This paper presents a new algorithm for global path planning to a goal for a mobile robot using Genetic Algorithm (GA). A genetic algorithm is used to find the optimal path for a mobile robot to move in a static environment expressed by a map with nodes and links. Locations of target and obstacles to $nd an optimal path are given in an environment that is a 2-0 workplace. Each via point (landmark) in the net is a gene which is represented using binary code. The number of genes in one chromosome is function of the number of obstacles in the map. Therefore, we used a $xed length chromosome. The generated robot path is optimal in the sense of the shortest distance. The robot has a starting point and a target point under the assumption that the robot passes each point oni) once or not at all. The obtained results in simulation af$rmed the potential of the proposed algorithm.

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This paper presents the design of an embedded control system for insulin pump. The insulin pump is an integrated component in any closed loop insulin delivery system for type 1 diabetes. The pump consists of three main components: micro-needles, insulin reservoir(syringe), and piezoelectric (PZT) linear servo motor. The actuated syringe has an injection back pressure that resists the linear motion of the driving PZT motor. This back pressure acts as a disturbance and leads to in accurate position and consequently an imprecise insulin dosage. Therefore, a highly precise positioning control on the pump is required to control the insulin dosage and to maintain the blood glucose level in its safe range. The proposed controller is designed using fuzzy logic as a nonlinear controller to compensate any non-modeled nonlinear ities in the system.The embedded controller for the PZT motor can be implemented using FPGA or microcontroller chip. This controller acts as a slave and responds to its master controller which controls the complete closed loop insulin delivery system.