Spatial Representation for Navigation in Animats

Prescott, Tony J.

doi:10.1177/105971239600400201

Cited by 49 publications

(42 citation statements)

References 42 publications

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“…A neural network theory for storing the required information in the form of a labeled graph has been presented by Schölkopf and Mallot (1995). For related approaches including hippocampal modeling, see Muller, Stead, and Pach (1996), Prescott (1996) and Touretzky and Redish (1996).…”

Section: Routes and Con Gurationsmentioning

confidence: 99%

Navigation and Acquisition of Spatial Knowledge in a Virtual Maze

Gillner

Mallot

1998

Journal of Cognitive Neuroscience

254

161

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Spatial behavior in humans and animals includes a wide variety of behavioral competences and makes use of a large number of sensory cues. Here we studied the ability of human subjects to search locations, to nd shortcuts and novel paths, to estimate distances between remembered places, and to draw sketch maps of the explored environment; these competences are related to goal-independent memory of space, or cognitive maps. Information on spatial relations was restricted to two types: a visual motion sequence generated by simulated movements in a virtual maze and the subject's own movement decisions de ning the path through the maze. Visual information was local (i.e., no global landmarks or compass information was provided). Other position and movement information (vestibular or proprioceptive) was excluded. The amount of visual information provided was varied over four experimental conditions. The results indicate that human subjects are able to learn a virtual maze from sequences of local views and movements. The information acquired is local, consisting of recognized positions and movement decisions associated to them. Although simple associations of this type can be shown to be present in some subjects, more complete con gurational knowledge is acquired as well. The results are discussed in a view-based framework of navigation and the representation of spatial knowledge by means of a view graph.

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Section: Routes and Con Gurationsmentioning

confidence: 99%

Navigation and Acquisition of Spatial Knowledge in a Virtual Maze

Gillner

Mallot

1998

Journal of Cognitive Neuroscience

254

161

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“…Landmarks play a prominent role in many approaches to robot navigation, for example in the work by Lazanas and Latombe [2] or Prescott [5], who describes relations between landmarks. While these approaches use metrical information, there exist quite a few qualitative approaches to landmark based navigation.…”

Section: Related Workmentioning

confidence: 99%

Representing and Selecting Landmarks in Autonomous Learning of Robot Navigation

Frommberger

2008

Intelligent Robotics and Applications

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Abstract. Navigation based on detected landmarks is an important facet of robot navigation. This work investigates into a qualitative representation of landmarks for an autonomous learning task where a robot learns a goal directed navigation strategy with reinforcement learning. We discuss how to build a suitable landmark-based representation. In particular, we focus on selection of landmarks to regard when experiencing a multitude of landmarks, because representing all of them would blow up the state space inappropriately. Thus, we examine strategies for this selection. Furthermore, we introduce a background knowledge based structure-aware landmark selection mechanism to limit landmark observation to the cases where it is really needed.

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“…Local navigation methods have also been called "tactics" [82] or local control strategies [33]. Way-finding involves the recognition of several places, and the representation of relations between places which may be outside the current range of perception [59]. Way-finding relies on local navigation skills to move from one place to another, but it allows the agent to find places that could not be found by local navigation alone.…”

Section: "Navigation Is the Process Of Determining And Maintaining A mentioning

confidence: 99%

Biomimetic robot navigation

Franz

Mallot

2000

Robotics and Autonomous Systems

256

164

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In the past decade, a large number of robots has been built that explicitly implement biological navigation behaviours. We review these biomimetic approaches using a framework that allows for a common description of biological and technical navigation behaviour. The review shows that biomimetic systems make significant contributions to two fields of research: First, they provide a real world test of models of biological navigation behaviour; second, they make new navigation mechanisms available for technical applications, most notably in the field of indoor robot navigation. While simpler insect navigation behaviours have been implemented quite successfully, the more complicated way-finding capabilities of vertebrates still pose a challenge to current systems.

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Spatial Representation for Navigation in Animats

Cited by 49 publications

References 42 publications

Navigation and Acquisition of Spatial Knowledge in a Virtual Maze

Navigation and Acquisition of Spatial Knowledge in a Virtual Maze

Representing and Selecting Landmarks in Autonomous Learning of Robot Navigation

Biomimetic robot navigation

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