As Co-Director of the iCORE lab, I am leading the Robotic Kinematics and Dynamics (RKindD) group. Our group is focused on developing robotic systems that are able to operate in complex and unstructured environments, focusing on topics such as: Control Theory, Motion Planning, Dynamic Modeling and Visual Robotic Control and Navigation.
Complete publications can be found on google scholar here.
Marine robotics has become an important research topic, with applications ranging from subsea oil and gas, construction, military and archaeological intervention, to deep sea specimen collection. Over the years, my group has focused on better understanding the behavior of marine robots, with an emphasis on underwater manipulators and autonomous underwater vehicles (AUVs).
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The goal of this project is to develop motion planning algorithms for shipwreck surveys to enable data gathering in the proximity of the archaeological sites. The main challenge to address during this work is to ensure the robotic system will successfully gather the necessary data by having complete coverage of the area without risking damage to the site.
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Autonomous underwater robots are significantly hindered by the underwater poor visibility conditions, decreasing their ability to closely perceive the environment. Nevertheless, optical cameras are one of the most cost effective perception sensors sensors that can contribute towards better navigation capabilities for autonomous underwater systems.
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Large-scale manufacturing is common practice in several industries: transportation, maritime, energy, aerospace and construction. Finishing operations, such as trimming, sanding and painting, are necessary to guarantee tolerances and required properties are met. For humans, those tasks are stressful, and may lead to physical discomfort and potential for repetitive strain injury.
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Automation by means of robotics for additive manufacturing (AM) technologies offers greater freedom of movement compared with conventional gantry designs, larger print volumes by virtue of mobility around the printing space on wheels or rails, and reduced human supervision and interaction. This project is focused on enabling robotic manipulators with 3D printing capabilities to advance the area of robotic-driven AM.
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