Motion planning is essential for mobile robot successful navigation. There are many algorithms for motion planning under various constraints. However, in some cases the h [...]

The paper presents both hardware and software means used to develop a scalable low/middle level control system for the autonomous mobile robot Advee. Brief description of [...]

Presented paper deals with a global localization of an autonomous mobile robot in indoor environment. The method is based on the application of Bayesian filter algorithm [...]

The achievable force at the end of human forearm depends on the forearm position. The actual value of this force is one of the most important variables affecting the desi [...]

This paper deals with the probabilistic model of wheel robot motion. Such probabilistic model is often used in navigation algorithms for prediction of the real position o [...]

The paper describes the high level software issues in the task of autonomous robot driving on the park pavement. The wheel robot is equipped with limited number of sensor [...]

This paper describes our approach to control of the two types of experimental devices for biomechanics. First type of experimental device is the device for examining the [...]

Locally Weighted Learning (LWR) is a class of approximations, based on a local model. In this paper we demonstrate using LWR together with Q-learning for control tasks. Q [...]

The creation of direct kinematic model is relatively simply in contrast with creation of analytic inverse model. With using of approximating methods is inverse modelling [...]

Abstrakt: A great intention is lately focused on Reinforcement Learning (RL) methods. The article is focused on improving model free RL method known as Q-Iearning algorit [...]