Abstract – This paper presents sensor-based intelligent mobile robot navigation in unknown environments. The paper deals with fuzzy control of autonomous mobile robot motion in an unknown environment with obstacles and gives a wireless sensor-based remote control of mobile robots motion in an unknown environment with obstacles using the Sun SPOT technology. Simulation results show the effective...

This paper presents an optimization of POSIT (Pose from Orthographic and Scaling with Iterations), a model-based camera location algorithm, in the domain of indoor mobile robot navigation. The method finds the rotation matrix and the translation vector of the camera with respect to an object. The novelty of the proposed modified algorithm is that it does not need the perfect knowledge of camera...

The work presents the development of a complex navigational behavior combining some simple fuzzy behaviors for a mobile agricultural robot (MAR). Fuzzy rules are used to compose and coordinate the simple behaviors and an experimental robotic platform based on Khepera mini-robot is proposed to simulate and support the researches on behavior based architecture for agricultural robots. The mini-ro...

AbSTRACT This work is intended to give an overview of technologies, developed from an artificial intelligence standpoint, devised to face the different planning and control problems involved in trajectory generation for mobile robots. The purpose of this analysis is to give a current context to present the Evolutionary Robotics approach to the problem, which is now being considered as a feasibl...

This paper presents an emotion based process gener ating cognition through learning Two models are de scribed which investigates the possibilities of designing cognitive systems based on emotion In order to test these models through experiments we used a mobile robot simulator Webots modeling the real Khepera robot The rst proposed model is the simplest since it uses only positive and negative ...

A biologically inspired computational model of rodent representation–based (locale) navigation is presented. The model combines visual input in the form of realistic two dimensional grey-scale images and odometer signals to drive the firing of simulated place and head direction cells via Hebbian synapses. The space representation is built incrementally and on-line without any prior information ...

Due to their distributed architecture, artificial neural networks often show a graceful performance degradation to the loss of few units or connections. Living systems also display an additional source of fault-tolerance obtained through distributed processes of self-healing: defective components are actively regenerated. In this paper, we present results obtained with a model of development fo...

Giving robots the ability to learn without the guidance of a researcher is a practical method of developing more adaptable and intelligent systems. Self-Organizing Distinctive-State Abstraction (SODA) is an algorithm that allows a robot to learn routines from from raw sensorimotor inputs through training. The goal of our experiment was to implement SODA on a simulated version of the Khepera II ...

In this paper, a new coevolutive method, called Uniform Coevolution, is introduced to learn weights of a neural network controller in autonomous robots. An evolutionary strategy is used to learn high-performance reactive behavior for navigation and collisions avoidance. The introduction of coevolutive over evolutionary strategies allows evolving the environment, to learn a general behavior able...