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  • COMPUTER SYSTEMS  (1)
  • collision avoidance  (1)
  • geometric reasoning  (1)
  • 1
    Electronic Resource
    Electronic Resource
    Springer
    Journal of intelligent manufacturing 2 (1991), S. 315-326 
    ISSN: 1572-8145
    Keywords: Path planning ; neural optimization ; path representation ; collision avoidance ; potential field
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mechanical Engineering, Materials Science, Production Engineering, Mining and Metallurgy, Traffic Engineering, Precision Mechanics
    Notes: Abstract Automatic path planning plays an essential role in planning of assembly or disassembly of products, motions of robot manipulators handling part, and material transfer by mobile robots in an intelligent and flexible manufacturing environment. The conventional methodologies based on geometric reasoning suffer not only from the algorithmic difficulty but also from the excessive time complexity in dealing with 3-D path planning. This paper presents a massively parallel, connectionist algorithm for collision-free path planning. The path planning algorithm is based on representing a path as a series ofvia points or beads connected by elastic strings which are subject to displacement due to a potential field or a collision penalty function generated by polyhedral obstacles. Mathematically, this is equivalent to optimizing a cost function, defined in terms of the total path length and the collision penalty function, by moving thevia points simultaneously but individually in the direction that minimizes the cost function. Massive parallelism comes mainly from: (1) the connectionist model representation of obstacles and (2) the parallel computation of individualvia-point motions with only local information. The algorithm has power to deal effectively with path planning of three-dimensional objects with translational and rotational motions. Finally, the algorithm incorporates simulated annealing to solve a local minimum problem. Simulation results are shown.
    Type of Medium: Electronic Resource
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  • 2
    Electronic Resource
    Electronic Resource
    Springer
    Journal of intelligent manufacturing 4 (1993), S. 183-198 
    ISSN: 1572-8145
    Keywords: Assembly planning ; subassembly ; liaison graph ; geometric reasoning ; assembly cost ; stability ; partial-order graph
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mechanical Engineering, Materials Science, Production Engineering, Mining and Metallurgy, Traffic Engineering, Precision Mechanics
    Notes: The distribution of assembly workstations enables assembly operations to be done in parallel, while the multiple routing of parts in flexible assembly systems allows the opportunistic scheduling of assembly operations. This paper presents an assembly planning system, called the Assembly Coplanner, which automatically constructs an assembly partial order and generates a set of assembly instructions from a liaison graph representation of an assembly based on the extraction of preferred subassemblies. Assembly planning in Coplanner is carried out by the co-operation of multiple planning agents, such as the geometric reasoner, the physical reasoner, the resource manager and the plan coordinator, under the constraints of finding a cost-effective assembly plan in a flexible assembly system. The Coplanner identifies spatial parallelism in assembly as a means of constructing temporal parallelism among assembly operations. This is achieved in the following way: (1) the selection of a set of tentative subassemblies by decomposing a liaison graph into a set of subgraphs based on feasibility and difficulty of disassembly; (2) the evaluation of each of the tentative subassemblies in terms of assembly cost represented by subassembly selection indices; and (3) the construction of a hierarchical partial order graph (HPOG) as an assembly plan. A case study applying the Coplanner to a mechanical assembly is illustrated in this paper.
    Type of Medium: Electronic Resource
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  • 3
    Publication Date: 2011-08-24
    Description: Sensing-knowledge-command (SKC) fusion is presented as a fundamental paradigm of implementing cooperative control for an advanced man-machine system. SKC fusion operates on the 'SKC fusion network,' which represents the connection between sensor data to commands through knowledge. Sensing, knowledge, and command of a human and a machine are tapped into the network to provide inputs, or stimuli, to the network. Such stimuli automatically invoke an SKC fusion process and generate a fused output for cooperative control. Once invoked by stimuli, the SKC fusion process forces the network to converge to a new equilibrium state through the network dynamics composed of data fusion, feature transformation, and constraint propagation. The SKC fusion process thus integrates redundant information, maintains network consistency, identifies faulty data and concepts, and specifies those concepts to be strengthened through sensor planning.
    Keywords: COMPUTER SYSTEMS
    Type: In: Sensor fusion III: 3-D perception and recognition; Proceedings of the Meeting, Boston, MA, Nov. 5-8, 1990 (A93-24993 08-63); p. 391-402.
    Format: text
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