Manifold-Based Sensorimotor Representations for Bootstrapping of Mobile Agents
by
Abstract:
Subject of this thesis is the development of a domain-independent algorithm that allows an autonomous system to process sequences of the sensorimotor interaction with its environment and to assign a geometric interpretation to its motor capabilities. We utilize Lie groups, smooth manifolds endowed with a group structure, that allow for an elegant representation of geometric operations as a central foundation for such a sensorimotor representation. Expressing motor controls with respect to the manifold structure allows us to transform the sensorimotor interaction sequence into a specific set of data points. Finding a manifold and a transformation that minimizes an intrinsic conflict function corresponds to finding a topological structure that is the best fit for expressing the sensorimotor space the entity resides in. Experiments in a virtual environment are conducted that show the applicability of the approach with respect to different sensor and motor configurations.
Reference:
Manifold-Based Sensorimotor Representations for Bootstrapping of Mobile Agents (Carsten Rachuy), PhD thesis, Cognitive Neuroinformatics, University of Bremen, 2020.
Bibtex Entry:
@phdthesis{rachuy2020thesis,
	author = {Carsten Rachuy},
	title = {Manifold-Based Sensorimotor Representations for Bootstrapping of Mobile Agents},
	year = {2020},
	abstract = {Subject of this thesis is the development of a domain-independent algorithm that allows an autonomous system to process sequences of the sensorimotor interaction with its environment and to assign a geometric interpretation to its motor capabilities. We utilize Lie groups, smooth manifolds endowed with a group structure, that allow for an elegant representation of geometric operations as a central foundation for such a sensorimotor representation. Expressing motor controls with respect to the manifold structure allows us to transform the sensorimotor interaction sequence into a specific set of data points. Finding a manifold and a transformation that minimizes an intrinsic conflict function corresponds to finding a topological structure that is the best fit for expressing the sensorimotor space the entity resides in. Experiments in a virtual environment are conducted that show the applicability of the approach with respect to different sensor and motor configurations.},
	doi = {10.26092/elib/24},
	url = {10.26092/elib/24">https://doi.org/10.26092/elib/24},
  school = {Cognitive Neuroinformatics, University of Bremen},
  address = {Bremen},
}