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For educational purposes there is a need to teach electrical and computer engineering students the basics of the design of state machines using programmable logic devices, and for students interested in mobile robots to teach them the basics of mobile robots' behaviors. At the same time one of the topics of interest in the mobile robot's community is how to generate their new behaviors, using state...
Effective control of autonomous robots evolving in dynamic and unpredictable environments is a hard problem. The challenging issue is to achieve this control while the robot is performing a constrained and an interactive task. Namely, our aim is endow a mobile manipulator by controllers allowing safe and effective interactions with humans. This multi criteria optimization problem includes the coordination...
This paper deals with a method of distributed behavior learning of multiple mobile robots. Various types of artificial neural networks are applied for behavior learning of mobile robots in unknown and dynamic environments. In the paper, we propose a method of distributed behavioral learning based on a spiking neural network. The robot learns the forward relationship from sensory inputs to motor outputs...
In this paper we exercise the genetic programming of a artificial neural network (ANN) that integrates sensor vision, path planning and steering control of a mobile robot. The training of the ANN is done by a simulation of the robot, its sensors, and environment. The results of each simulation run are then used to denote the ability for the tested network to operate the robot. After less than hundred...
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