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LEAD RESEARCHER: ALESSANDRO ALTOBELLI I received the B.S degree in Information Engineering in 2009 from University of Perugia, the M.S degree in Automation Engineering from University of Pisa in 2011 and the PhD in Automatics, Robotics and Bioengineering from University of Pisa in 2015. I carried out my research activity at the Advanced Robotics Department of Italian Institute of Technology, from 2012 to 2015. From 2016 to 2017 I worked as software engineer in R&D group at Infinity Technology Solutions. From 2018 to 2020 I worked as research engineer at RACE (part of UKAEA) in the RAIN Hub. I am now working as a senior post doc at Italian Institute of Technology. I have a strong interest in haptics, robotics and teleoperation. OPTIMAL ROBOTIC GRASPING 56 SUMMARY // In the last few decades, several approaches have been presented to accomplish tasks with robots or autonomous systems in a glovebox; nevertheless, in nuclear facilities, risky operations are still executed by humans that guarantee a high manipulation capability and dexterity. Inside the gloveboxes, robotic devices have to operate in cluttered environments, or environments with limited space for movement; therefore, it is of significant interest to identify grasping poses that are feasible within such constrained environments. The outcomes of this research present and experimentally evaluate a strategy to synthesise optimal grasps considering geometric primitives for a manipulation system in a constrained environment. The novel strategy has been experimentally evaluated in a cluttered environment (via a glovebox mock-up) with realistic objects, and the efficacy of the proposed grasping algorithm has been described. Integration, teleoperation and virtual reality aspects were investigated as secondary topics in order to contribute on the development of the RAIN teleoperation setup.

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