Skip to main content
Dryad logo

Data from: Salmon behavioural response to robots in an aquaculture sea cage

Citation

Kruusmaa, Maarja et al. (2020), Data from: Salmon behavioural response to robots in an aquaculture sea cage, Dryad, Dataset, https://doi.org/10.5061/dryad.x0k6djhfs

Abstract

Animal-robot studies can inform us about animal behaviour and inspire advances in agriculture, environmental monitoring and animal health and welfare. Currently, experimental results on how fish are affected by the presence of underwater robots are largely limited to laboratory environments with few individuals and a focus on model species. Laboratory studies provide valuable insight, but their results are not necessarily generalizable to larger scales such as marine aquaculture. This paper examines the effects of underwater robots and a human diver in a large fish aggregation within a Norwegian aquaculture facility, with the explicit purpose to improve the use of underwater robots for fish observations.

We observed aquaculture salmon’s reaction to the flipper-propelled robot U-CAT in a sea cage with 188,000 individuals. A significant difference in fish behaviour was found using U-CAT when compared to a thruster-driven underwater robot, Argus Mini and a human diver. Specifically, salmon were more likely to swim closer to U-CAT at a lower tailbeat frequency. Fish reactions were not significantly different when considering motor noise or when U-CAT’s colour was changed from yellow to silver. No difference was observed in the distance or tailbeat frequency as a response to thruster or flipper motion, when actuated and passively floating robots were compared. 

These results offer insight into how large aggregations of aquaculture salmon respond to underwater robots. Furthermore, the proposed underwater video processing workflow to assess fish’s response to underwater robots is simple and reproducible. This work provides a practical method to study fish-robot interactions, which can lead to improved underwater robot designs to provide more affordable, scalable and effective solutions.
 

Methods

Please refer to the paper for data collection methods

Usage Notes

-------------------------------------------------------------------------------------
".mp4" files come from moving cameras from the robots or the diver. Naming of files: 
    "Xnn dd" (X:{A,B,C,D}, nn:{01-07}, dd:{28-31}) corresponds to day of experiments (May 28 - May 31, 2018) and ascending number of run during that day (e.g. "A04 28" corresponds to the fourth run on May 28, 2018.) 
    "ROV, U-CAT, diver": correspond to the robot/diver used for filming for a specific run.

The .kva (Kinovea) files are associated to the .mp4 video files (the file "File_index" shows how). In two instances more than one .kva files correspond to one .mp4 file. These files can be separately loaded in Kinovea. The .kva files can be used to export xml files from kinovea for further processing.

-------------------------------------------------------------------------------------

".asf" files with filenames starting with "Facility_Merd_" are from the stationary camera at the bottom of the cage. Date and time of the filming are encoded in the file name.

Files "fish_distance.csv" and "fish_swimming_speed.csv" contain data extracted from the stationary camera videos, observing the robots and diver.

Funding

Eesti Teadusagentuur, Award: IUT-339

Eesti Teadusagentuur, Award: PUT-1690

Norges Forskningsråd, Award: 223254-NTNU AMOS

Horizon 2020 Framework Programme, Award: 65283 Aquaexcel TNA