Natural terrain is rarely flat. Substrate irregularities challenge walking animals to maintain stability, yet we lack quantitative assessments of walking performance and limb kinematics on naturally uneven ground. We measured how continually uneven 3D-printed substrates influence walking performance of Argentine ants by measuring walking speeds of workers from lab colonies and by testing colony-wide substrate preference in field experiments. Tracking limb motion in over 8,000 videos, we used statistical models that associate walking speed with limb kinematic parameters to compare movement over flat versus uneven ground of controlled dimensions. We found that uneven substrates reduced preferred and peak walking speeds by up to 42% and that ants actively avoided uneven terrain in the field. Observed speed reductions were modulated primarily by shifts in stride frequency instead of stride length (flat R²: 0.91 vs. 0.50), a pattern consistent across flat and uneven substrates. Mixed-effect modeling revealed that walking speeds on uneven substrates were accurately predicted based on flat walking data for over 89% of strides. Those strides that were not well modeled primarily involved limb perturbations, including missteps, active foot repositioning, and slipping. Together these findings relate kinematic mechanisms underlying walking performance on uneven terrain to ecologically-relevant measures under field conditions.

All files are saved as .pickle and can be read into python using the pandas package and function pandas.read_pickle

All distance variables are in pixels. 31.992 pixels per mm

Data was tracked from videos filmed at 240 fps

 

GENERAL INFO FOR EACH TRACKWAY

'ID' - identifier for the ant (number of trackway found in given video)
'colony' - date of the colony collected
'date' - date of recording
'datetime' - date and time of recording
'substrate' - what substrate 0 = flat, 1/3/5 = checkerboards of mm dimension
'time' - time of recording
'video' - full path of video associated with trackway

 

 

FULL BODY TRACKING AND ASSOCIATING OUTPUT

'x_kal' - raw x-position output of body centroid from OpenCV contour fit, associated across frames using kalman filter
'y_kal' - raw y-position output of body centroid from OpenCV contour fit, associated across frames using kalman filter
'angle' - raw angle of body from OpenCV contour fit, associated across frames using kalman filter, +y axis = 0 radians
'frames' - frames associated with x_kal, y_kal, x_raw, y_raw, angle, and all LEAP output
'area' - area of the tracked contour from OpenCV contour fit
'xy_cov_matrix' - output from kalman filter associating across frames
'error' - norm of covariance output from kalman filter associating across frames
'measurements' - xhat, P, and K measurements from kalman filter associating across frames
'LA' - previous version of tracking left antennal tip, should be empty
'RA' - previous version of tracking right antennal tip, should be empty

 

 

POST-PROCESSING OUTPUT

'x_raw' - lowpass butterworth filtered x_kal
'y_raw' - lowpass butterworth filtered y_kal
'vfilt' - instantaneous speed of ant using x_raw, y_raw
'vxfilt' - instantaneous speed of ant in x-axis using x_raw
'vyfilt' - instantaneous speed of ant in y-axis using y_raw
'movave_v' - moving average of vfilt across 24 frames = 0.1 s
'movave_fr' - frames associated with movave_v

'dist_90fr' - moving calculation of distance traveled over 90 frames = 375 ms
'x' - removed x_raw data where ant is close to frame edge and when ant is stopped/moving slowly
'y' - removed y_raw data where ant is close to frame edge and when ant is stopped/moving slowly
'v' - instantaneous speed of ant using x, y
'vx' - instantaneous speed of ant in x-axis using x
'vy' - instantaneous speed of ant in y-axis using y
'median_v' - median velocity of 'v'
'median_vx' - median velocity of 'vx'
'median_vy' - median velocity of 'vy'
'sinuosity' - sinuosity calculation of trackway using x, y

'angle_improved' - raw OpenCV contour angle output does not factor in facing. this uses antennae and comparisons across a tracked trailway to correct the angle to be the ant facing. it is then interpolated and smoothed
'frames_final' - frame number associated with x, y

 

 

LEAP TRACKING OUTPUT

 'thorax_conf' - body center confidence
 'thorax_x' - body center x position
 'thorax_y' - body center y position

 'neck_conf' - neck confidence
 'neck_x' - neck x position
 'neck_y' - neck y position

 'antenna0_conf' - left antenna confidence 
 'antenna0_x' - left antenna tip x-position
 'antenna0_y' - left antenna tip y-position
 'antenna1_conf' - right antenna confidence
 'antenna1_x' - right antenna tip x-position
 'antenna1_y' - right antenna tip y-position

 'joint0_conf' - left hindlimb
 'joint0_x',
 'joint0_y',
 'joint1_conf' - left midlimb
 'joint1_x',
 'joint1_y',
 'joint2_conf' - left forelimb
 'joint2_x',
 'joint2_y',
 'joint3_conf' - right hindlimb
 'joint3_x',
 'joint3_y',
 'joint4_conf' - right midlimb
 'joint4_x',
 'joint4_y',
 'joint5_conf' - right forelimb
 'joint5_x',
 'joint5_y',