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Operations Research, Systems Engineering and Industrial Engineering Commons

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Departmental Papers (ESE)

Controls and Control Theory

Configuration spaces

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Full-Text Articles in Operations Research, Systems Engineering and Industrial Engineering

Clustering-Based Robot Navigation And Control, Omur Arslan Aug 2016

Clustering-Based Robot Navigation And Control, Omur Arslan

Departmental Papers (ESE)

In robotics, it is essential to model and understand the topologies of configuration spaces in order to design provably correct motion planners. The common practice in motion planning for modelling configuration spaces requires either a global, explicit representation of a configuration space in terms of standard geometric and topological models, or an asymptotically dense collection of sample configurations connected by simple paths, capturing the connectivity of the underlying space. This dissertation introduces the use of clustering for closing the gap between these two complementary approaches. Traditionally an unsupervised learning method, clustering offers automated tools to discover hidden intrinsic structures in ...


Clustering-Based Robot Navigation And Control, Omur Arslan, Dan P. Guralnik, Daniel E. Koditschek May 2016

Clustering-Based Robot Navigation And Control, Omur Arslan, Dan P. Guralnik, Daniel E. Koditschek

Departmental Papers (ESE)

In robotics, it is essential to model and understand the topologies of configuration spaces in order to design provably correct motion planners. The common practice in motion planning for modelling configuration spaces requires either a global, explicit representation of a configuration space in terms of standard geometric and topological models, or an asymptotically dense collection of sample configurations connected by simple paths. In this short note, we present an overview of our recent results that utilize clustering for closing the gap between these two complementary approaches. Traditionally an unsupervised learning method, clustering offers automated tools to discover hidden intrinsic structures ...