Humans as path-finders for mobile robots using teach-by-showing navigation

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Abstract

One of the most important barriers towards a widespread use of mobile robots in unstructured, human populated and possibly a-priori unknown work environments is the ability to plan a safe path. In this paper, we propose to delegate this activity to a human operator that walks in front of the robot marking with her/his footsteps the path to be followed. The implementation of this approach requires a high degree of robustness in locating the specific person to be followed (the path-finder). We propose a three phases approach to fulfil this goal: 1. Identification and tracking of the person in the image space, 2. Sensor fusion between camera data and laser sensors, 3. Point interpolation with continuous curvature paths. The approach is described in the paper and extensively validated with experimental results.

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Antonucci, A., Bevilacqua, P., Leonardi, S., Paolopoli, L., & Fontanelli, D. (2023). Humans as path-finders for mobile robots using teach-by-showing navigation. Autonomous Robots, 47(8), 1255–1273. https://doi.org/10.1007/s10514-023-10125-5

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