A major challenge in deploying robots into the real world is the design of an architectural framework which can provide extended, natural and effective interactions with people. Within this framework, key issues that need to be solved relate to the…

In this paper we present a scalable machine learning approach to mobile robots visual localization. The applicability of machine learning approaches is constrained by the complexity and size of the problem’s domain. Thus, dividing the problem becomes necessary and two…

Self-organising neural models have the ability to provide a good representation of the input space. In particular the Growing Neural Gas (GNG) is a suitable model because of its flexibility, rapid adaptation and excellent quality of representation. However, this type…

In this paper we present an approach for the control of autonomous robots, based on Automated Planning (AP) techniques, where a control architecture was developed (ROPEM: RObot Plan Execution with Monitoring). The proposed architecture is composed of a set of…