In this paper we show the process of a class of algorithms parallelization which are used in digital signal processing. We present this approach on the instance of the popular LMS algorithm which is used in noise redu...
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This paper describes a method of augmenting real-time ultrasound imagery with accurate 3D models computed earlier from sources richer in data - Computed Tomography (CT) or Magnetic Resonance (MR) images. The 3D models...
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This paper describes a method of augmenting real-time ultrasound imagery with accurate 3D models computed earlier from sources richer in data - Computed Tomography (CT) or Magnetic Resonance (MR) images. The 3D models are built for a number of phases of motion, therefore a collection of CT / MR scans needs to be taken or techniques such as Cine-MRI can be used. The ultrasound data is processed on-line and the phase of organ motion is estimated at each frame. That information is used to pick a nearest-match 3D model. In this paper we will examine the heart and its motion during its systole-diastole cycle as an example.
This paper describes a problem of designing control laws preserving a motion along desired path for doubly nonholonomic mobile manipulators. The doubly nonholonomic mobile manipulator is composed of a mobile platform ...
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ISBN:
(纸本)9789898425010
This paper describes a problem of designing control laws preserving a motion along desired path for doubly nonholonomic mobile manipulators. The doubly nonholonomic mobile manipulator is composed of a mobile platform moving without slipping effect between wheels and the surface (i.e. nonholonomic platform) and an onboard manipulator equipped with special nonholonomic gears, designed by Nakamura, Chung and Sørdalen. A task for any nonholonomic subsystem (i.e. nonholonomic platform or nonholonomic manipulator) is to follow a desired path - some geometric curve parameterized by curvilinear distance from selected point. A description of the nonholonomic subsystem relative to the desired path using so-called Frenet parametrization is a basis for formulating the path following problem and designing a kinematic control algorithm.
In the paper an adapted version of the differential evolution algorithm has been created to solve a multi-objective optimization problem. Multi-objective Differential Evolution Algorithm using vector differences for p...
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ISBN:
(纸本)9781424476527
In the paper an adapted version of the differential evolution algorithm has been created to solve a multi-objective optimization problem. Multi-objective Differential Evolution Algorithm using vector differences for perturbing the vector population with self adaptation is introduced. Through the combination of mutation strategies and self adaptation of crossover and differentiation constants the proposed MO algorithm performs better than the one with the simple DE scheme in terms of computation speed and quality of the generated multi-objective non-dominated solutions.
We address the motion planning problem in non-holonomic robotic systems with constraints imposed on configuration and control variables. The imbalanced Jacobian motion planning algorithm is compared with the optimal c...
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We address the motion planning problem in non-holonomic robotic systems with constraints imposed on configuration and control variables. The imbalanced Jacobian motion planning algorithm is compared with the optimal control approach. computer simulations of the unicycle-type mobile robot underlie the comparison.
Summary form only given. Approaches used to solve optimization tasks generated in problems of control, planning, designing and management have completely changed during recent years. Cases with unimodal, convex, diffe...
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Summary form only given. Approaches used to solve optimization tasks generated in problems of control, planning, designing and management have completely changed during recent years. Cases with unimodal, convex, differentiable scalar goal functions have disappeared from research labs, because a lot of satisfactory efficient methods were developed. On the battle square there have remained hard cases: multimodal, multi-criteria, non-differentiable, NP-hard, discrete, with huge dimensionality. These practical tasks, generated by industry and market, have caused serious troubles in seeking global optimum. Main reasons of these troubles are recognized as: huge cardinality of local extremes frequently with the exponential number of extremes; curse of dimensionality; NP-hardness; lack of differentiability. Unfortunately, known “classical” exact solution methods have considered as rather weak in so hard conditions of the work. From the beginning of eighties have been observed fast development of approximate methods, resistant to local extremes. In fact, practice of these methods antecede development of the suitable theory, which has been formed usually 10-15 years later than the time moment of creating the approach. That's why we observe now more than 20 different approaches inspired by Nature and more than 30 if we include parallel computing environments. The paper presents critical survey of methods, approaches and trends observed in modern optimization, focusing on nature-inspired techniques recommended for particularly hard problems. Applicability of the methods, depending the class of stated optimization task and classes of goal function, have been discussed. Numerical as well theoretical properties of these algorithms are shown. Newest our own very efficient proposals are also provided.
In this paper a method to speed up a convergence of the Newton algorithm of motion planning for manipulators was presented. The method couples one dimensional optimization (with respect to a coefficient influencing th...
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In this paper a method to speed up a convergence of the Newton algorithm of motion planning for manipulators was presented. The method couples one dimensional optimization (with respect to a coefficient influencing the convergence property of the algorithm) with a virtual goal replacing a real goal of the planning. The first modification of the basic Newton algorithm can be used for any taskspace while the second one works only for low dimensional (not greater than 3) taskspaces. An algorithm based on the method was provided and its efficiency was illustrated on a planar double pendulum manipulator.
The aim of signal decomposition in wavelet bases is to represent a signal as a sequence of wavelet coefficients sets. There is proposed a multistage classification rule using on every stage only one set of the signal ...
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The aim of signal decomposition in wavelet bases is to represent a signal as a sequence of wavelet coefficients sets. There is proposed a multistage classification rule using on every stage only one set of the signal coefficients. The hierarchical construction of wavelet multiresolution analysis was an inspiration for the multistage classification rule. The algorithm makes an optimal decision for every set of coefficients and its main advantage is a smaller dimension of classification problem on every stage.
In developing nano-devices and nano-structures, traditional methodologies on MEMS meet the difficulty from the scale restriction. With the strategy of objects assembly, using AFM to handle nano-rods and other nano-obj...
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This paper addresses a constrained motion planning problem for mobile manipulators. The constraints are included into the system model by means of a sort of penalty function, and then processed in accordance with the ...
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This paper addresses a constrained motion planning problem for mobile manipulators. The constraints are included into the system model by means of a sort of penalty function, and then processed in accordance with the endogenous configuration space approach. Main novelty of this paper lies in deriving a constrained Jacobian motion planning algorithm with the following features: inequality constraints are included into an extended kinematics model using a smooth approximation of the plus function, the model is then regularized against singularities, and the resulting imbalance in error equations is handled as a perturbation of an exponentially stable linear dynamic system. The operation of the constrained motion planning algorithm is illustrated by a motion planning problem of a mobile manipulator with bounds imposed on a platform variable. Performance of the algorithm is tested by computer simulations.
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