexibility when adapting to different query requirements.

72 citations


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

  • ...Unfortunately, however, as previously noted, complete, exact evaluation of configurations in the roadmap construction phase leads to infeasible construction times for many important applications....

    [...]

  • ...The resolution at which to terminate the process during roadmap construction can be some computed value related to the environment characteristics, or can be set by the user....

    [...]

  • ...Also, some novel approaches for improving PRM efficiency have shown promising results [6, 17] (these methods do not address the narrow passage problem)....

    [...]

  • ...In addition to yielding big performance gains, this strategy enables us to support additional, and variable, requirements or preferences on the properties of the solution path obtained....

    [...]

Book ChapterDOI
20 Oct 2008
TL;DR: A planner to compute motions of a large and highly mobile six-legged lunar vehicle called athlete is presented that combines graph searching techniques to generate a sequence of candidate footfalls with probabilistic sample-based planning to generate continuous motions to reach them.
Abstract: This paper studies the motion of a large and highly mobile six-legged lunar vehicle called athlete, developed by the Jet Propulsion Laboratory. This vehicle rolls on wheels when possible, but can use the wheels as feet to walk when necessary. While gaited walking may suffice for most situations, rough and steep terrain requires novel sequences of footsteps and postural adjustments that are specifically adapted to local geometric and physical properties. This paper presents a planner to compute these motions that combines graph searching techniques to generate a sequence of candidate footfalls with probabilistic sample-based planning to generate continuous motions to reach them. The viability of this approach is demonstrated in simulation on several example terrains, even one that requires rappelling.

72 citations


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

  • ...But when motion is distinctly non-gaited (as in manipulation planning [33,37], freeclimbing [6], or for athlete), each step requires the exploration of configuration space....

    [...]

  • ...We increase the cost of σ proportional to the amount of time spent trying to sample a transition q ∈ Fσ′ ∩ Fσ to reach it [33]....

    [...]

Journal ArticleDOI
TL;DR: This paper proposes a new concept in which a digital twin derived from a digital product description will automatically perform assembly planning and orchestrate the production resources in a manuf ...

71 citations


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

  • ...Automatic methods for ASP have been studied since 1980’s [56, 57, 58] and the study of robotic manipulation planning continues actively in the framework of integrated task and motion planning as the manipulation planning problem contains both discrete (which part next) and continuous (which continuous trajectory) components [59,60]....

    [...]

Proceedings ArticleDOI
29 Sep 2014
TL;DR: This work presents a new approach to integrated task and motion planning (ITMP) for robots performing mobile manipulation that captures partial knowledge about a mobile manipulation setting and is capable of generating integrated plans for a number of interesting variations on the problem.
Abstract: We present a new approach to integrated task and motion planning (ITMP) for robots performing mobile manipulation. In our approach, the user writes a high-level specification that captures partial knowledge about a mobile manipulation setting. In particular, this specification includes a plan outline that syntactically defines a space of plausible integrated plans, a set of logical requirements that the generated plan must satisfy, and a description of the physical space that the robot manipulates. A synthesis algorithm is now used to search for an integrated plan that falls within the space defined by the plan outline, and also satisfies all requirements. Our synthesis algorithm complements continuous motion planning algorithms with calls to a Satisfiability Modulo Theories (SMT) solver. From the scene description, a motion planning algorithm is used to construct a placement graph, an abstraction of a manipulation graph whose paths represent feasible, low-level motion plans. An SMT-solver is now used to symbolically explore the space of all integrated plans that correspond to paths in the placement graph, and also satisfy the constraints demanded by the plan outline and the requirements. Our approach is implemented in a system called ROBOSYNTH. We have evaluated ROBOSYNTH on a generalization of an ITMP problem investigated in prior work. The experiments demonstrate that our method is capable of generating integrated plans for a number of interesting variations on the problem.

71 citations


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

  • ...this information will be computed automatically and possibly adaptively while the graph will be computed lazily [26], [27]....

    [...]

Proceedings ArticleDOI
11 Mar 2001
TL;DR: A new approach for motion planning for nonholonomic car-like robots which is based on a customizable probabilistic roadmap (C-PRM) that enables the same roadmap to be efficiently utilized for car- like robots with different turning radii, which need not be known before the query time.
Abstract: We propose a new approach for motion planning for nonholonomic car-like robots which is based on a customizable probabilistic roadmap (C-PRM). A major advantage of our approach is that it enables the same roadmap to be efficiently utilized for car-like robots with different turning radii, which need not be known before the query time. Our C-PRM-based approach first builds a so-called control roadmap which does not incorporate any nonholonomic constraints. The control roadmap is used to efficiently generate 'good' configurations of the car, e.g., aligned with the roadway. The control roadmap is also used to guide the roadmap connection. The paths encoded in the roadmap consist of straight-line segments and arcs, where transitions between the two require full stopping of the car. The control roadmap assists in the optimization and smoothing of these paths using cubic B-splines. Results with a simple car-like robot are very promising.

65 citations


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

  • ...A similar philosophy is proposed in the Lazy PRM [7] and Fuzzy PRM [17] methods, which advocate an even coarser validation thanC-PRM – either no validation at all [7] (i.e., accepting all roadmap nodes and edges in the construction phase) or validating nodes but not edges [17]....

    [...]

  • ...A similar philosophy is proposed in the Lazy PRM [7] and Fuzzy PRM [17] methods, which advocate an even coarser validation than C-PRM – either no validation at all [7] (i....

    [...]

  • ..., accepting all roadmap nodes and edges in the construction phase) or validating nodes but not edges [17]....

    [...]

References
More filters
Journal ArticleDOI
01 Aug 1996
TL;DR: Experimental results show that path planning can be done in a fraction of a second on a contemporary workstation (/spl ap/150 MIPS), after learning for relatively short periods of time (a few dozen seconds).
Abstract: A new motion planning method for robots in static workspaces is presented. This method proceeds in two phases: a learning phase and a query phase. In the learning phase, a probabilistic roadmap is constructed and stored as a graph whose nodes correspond to collision-free configurations and whose edges correspond to feasible paths between these configurations. These paths are computed using a simple and fast local planner. In the query phase, any given start and goal configurations of the robot are connected to two nodes of the roadmap; the roadmap is then searched for a path joining these two nodes. The method is general and easy to implement. It can be applied to virtually any type of holonomic robot. It requires selecting certain parameters (e.g., the duration of the learning phase) whose values depend on the scene, that is the robot and its workspace. But these values turn out to be relatively easy to choose, Increased efficiency can also be achieved by tailoring some components of the method (e.g., the local planner) to the considered robots. In this paper the method is applied to planar articulated robots with many degrees of freedom. Experimental results show that path planning can be done in a fraction of a second on a contemporary workstation (/spl ap/150 MIPS), after learning for relatively short periods of time (a few dozen seconds).

4,977 citations

Proceedings Article
01 Aug 1998
TL;DR: This paper presents a new class of randomized path planning methods, known as Probabilistic Roadmap Methods (prms), which use randomization to construct a graph of representative paths in C-space whose vertices correspond to collision-free con gurations of the robot.
Abstract: Recently, a new class of randomized path planning methods, known as Probabilistic Roadmap Methods (prms) have shown great potential for solving complicated high-dimensional problems. prms use randomization (usually during preprocessing) to construct a graph of representative paths in C-space (a roadmap) whose vertices correspond to collision-free con gurations of the robot and in which two vertices are connected by an edge if a path between the two corresponding con gurations can be found by a local planning method.

533 citations

Proceedings Article
01 Aug 1998
TL;DR: Y@lBEDGF HEIKJ L„DzMPORQSIUT MV@CW2X >A@CBEDGF HeIKJRX\[^]\X,L>z]  ~Uw ’Nw2x  “eUfa3Vx=
Abstract: .0/2143658709;:=A@CBEDGF HEIKJ L DNMPORQSIUT MV@CW2X >Y@CBEDZF HEIUJRX\[^]\X,L=>N] _?`N5a3P/(b-cYd,/21aeZ/Rfa3CN] vpw /Rxzy;{ |6/R:Y54w}_=/R~Kp€(‚wƒ<‚>Y@lBEDGF HEIUJ L„DNMPO QSI…T MV@lWmX >Y@lBEDGF HEIKJRX\[^]†XsL=>N] ‡†/ ˆ‰w2w21‹ŠŒp~‰Ž/ xN3CY@lBEDGF HEIKJ L„DzMPORQSIUT MV@CW2X >A@CBEDGF HEIKJRX\[^]\X,L>z]  ~Uw ‘N’Nw2x  “eUfa3Vx=Y@lBEDGF HEIKJ L„DzMPORQSIUT MV@CW2X >A@CBEDGF HEIKJRX\[^]\X,L>z]

364 citations

Proceedings Article
12 May 1995
TL;DR: This paper addresses the motion planning problem for a robot in presence of movable objects with an overview of a general approach which consists in building a manipulation graph whose connected components characterize the existence of solutions.
Abstract: This paper addresses the motion planning problem for a robot in presence of movable objects. Motion planning in this context appears as a constrained instance of the coordinated motion planning problem for multiple movable bodies. Indeed, a solution path in the configuration space of the robot and all movable objects is a sequence of transit paths where the robot moves alone and transfer paths where a movable object follows the robot. A major problem is to find the set of configurations where the robot has to grasp or release objects. The paper gives an overview of a general approach which consists in building a manipulation graph whose connected components characterize the existence of solutions. Two planners developed at LAAS-CNRS illustrate how the general formulation can be instantiated in specific cases.

175 citations

Proceedings Article
12 May 1995

160 citations