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This paper presents a novel method for singularity-free path planning and obstacle avoidance of parallel manipulators. A modified 3-4-5 interpolating polynomial is used to plan a trajectory for a planar 3-DOF parallel manipulator. The polynomial function which is smooth and continuous in displacement, velocity, and acceleration is used to find a smooth path avoiding the obstacles and singularities. An artificial neural network is implemented to solve forward kinematics of the manipulator to estimate the distance between gripper and singularity or obstacle. The simulating results demonstrate the efficiency of the proposed algorithm. [ABSTRACT FROM AUTHOR]

The discrimination of the composition of environmental and non-environmental materials by the estimation of the 234 U/ 238 U activity ratio in alpha-particle spectrometry is important in many applications. If the interfering elements are not completely separated from the uranium, they can interfere with the determination of 234 U. Thickness as a result of the existence of iron in the source preparation phase and their alpha lines can broaden the alpha line of 234 U in alpha spectra. Therefore, the asymmetric broadening of the alpha line of 234 U and overlapping of peaks make the analysis of the alpha particle spectra and the interpretation of the results difficult. Applying Artificial Neural Network (ANN) to a spectrometry system is a good idea because it eliminates limitations of classical approaches by extracting the desired information from the input data. In this work, the average of a partial uranium raw spectrum, were considered. Each point that its slope was of the order of 0–1% per 10 channels, was used as input to the multi-layer feed forward error-back propagation network. The network was trained by an alpha spectrum library which has been developed in the present work. The training data in this study was actual spectral data with any reasonable thickness and interfering elements. According to the results, the method applied to estimate the activity ratio in this work, can examine the alpha spectrum for peaks which would not be expected for a source of given element and provide the clues about composition of uranium contamination in the environmental samples in a fast screening and classifying procedures. [ABSTRACT FROM AUTHOR]