Kinematic data and mathematical modeling of sea star locomotion
Cite this dataset
McHenry, Matthew; Po, Theodora; Kanso, Eva (2023). Kinematic data and mathematical modeling of sea star locomotion [Dataset]. Dryad. https://doi.org/10.5061/dryad.hqbzkh1p3
Abstract
It is unclear how animals with radial symmetry control locomotion without a brain. Using a combination of experiments, mathematical modeling, and robotics, we tested the extent to which this control emerges in sea stars from the local control of their hundreds of feet and their mechanical interactions with the body. We discovered that these animals (Protoreaster nodosus) compensate for an experimental increase in their submerged weight by recruiting more feet that synchronize in the power stroke of the locomotor cycle. Mathematical modeling replicated this response to loading in the absence of nervous communication and demonstrated how the body weight serves as a regulator of recruitment. We built a robotic sea star with an array of independently-controlled actuators that were also recruited in greater numbers under higher loads due to their collective mechanics. These findings demonstrate that an array of actuators in biological and robotic systems are capable of cooperative transport with dynamic adjustments to loading. This form of distributed control contrasts the conventional view of animal locomotion as governed by the central nervous system and offers inspiration for the design of engineered devices with arrays of actuators.
README: Kinematic data and mathematical modeling of sea star locomotion
https://doi.org/10.5061/dryad.hqbzkh1p3
MATLAB data and code for kinematic analysis and mathematical modeling.
Here is a catalog of individual items in the repository:
1D model
Matlab code for performing simulations of a one-dimensional mathematical model. The file spring.m performs the numerical simulation and the remaining functions allow for plotting and analyzing the results.
2D model
Matlab code for performing simulations of the 2D model of the mechanics of a sea star. The spring.m function performs an individual simulation and runBatch.m runs that function in the variety of ways detailed in the manuscript. The remaining functions allow for analyzing and visualizing the results.
Animal_kinematics_code
Includes Matlab code for acquiring and analyzing kinematics. Specifically, we used DeepLabCut to collect kinematics of locomotion of sea stars from a side view. Automated tracking in matlab was used to measure whole-body motion using thresholding. The manual tracking was performed in matlab to measure the motion of individual tube feet.
Animal_kinematics_data
Includes the data files for side-view kinematics (acquired with DeepLabCut) and the individual foot tracking. The results of all experiments are summarized in Weights_experiments.xlsx. Inappropriate or unnecessary values entered as "null".
The tube-foot kinematics are stored within the 'F' structure, save in 'footData.mat', with units of meters and seconds. The 'ftL' field in the 'F' structure stores the kinematics with respect to the stroke plane of the power stroke of each foot.
All coordinates contained within 'side-view data' are in pixels, with the spatial calibration constant for each in Weights_experiments.xlsx.
Robotics_experiments.xlsx
Includes all measurements for the robotics experiments. A lack of notes recorded as "null".
Methods
The dataset includes code necessary to acquire and analyze the kinematics of sea -star locomotion. The ressulting data files are included. In addition, we have included the code to mathematically model the mechanics of sea-star locomotion.
Funding
National Science Foundation, Award: 2034043, IOS