A novel method for robust estimation of ants' walking speed and curvature on convoluted trajectories derived from their gait pattern

Accurate measurements of travel distance and speed are crucial for the analysis of animal movements. Measuring the movements of ants entails measuring the change in locations registered at time intervals. This process involves dilemma of setting the proper time window: a short time window is vulnerable to spatial errors in observation, while a long time window leads to underestimation of the travel distance. To overcome these difficulties, we propose a novel algorithm that successively interpolates two consecutive points of ants trajectory for a given time window by embracing the alternating tripod gait of ants. We demonstrate that this algorithm is more reliable compared to the conventional method of travel distance estimation based on the sum of the consecutive straight-line displacements (SLD). After obtaining speed estimates for a range of sampling time windows, we applied a fitting method that can estimate the actual speed without prior knowledge of spatial error distribution. We compared results from several methods of speed and curvature extracted from the empirical data of ant trajectories. We encourage empirical scientists to utilize the proposed methods rather than the conventional SLD method of speed estimation as this process is a more reliable and subjective selection of the sampling time window can be avoided.