Visual sensing can be difficult to incorporate into undergraduate robotics and AI assignments. Images, after all, do not provide a direct estimate of the geometric conditions within the field of view. Yet vision is increasingly compelling as a part of undergraduate AI and robotics, given the centrality of pixels in our students' interactions with technology and each other. This paper shares a small-footprint framework designed to make visual sensing as easy to incorporate into AI projects and assignments, e.g., as a source of evidence for localization algorithms, as range sensors. The framework leverages (hand-built) circular panoramas and the image-matching capabilities provided by OpenCV's python library. An example localization project highlights its pedagogical accessibility and ease of deployment atop low-cost hardware and alongside other sensors.
CITATION STYLE
Zhang, A., Lee, J., Jones, C., & Dodds, Z. (2017). An image wherever you look! making vision just another sensor for AI/robotics projects. In 31st AAAI Conference on Artificial Intelligence, AAAI 2017 (pp. 4806–4811). AAAI press. https://doi.org/10.1609/aaai.v31i1.10551
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