Robotics and Cognitive Approaches to Spatial Mapping

Simultaneous Localization and Mapping

Cognitive Approach to Robot Spatial Mapping

One of the major issues in Robotics or more precisely in Intelligent Systems in current research and innovation is self awareness. The world of innovation in Robotics has been developing autonomous robots with the ability to reason, learn and accomplish basic tasks. Self mapping is one of these abilities and it is very crucial to any physical agent that claims to be aware of its environment. To...

Modelling Models of Robot Navigation Using Formal Spatial Ontology

In this paper we apply a formal ontological framework in order to deconstruct two prominent approaches to navigation from cognitive robotics, the Spatial Semantic Hierarchy of Kuipers and the Route Graph of Krieg-Brückner, Werner and others. The ontological framework is based on our current work on ontology specification, where we are investigating Masolo et al.’s Descriptive Ontology for Lingu...

Towards a Generalization of Self-localization

Self-localization is an important task for humans and autonomous robots as it is the basis for orientation and navigation in a spatial environment and for performing mapping tasks. In robotics, self-localization on the basis of monomodal perceptual information has been investigated intensively. The present chapter looks at self-localization in a more general setting where the reference informat...

Towards real-world capable spatial memory in the LIDA cognitive architecture

The ability to represent and utilize spatial information relevant to their goals is vital for intelligent agents. Doing so in the real world presents significant challenges, which have so far mostly been addressed by robotics approaches neglecting cognitive plausibility; whereas existing cognitive models mostly implement spatial abilities in simplistic environments, neglecting uncertainty and c...