The least-squares policy iteration approach works efficiently in value function approximation, given appropriate basis functions. Because of its smoothness, the Gaussian kernel is a popular and useful choice as a basis function. However, it does not allow for discontinuity which typically arises in real-world reinforcement learning tasks. To overcome this problem, new basis functions called geo...

Behaviors such as exploration and homing, that seemingly demand a complex control system, only require a perceptron that connects a robot’s sensors to its motors. This is shown by evolving such neurocontrollers for the Khepera robot. An exploitation of the robot’s perception of the environment’s geometrical shape allows the robot to encode time, even though explicitly it is not presented with t...

The objective of this paper is to devise a vision-based control scheme for the Khepera-II robot to achieve efficient object tracking using fuzzy logic. The robot is equipped with a K2D video turret. The algorithm was verified in simulation study by the Webots simulator using a colored ball as the sample object. Pattern recognition was not performed hence the algorithm can be used for tracking t...

The least-squares policy iteration approach works efficiently in value function approximation, given appropriate basis functions. Because of its smoothness, the Gaussian kernel is a popular and useful choice as a basis function. However, it does not allow for discontinuity which typically arises in real-world reinforcement learning tasks. In this paper, we propose a new basis function based on ...

This paper provides a new approach to the multi-robot path planning problem predicting the position of a dynamic obstacle which undergoes linear motion in the given workspace changing its direction at regular intervals of time. The prediction is done in order to avoid collision of the robots with the dynamic obstacle. First the work is done in simulation environment then the entire work has bee...

Mobile robots offer a typical example of systems with nonholonomic constraints. Several controllers have been proposed in the literature for stabilizing these systems. However, few experimental studies have been reported comparing the characteristics and the performance of these controllers with respect to neglected dynamics, quantization, noise, delays, etc. In this paper, we use a Khepera mob...

The purpose of this chapter is to introduce gently the basics concepts of Bayesian Programming. After a short formal introduction of Bayesian Programming, we present these concepts using three simple experiments with the mini mobile robot Khepera. These three instances have been selected among the numerous experiments done with this robots for their simplicity and didactic quality. A more exten...

We have used an automatic programming method called genetic programming (GP) for control of a miniature robot. Our earlier work on real-time learning suffered from the drawback of the learning time being limited by the response dynamics of the robot's environment. In order to overcome this problem we have devised a new technique which allows learning from past experiences that are stored in mem...

We have used an automatic programming method called Genetic Programming (GP) for control of a miniature robot. Our earlier work on real-time learning su ered from the drawback of the learning time being limited by the response dynamics of the robot's environment. In order to overcome this problem we have devised a new technique which allows learning from past experiences that are stored in memo...

This paper presents preliminary results of an experimental study that intends to find the best chemical volatiles to mark odourific trails with mobile robots. The characteristics of the chemicals chosen for this purpose is presented and the influence of the substrate permeability on the ability to detect those chemicals along the time is analysed. The detection of a chemical trail by a Khepera ...