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This paper presents a novel fuzzy genetic algorithm (GA) approach to tackling the problem of trajectory planning of two collaborative robot manipulators sharing a common workspace, where the manipulators have to consider each other as a moving obstacle whose trajectory or behaviour is unknown and unpredictable, as each manipulator has individual goals and where both have the same priority. The goals are not restricted to a given set of joint values, but are specified in the workspace as coordinates at which it is desired to place the end-effector of the manipulator. By not constraining the goal to the joint space, the number of possible solutions that satisfies the goal increases according to the number of degrees of freedom of the manipulators. A simple GA planner is used to produce an initial estimation of the movements of the robots' articulations and collision free motion is obtained by the corrective action of the collision-avoidance fuzzy units. [ABSTRACT FROM AUTHOR]

Investigates the potential use of fuzzy logic to enhance the performance of statistical process control (SPC). Definition of SPC; Design and implementation of the fuzzy expert system (FES); Role of FES in the performance of SPC; Efficiency of FES.

Proposes a model of cerebellum motor learning based on a neuroadaptive robot manipulator controller. Artificial neuroadaptive robot manipulator model; Application of neuroadaptive controller cerebellum model in driving a two-link arm; Robot motion in a constrained environment.

This paper describes a framework for summarizing and comparing the distributions of image features on anatomical shape surfaces in populations. The approach uses a point-based correspondence model to establish a mapping among surface positions and may be useful for anatomy that exhibits a relatively high degree of shape variability, such as cardiac anatomy. The approach is motivated by the MRI-based study of diseased, or fibrotic , tissue in the left atrium of atrial fibrillation (AF) patients, which has been difficult to measure quantitatively using more established image and surface registration techniques. The proposed method is to establish a set of point correspondences across a population of shape surfaces that provides a mapping from any surface to a common coordinate frame, where local features like fibrosis can be directly compared. To establish correspondence, we use a previously-described statistical optimization of particle-based shape representations. For our atrial fibrillation population, the proposed method provides evidence that more intense and widely distributed fibrosis patterns exist in patients that do not respond well to radiofrequency ablation therapy.