Anna Grosso
Vision and inertial data fusion for collaborative robotics.
Rel. Marcello Chiaberge, Sarah Cosentino. Politecnico di Torino, Corso di laurea magistrale in Mechatronic Engineering (Ingegneria Meccatronica), 2020
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Abstract
Robots capable of engaging in collaborative behaviours with humans, widely known as cobots, are characterized by incredibly complex requirements and are one of today's major challenges in the robotics field. In order to meet the rather strict accuracy requirements needed to ensure human safety and to gather context information useful for intelligent human-robot collaboration, these robots must adequately localize human operators who move freely in the robotic workplaces. In today’s industrial environments, this objective can be achieved by adopting sophisticated sensory devices like lasers, ultrasounds or vision systems. However, human tracking can be particularly difficult in presence of occluding factors that could severely affect vision-based or light-based approaches and in unconstrained conditions like crowded spaces.
This thesis analyzes the integration of inertial measurement units and a vision system in order to improve the human localization for collaborative robotics purposes
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