Mass transfer through a liquid membrane was studied in a macroscopic setup that allowed an estimate of the resistance to interface crossing. It was found that the interfacial transfer was associated with the phase behavior and physicochemical formulation of the surfactant-oil-water system. The resistance to interfacial mass transfer closely followed the variation of interfacial tension, i.e., it was minimal at the optimal formulation of the so-called Winsor III phase behavior systems.

This paper presents a new version of the camera-spacemanipulation method (CSM). The set of nonlinear view parameters of the classic CSM is replaced with a linear model. Simulations and experiments show a similar precision error for the two methods. However, the new approach is simpler to implement and is faster.Index Terms-Camera matrix, camera-space manipulation (CSM), pinhole camera model, robot control, vision-based control.

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In this paper the workspace and payload capacity of a new design of reconfigurable Delta-type parallel robot is analysed. The reconfiguration is achieved by adjusting the length of the kinematic chains of a given robot link simultaneously and symmetrically during the operation of the robot. This would produce a dynamic workspace in shape and volume. A numerical analysis of the variation of shape and volume of the workspace and payload capacity of the robot is presented. Based both on the results of this analysis and on practical requirements, a proposal for the design of a reconfiguring mechanism is presented.

Purpose The purpose of this paper is to present a new vision-based control method, which enables delta-type parallel robots to track and manipulate objects moving in arbitrary trajectories. This constitutes an enhanced variant of the linear camera model-camera space manipulation (LCM-CSM). Design/methodology/approach After obtaining the LCM-CSM view parameters, a moving target’s position and its velocity are estimated in camera space using Kalman filter. The robot is then commanded to reach the target. The proposed control strategy has been experimentally validated using a PARALLIX LKF-2040, an academic delta-type parallel platform and seven different target trajectories for which the positioning errors were recorded. Findings For objects that moved manually along a sawtooth, zigzag or increasing spiral trajectory with changing velocities, a maximum positioning error of 4.31 mm was found, whereas objects that moved on a conveyor belt at constant velocity ranging from 7 to 12 cm/s, average errors between 2.2-2.75 mm were obtained. For static objects, an average error of 1.48 mm was found. Without vision-based control, the experimental platform used has a static positioning accuracy of 3.17 mm. Practical implications The LCM-CSM method has a low computational cost and does not require calibration or computation of Jacobians. The new variant of LCM-CSM takes advantage of aforementioned characteristics and applies them to vision-based control of parallel robots interacting with moving objects. Originality/value A new variant of the LCM-CSM method, traditionally used only for static positioning of a robot’s end-effector, was applied to parallel robots enabling the manipulation of objects moving along unknown trajectories.