Abstract This research focuses on the performance of obstacle avoidance feature implemented a wheeled mobile robot by using Sugeno Fuzzy Inference System (FIS). The test was done simulation software Webots and layout first draft out walls, floors, objects in order to set boundary obstacles for simulation. To effectiveness efficiency terms time distance, trajectory Khepera implementing FIS recor...

An experimental comparison among the main behavioral control techniques for autonomous mobile robots is presented in this paper. The behavioral algorithms tackle the problem in a similar way: they decompose the mission planning of the robot in simple tasks; each task is then approached independently from the others and, at the end, the behavioral algorithms arrange the tasks’ output to give an ...

A distributed mobile robot software application infrastructure is developed, improving integration and leverage between projects in a research environment. The resulting design includes a three layer CORBA based, service broker application architecture. A reference implementation and tests on B21r, LEGO Mindstorm and Khepera robots demonstrate the feasibility of the design.

In this paper, we present the implementation, both in a simulator and in a real-robot version, of an efficient solution to the so-called dynamical nightwatch’s problem on the micro-robot Khepera. The problem consists mainly in exploring a previously unknown environment while detecting, registering and recognizing light sources which may dynamically be turned on and off. At the end of each round...

The advantages and disadvantages of evolving neural control systems for mobile robots using genetic algorithms are investigated. The Khepera robot is trained using the evolutionary neural networks (E“) algorithm for the task of obstacle avoidance. The feasibility of using Q-learning for robot learning is also studied. It is found that Q-learning can be successfully used to train a robot and is ...

The performances of an EKF-based SLAM approach are experimentally discussed in the case of a mini-robot equipped with low-cost IR sensors only, showing that despite of the sparseness and noisiness of the sensors, SLAM experiments using classical SLAM methods can be performed even on a Khepera robot in a real arena, whose dimensions may be significantly larger than the robot size. The main chara...

In this paper, we compare the performance of hierarchical GP methods (Automatically Defined Functions, Module Acquisition, Adaptive Representation through Learning) with the canonical GP Implementation and with a linear genome GP system in the domain of evolving robotic controllers for a simulated Khepera miniature robot. We successfully evolve robotic controllers to accomplish obstacle avoidan...

Habituation is a form of non-associative learning observed in a variety of species of animals. Arguably, it is the simplest form of learning. Nonetheless, the ability to habituate to certain stimuli implies plastic neural systems and adaptive behaviors. This article describes how computational models of habituation can be applied to real robots. In particular, we discuss the problem of the osci...

A model-free learning algorithm called Predictive Sequence Learning (PSL) is presented and evaluated in a robot Learning from Demonstration (LFD) setting. PSL is inspired by several functional models of the brain. It constructs sequences of predictable sensory-motor patterns, without relying on predefined higher-level concepts. The algorithm is demonstrated on a Khepera II robot in four differe...