Tracking the trajectory of a swarm of mobile robots with a computer vision system
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Abstract
Swarm robotics research uses a range of tools for evaluating the behaviors and metrics of robot
collectives. One crucial tool involves the capability to track each robot’s position and orientation
at various intervals, enabling the reconstruction of individual robot poses and trajectories.
Comprehensive analysis of swarm behavior hinges on the study of the collective trajectories of
each robot within the group. This paper demonstrates the implementation of a computer vision
system, utilizing a webcam and Python scripts, to effectively track a mobile robot group within
a swarm. This shows the feasibility of developing such research tools using commonplace
computing equipment. The design and development of the vision system, including a detailed
calibration procedure, robot identification methods, and practical examples, are also shown.
Furthermore, it offers an exhaustive explanation of the robot tracking process. Experimental trials
with three robots validate the system’s ability to extract images from video feeds and accurately
identify each robot. Subsequently, after image processing, the system generates a dataset
encompassing image numbers, robot IDs, x and y positions, and orientations.
Article Details
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