The operation of the quantum free-electron lasers (QFELs) with a helical wiggler and in the presence of ion-channel guiding is considered. The quantum Hamiltonian of single particle has been derived in the Bambini-Renieri (BR) frame. Time dependent wave function and three constants of motion are obtained. The Raman-Nath equation (RNE) and its approximation solution have been calculated, and then the resulted solution has been employed to obtain the quantum gain, photon statistics parameter and squeezing parameter. A quantum approach has been used to get quantum statistical properties of the FEL and the photon gain formula for the small signal gain limit. It is found that the ion-channel guiding decreases the squeezing. Also, the conditions for positive (bunching) and negative (antibunching) gain have been studied numerically.

A theory of two-stream free-electron laser in a combined electromagnetic wiggler and an ion-channel guiding is developed. In the analysis, the electron trajectories and the small signal gain are derived by considering the effects of self-fields. Numerical calculations show that there are seven group's trajectories rather than nine groups reported in Mehdian and Saviz (2010 Chin. Phys. B 19(1), 014214). The comparison of the normalized gains and their corresponding normalized frequencies by employing the axial magnetic field and ion-channel guiding, with and without self-fields, in FEL has been studied numerically. The results show that the normalized maximum gain in FEL with axial magnetic is larger than that for using ion-channel guiding except in small region, but the results for their corresponding normalized frequencies are opposite.

An algorithm is presented for the recognition of a set of prototype, solid objects. Cost estimate and simulation results suggest that the algorithm would provide rapid recognition of the objects over a greater range of horizontal, vertical and rotational errors, in the position of the object than is likely to be encountered in practice.

This paper outlines a method for control of robotic systems for part sorting operations in unstructured manufacturing environments. The sorting is accomplished simply and without any change in the kinematic structure of the robot or any need for inclusion of complicated external sensory systems. The method developed is based on the inherent relationship between the mass of parts to be carried and the maximum velocity of the tool centre point attainable along certain specified paths.

The actuators' maximum velocity is detected and is communicated to a devised expert system. The expert system uses this maximum velocity as a part of its matching procedure for the purpose of part sorting.

This paper presents a sensory gripper, consisting of two tactile sensing matrices which acquire three dimensional images of objects of interest. The image processing algorithm uses elastostatic contact information to discriminate among a host of parts made of different materials. The algorithm also enables the assessment of orientation of parts without the pre-requisite of having to recognise them. The positions of stable holdsites and a safe gripping force are also evaluated.

A binary tactile image feature extraction algorithm using image primitive notation and perceptrons is presented. The basic image segments are defined as geometric factors by which the image structure is described so that effective feature values such as image shape, image size, perimeter and texture may be extracted on the basis of local image computation. The local property of the tactile image computation is evaluated by the concept called order of the perceptrons and based on this feature extraction algorithm, an efficient tactile image recognition system is realised.

This paper outlines the analysis methodology employed in the design of an anthropomorphic hand for the purposes of object handling by robotic manipulators, and for prosthetics. The final design is described and the safe handling of various objects using this anthropomorphic hand is discussed.