The goal of this work is to compare fuzzy, neural network and neuro-fuzzy approaches to the control of mobile robots. The rst part of this paper is devoted to the formal framework of fuzzy controllers. Results of an example of their use for a mobile robot are discussed. As an experimental platform, the Khepera mobile robot is used. The same example is studied using artiicial neural networks. Fo...

This work presents the application of a new hybrid neuro-fuzzy model, called RL-HNFP (Reinforcement Learning – Neuro Fuzzy Hierarchical Politree), in automatic learning of autonomous robots. This model provides an agent with intelligence, making it capable, by interacting with its environment, to acquire and retain knowledge for reasoning (infer an action). Promising results have already been o...

— Dissociated culture system with multi-electrode array is fully useful for elucidation of network dynamics of neurons. The living neuronal network can obtain a kind of “learning and memory, i.e., intelligence” by interactions with outer world. In this paper, we introduce Biologically Inspired Model as a fuzzy computational system for living neuronal networks connected to moving robot, Khepera ...

A novel robot learning algorithm called Predictive Sequence Learning (PSL) is presented and evaluated. PSL is a model-free prediction algorithm inspired by the dynamic temporal difference algorithm S-Learning. While S-Learning has previously been applied as a reinforcement learning algorithm for robots, PSL is here applied to a Learning from Demonstration problem. The proposed algorithm is eval...

In this paper, we study the path planning for khepera II mobile robot in an unknown environment. The well known heuristic D* lite algorithm is implemented to make the mobile robot navigate through static obstacles and find the shortest path from an initial position to a target position by avoiding the obstacles. and to perform efficient re-planning during exploration. The proposed path finding ...

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 ...

Local reconstruction of differential-drive mobile robots position and orientation is made possible with an accurate odometry calibration. Starting from the encoders readings, and assuming an absolute measurement available, a deterministic filter to localize the vehicle while estimating a proper set of odometric parameters is proposed. A stability analysis guarantees that the position and orient...

Behavioral robustness at antibody and immune network levels is discussed. The robustness of the immune response that drives an autonomous mobile robot is examined with computational experiments in the trajectory generation context in unknown environments. The immune response is met based on the immune network metaphor for different low-level behaviors coordination. These behaviors are activated...