Realization of task intelligence for service robots in an unstructured environment

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In order to perform various tasks using a robot in a real environment, it is necessary to learn the tasks based on recognition, to be able to derive a task sequence suitable for the situation, and to be able to generate a behavior adaptively. To deal with this issue, this paper proposes a system for realizing task intelligence having a memory module motivated by human episodic memory, and a task planning module to resolve the current situation. In addition, this paper proposes a technique that can modify demonstrated trajectories according to current robot states and recognized target positions in order to perform the determined task sequence, as well as a technique that can generate the modified trajectory without collisions with surrounding obstacles. The effectiveness and applicability of the task intelligence are demonstrated through experiments with Mybot, a humanoid robot developed in the Robot Intelligence Technology Laboratory at KAIST.
Publisher
PERGAMON-ELSEVIER SCIENCE LTD
Issue Date
2017-10
Language
English
Article Type
Review
Keywords

PROBABILISTIC ROADMAPS

Citation

ANNUAL REVIEWS IN CONTROL, v.44, pp.9 - 18

ISSN
1367-5788
DOI
10.1016/j.arcontrol.2017.09.013
URI
http://hdl.handle.net/10203/237199
Appears in Collection
EE-Journal Papers(저널논문)
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