Automatic tracking and analysis of fish trajectories for developing a bio-inspired robot controller

Cloud Coppola; Lissa O'Reilly; Sarah Dalesman; Otar Akanyeti

doi:10.31256/Mb6Zo1T

Automatic tracking and analysis of fish trajectories for developing a bio-inspired robot controller

Cloud Coppola, Lissa O'Reilly, Sarah Dalesman, Otar Akanyeti

Research output: Chapter in Book/Report/Conference proceeding › Conference Proceeding (Non-Journal item)

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Abstract

Bio-inspired controllers may help robots better adapt to dynamic and unpredictable environments. In this paper, we present work in progress towards developing an automated tool for tracking and analysis of fish trajectories. These trajectories will be used to develop a bio-inspired robot controller through learning by demonstration paradigm.

Original language	English
Title of host publication	UKRAS22 Conference “Robotics for Unconstrained Environments” Proceedings
Publisher	UK-RAS Network
Pages	88-89
Number of pages	2
DOIs	https://doi.org/10.31256/Mb6Zo1T
Publication status	Published - 26 Aug 2022

Keywords

bio-inspired robot controller
deeplabcut
fish tracking
learning by demonstration

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10.31256/Mb6Zo1T

UK-RAS2022_proceedings_Paper-42Final published version, 526 KB

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title = "Automatic tracking and analysis of fish trajectories for developing a bio-inspired robot controller",

abstract = "Bio-inspired controllers may help robots better adapt to dynamic and unpredictable environments. In this paper, we present work in progress towards developing an automated tool for tracking and analysis of fish trajectories. These trajectories will be used to develop a bio-inspired robot controller through learning by demonstration paradigm.",

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author = "Cloud Coppola and Lissa O'Reilly and Sarah Dalesman and Otar Akanyeti",

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Automatic tracking and analysis of fish trajectories for developing a bio-inspired robot controller. / Coppola, Cloud ; O'Reilly, Lissa ; Dalesman, Sarah et al.
UKRAS22 Conference “Robotics for Unconstrained Environments” Proceedings. UK-RAS Network, 2022. p. 88-89.

Research output: Chapter in Book/Report/Conference proceeding › Conference Proceeding (Non-Journal item)

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KW - learning by demonstration

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Automatic tracking and analysis of fish trajectories for developing a bio-inspired robot controller

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Keywords

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