We present an efficient path planning approach which represents a path by a series of via points connected by elastic strings that are subject to displacement due to collisions with obstacles as well as constraints pe...
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We present an efficient path planning approach which represents a path by a series of via points connected by elastic strings that are subject to displacement due to collisions with obstacles as well as constraints pertaining to the domain to which path planning is applied. Obstacle regions are represented by a potential field created by a multilayered neural network. A fast simulated annealing approach is used for local minima problems from the potential field. The automatic generation and removal of via points is incorporated in the path planning approach to ensure collision-free planning regardless of the complexity of the environment (e.g., convex, concave or complicated obstacle regions). Our path planning approach is flexible due to the automatic generation and removal of via points based on the complexity of the domain of the path planning process, efficient due to the use of the necessary via points for the path representation at all times, and massively parallel due to the parallel computation of motions of via points with only local information.
We present an efficient potential-field based path planning approach for point or higher dimensional objects which avoids effectively any local extreme problems. The approach represents a path by a series of via point...
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We present an efficient potential-field based path planning approach for point or higher dimensional objects which avoids effectively any local extreme problems. The approach represents a path by a series of via points connected by elastic strings which are subject to displacement due to collisions with obstacle regions as well as constraints pertaining to the domain to which path planning is applied. Obstacle regions are represented by a potential field created by a multilayered neural network. A fast simulated annealing approach is used for local minima problems from the potential field. The automatic generation and removal of via points is incorporated in the path planning approach to ensure collision-free planning regardless of the complexity of the environment. Local and global bias on the potential field is used to avoid any existing singularities and local minima. Our path planning approach is flexible, efficient and massively parallel.
A new paradigm of event-based robotic and telerobotic control, referred to here as the reference adaptive impedance control, is presented for partially constrained robotic and telerobotic tasks under uncertain or unkn...
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ISBN:
(纸本)0780341600
A new paradigm of event-based robotic and telerobotic control, referred to here as the reference adaptive impedance control, is presented for partially constrained robotic and telerobotic tasks under uncertain or unknown environmental constraints. The reference adaptive impedance control determines the desired next state adaptively, in such a way as to follow the optimal path from the current state, where the optimal path is generated with the environmental constraints updated through time. The embedded impedance control provides a mechanism for collecting more complete information on the environment. The reference adaptive impedance control also serves as a powerful tool for implementing shared control in teleoperation. A case study of robotic and telerobotic soil trenching is given with simulations.
This paper describes an effcient and simple coding algorithm of universally optimal codes for stationary (ergodic) sources and noiseless channel with unequal symbol costs. The symbol cost indicates the required time (...
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This paper describes an effcient and simple coding algorithm of universally optimal codes for stationary (ergodic) sources and noiseless channel with unequal symbol costs. The symbol cost indicates the required time (or space) for the transmission (or storage) of that symbol, and the cost of any code symbol depends only on that symbol. The proposed coding algorithm mainly consists of two parts. The first part is based on the well-known Ziv-Lempel coding algorithm proposed in 1978 (sometimes called LZ78), and the second part is based on the Varn coding algorithm. The coding algorithm asymptotically achieves an optimal average cost of codes for stationary sources, and also achieves an optimal cost of codes for stationary ergodic sources with probability one. Furthermore, the computational complexity of the proposed coding algorithm is linear with respect to the length of source sequence and coded sequence.
This paper describes an efficient and simple construction of a universal coding scheme for a noiseless channel with unequal symbol costs, and clarifies its asymptotic performance with respect to stationary sources or ...
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This paper describes an efficient and simple construction of a universal coding scheme for a noiseless channel with unequal symbol costs, and clarifies its asymptotic performance with respect to stationary sources or stationary ergodic sources. The symbol cost now indicates the time (or space) for the transmission (or storage) of that symbol, and the cost of transmitting (or storing) any code symbol depends only on that symbol. For example, in the Morse code, the dot is shorter in time duration than the dash.
One way to find an optimal plan is to enumerate all plans and evaluate a quality metric for each plan. However it is well known that N parts can have up to O(2/sup N/) assembly plans. Reducing N by grouping parts has ...
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One way to find an optimal plan is to enumerate all plans and evaluate a quality metric for each plan. However it is well known that N parts can have up to O(2/sup N/) assembly plans. Reducing N by grouping parts has been proposed earlier but to our knowledge has not been formally defined. In this paper we define two types of groups in terms of part geometry using the nondirectional blocking graph and binary adjacency matrices defined by Wilson and Latombe (1994). We give a polynomial time algorithm for identifying serial and parallel groups. We tested the algorithm on two planar assemblies where it reduced plan time by a factor of 4.
In this paper a method for collision detection and collision avoidance for dual arm robots is proposed. The collision detection, a fast geometric approach based on link intersection, detects the collision and construc...
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In this paper a method for collision detection and collision avoidance for dual arm robots is proposed. The collision detection, a fast geometric approach based on link intersection, detects the collision and constructs the collision region for given trajectories. The time delay planning determines the minimum necessary time delay to avoid collisions using a potential field representation for collision regions. The planning is based on a flexible, massively parallel approach. It effectively avoids any local minima problems due to the potential field representation and can be used regardless of the complexity of the collision region (e.g., concave or complicated regions).
Over recent years, the focus of artificial intelligence (AI) research has shifted from top-down simulation of high-level cognitive functions based on (essentially-ungrounded) symbolic computations to consideration of ...
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Over recent years, the focus of artificial intelligence (AI) research has shifted from top-down simulation of high-level cognitive functions based on (essentially-ungrounded) symbolic computations to consideration of the way that intelligent behaviour can emerge in bottom-up fashion in systems situated in the 'real' world. Inspirations from neurobiology and concepts of neural information processing have been very influential in this 'new' AI: most usually in the guise of 'parallel distributed processing' approaches operating at a high level of abstraction, or the more detailed and biologically-realistic 'computational neuroscience' paradigm. In this paper, we describe a biologically-motivated approach to learning in situated robots based on the computational neuroscience paradigm. The mechanisms by which such learning occurs are habituation, sensitization and classical conditioning of the neural responses involved in basic, pre-existing ('hand-wired') reflexes. Emergent light-seeking and collision-avoidance behaviors are observed in an adaptive mobile robot embodying these learning principles, as a result of interaction with its environment.
This article reviews the development of experimental visual tracking algorithms which have been implemented using TRICLOPS (The Real-time, intelligently-ControLled Optical Positioning System), a high-performance activ...
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Spatial scheduling considers not only traditional scheduling constraints like resource capacity and due dates, but also dynamic spatial layout of the objects. Automation of spatial scheduling is particularly important...
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Spatial scheduling considers not only traditional scheduling constraints like resource capacity and due dates, but also dynamic spatial layout of the objects. Automation of spatial scheduling is particularly important when the spatial resources are critical bottleneck resources, as is the case in the shipbuilding industry. To develop a spatial scheduling expert system for shipbuilding, a methodology for spatial layout of polygonal objects within rectangular plates is first developed. This study is then extended to the methodology for spatial scheduling, including the lime dimension. The methodology is applied to the scheduling of Daewoo shipbuilding to build a system DAS-CURVE. DAS-CURVE is successfully operational and its experimental performance is remarkable. Copyright (C) 1996 Elsevier Science Ltd
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