14 research outputs found

    Robotized underwater interventions

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    Working in underwater environments poses many challenges for robotic systems. One of them is the low bandwidth and high latency of underwater acoustic communications, which limits the possibility of interaction with submerged robots. One solution is to have a tether cable to enable high speed and low latency communications, but that requires a support vessel and increases costs. For that reason, autonomous underwater robots are a very interesting solution. Several research projects have demonstrated autonomy capabilities of Underwater Vehicle Manipulator Systems (UVMS) in performing basic manipulation tasks, and, moving a step further, this chapter will present a unifying architecture for the control of an UVMS, comprehensive of all the control objectives that an UVMS should take into account, their different priorities and the typical mission phases that an UVMS has to tackle. The proposed strategy is supported both by a complete simulated execution of a test-case mission and experimental results

    Flexible human-robot cooperation models for assisted shop-floor tasks

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    The Industry 4.0 paradigm emphasizes the crucial benefits that collaborative robots, i.e., robots able to work alongside and together with humans, could bring to the whole production process. In this context, an enabling technology yet unreached is the design of flexible robots able to deal at all levels with humans' intrinsic variability, which is not only a necessary element for a comfortable working experience for the person but also a precious capability for efficiently dealing with unexpected events. In this paper, a sensing, representation, planning and control architecture for flexible human-robot cooperation, referred to as FlexHRC, is proposed. FlexHRC relies on wearable sensors for human action recognition, AND/OR graphs for the representation of and reasoning upon cooperation models, and a Task Priority framework to decouple action planning from robot motion planning and control.Comment: Submitted to Mechatronics (Elsevier

    Autonomous Underwater Intervention: Experimental Results of the MARIS Project

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    open11noopenSimetti, E. ;Wanderlingh, F. ;Torelli, S. ;Bibuli, M. ;Odetti, A. ;Bruzzone, G. ; Lodi Rizzini, D. ;Aleotti, J. ;Palli, G. ;Moriello, L. ;Scarcia, U.Simetti, E.; Wanderlingh, F.; Torelli, S.; Bibuli, M.; Odetti, Angelo; Bruzzone, G.; Lodi Rizzini, D.; Aleotti, J.; Palli, G.; Moriello, L.; Scarcia, U

    Underwater intervention robotics: An outline of the Italian national project Maris

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    The Italian national project MARIS (Marine Robotics for Interventions) pursues the strategic objective of studying, developing, and integrating technologies and methodologies to enable the development of autonomous underwater robotic systems employable for intervention activities. These activities are becoming progressively more typical for the underwater offshore industry, for search-and-rescue operations, and for underwater scientific missions. Within such an ambitious objective, the project consortium also intends to demonstrate the achievable operational capabilities at a proof-of-concept level by integrating the results with prototype experimental systems

    Flexible human\u2013robot cooperation models for assisted shop-floor tasks

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    The Industry 4.0 paradigm emphasizes the crucial benefits that collaborative robots, i.e., robots able to work alongside and together with humans, could bring to the whole production process. In this context, a yet unreached enabling technology is the design of robots able to deal at all levels with humans\u2019 intrinsic variability, which is not only a necessary element to a comfortable working experience for humans, but also a precious capability for efficiently dealing with unexpected events. In this paper, a sensing, representation, planning and control architecture for flexible human\u2013robot cooperation, referred to as FlexHRC, is proposed. FlexHRC relies on wearable sensors for human action recognition, AND/OR graphs for the representation of and the reasoning upon human\u2013robot cooperation models online, and a Task Priority framework to decouple action planning from robot motion planning and control
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