Abstract The Qualitative Rectilinear Projection Calculus (QRPC), a new representation
model based on planar trajectories, is presented in this work for describing qualitatively …

Reinforcement learning has developed as a successful learning approach for domains that
are not fully understood and that are too complex to be described in closed form. However …

The representation of the surrounding world plays an important role in robot navigation,
especially when reinforcement learning is applied. This work uses a qualitative abstraction …

When a robot learns to solve a goal-directed navigation task with reinforcement learning, the
acquired strategy can usually exclusively be applied to the task that has been learned …

This paper introduces a reinforcement learning (RL) based autonomous waypoint
generation strategy (AWGS), for on-line path planning in unknown environments. An RL …

Spatial abstraction empowers complex agent control processes. We propose a formal
definition of spatial abstraction and classify it by its three facets, namely aspectualization …

Diese Arbeit erforscht adaptive Algorithmen zur Steuerung von autonomen Roboter bei
denen sich koordiniertes Verhalten ohne konkrete Ziele oder Informationen über die …

This paper introduces a novel waypoints selection framework for autonomous navigation in
unknown and continuous environments, which may use a number of existing path planners …

Programming robots is a useful tedious task, so there is growing interest in building robots
which can learn by themselves. This paper describes the Reinforcement Learning and …

Humans excel at communicating to one another about the objects and spaces that inhabit
our lives. For example, communicating about rooms in a house or a lost pair of keys can be …