Call for papers (apologies for multiple posting)
==================================================================== Workshop Title Towards the factory of the future: advancements in planning and control of industrial robots Organized and Co-chaired by Marco Faroni, National Research Council of Italy, CNR-STIIMA Alessandro Umbrico, National Research Council of Italy, CNR-ISTC Manuel Beschi, University of Brescia https://2021.ieee-etfa.org/solicited-workshops/ws1-towards-the-factory-of-the-future-advancements-in-planning-and-control-of-industrial-robots/ <https://2021.ieee-etfa.org/solicited-workshops/ws1-towards-the-factory-of-the-future-advancements-in-planning-and-control-of-industrial-robots/> The workshop will be held during the 26th International Conference on Emerging Technologies and Factory Automation (ETFA 2021 - https://2021.ieee-etfa.org/ <https://2021.ieee-etfa.org/>) Important Dates Submission deadline: June 11th **** Submission deadline: June 18th ***** Acceptance notification: July 7th Deadline for final manuscripts: July 14th ==================================================================== Aims and Objectives *********** Industrial robots play a key role in industrial automation. Robotic arms populate shop-floors: they are used for pick-and-place, assembly, inspection, and many other tasks, to increase the throughput of productive processes and alleviate fatigue and risks of human workers. A huge research effort has been put into the reasoning, planning, and control of robotic manipulators. Nonetheless, industrial implementations often do not exploit at full the great advancements made in these fields. This workshop aims to discuss how recent developments in the planning and control of robot manipulators, on the one hand, and the synergetic integration with results from Artificial Intelligence, on the other, can advance the state of the art and be applied to real-world manufacturing processes. Among the many challenges in the field, the workshop will focus on the following trends that emerged in recent years: Human-robot collaboration: collaborative robots are expected to play a key role in the factories of the future. The collaboration between humans and robots is supposed to combine the dexterity and reasoning ability of humans with the precision and continuity of robots. Current industrial solutions often lack smoothness and collaboration results to be discontinuous. This occurs at different decision-making levels. For example, implementations of safety rules according to safety standards (e.g., ISO-TS 15066) stop the robot as soon as human workers enter the robot workspace. Moreover, robot trajectories are often pre-computed and do not adapt to the system changes. Finally, ordering, scheduling, and assignment of tasks do not model human behaviors and preferences, resulting in poor dependability and jeopardizing the overall collaboration experience. Recent advances in task and motion planning addressed this issue in many several ways. Innovative methods have been developed to improve safety, ergonomics, and the efficiency of the process. Nonetheless, a well-established common paradigm is still to come. Cognitive manufacturing: a central aspect concerning the integration of AI and Robotics in modern manufacturing scenarios is the enhancement of perception and reasoning capabilities of robotic solutions. AI technologies can indeed help to endow robot controllers with the necessary cognitive capabilities to “understand” the state of human operators and the environment as well as contextualize robot behaviors accordingly. A collaborative robot would, for example, dynamically adapt its behaviors to known skills and monitored physiological state of human workers (e.g., ergonomics, cognitive load, fatigue, etc.) in order to achieve a smooth and natural interaction. Such higher level of cognition is crucial to systematically include human-factors in the loop and really enable symbiotic, personalized and adaptive interactions between humans and robots. Flexible manipulation in challenging scenarios: pick-and-place, sorting, and packaging can be efficiently automatized when they are required to manipulate objects with low variability (similar sizes and shapes) and they are performed in structured environments. However, when it comes to partially structured environments or high-variability, current industrial solutions usually fail because of a lack of flexibility and efficiency. Similarly, manipulation of large and/or deformable objects is still a hard task to perform with robotic manipulators. Examples are those draping processes required in automotive and aerospace (carbon-fiber manipulation) and in the textile industry. Despite these topics have been addressed for a long time by researchers, real-world implementations and successful case studies are rare and only recent research projects are trying to effectively automatize these processes. These new solutions should integrate vision, learning, and planning. We invite researchers from both industry and academia to contribute to this workshop with papers on their recent advances in these fields, focusing on both theoretical methodology and industrial case studies. Acknowledgement *********** This workshop is partially supported by the EU funded project Sharework (H2020 Factories of the Future GA No. 820807) - https://sharework-project.eu <https://sharework-project.eu/>. Topics of interest (but not limited to) *********** Applicants are expected to be conducting research in the field of planning and control of Industrial robots. Topics of interest include (but are not limited to): Human-aware planning and execution in human-robot collaboration Motion planning and control in dynamic environments Long-term autonomy in human-robot collaborative scenarios Manipulation of deformable/large objects Combined task and motion planning Multi-robot coordination and synchronization Design and optimization of robotized workcells Human-centered design of robotized cells Safety and ergonomics of physical human-robot collaboration Failure detection and recovery in HRC control systems Evaluation methods for HRC workplaces and process (productivity, flexibility, etc.) Vision and control of industrial robots for HRI applications Novel Sensing and grasping technologies for HRI Interfaces for real-time path and motion planning and collision avoidance Case studies, experiments, ethics and outreach Submissions *********** Papers are limited to 8 double column pages. They must comply with ETFA guidelines regarding formatting (https://www.ieee.org/conferences/publishing/templates.html <https://www.ieee.org/conferences/publishing/templates.html>) and must be submitted electronically in PDF format through the conference submission system: http://submit.ieee-ies.org/submit/etfa21/ <http://submit.ieee-ies.org/submit/etfa21/> Accepted papers must be presented at the workshop in order to be included in the ETFA conference proceedings and will be published on IEEE Xplore. Organisation Chairs ******************* Marco Faroni Institute of Intelligent Industrial Technologies and Systems for Advanced Manufacturing (STIIMA) National Research Council (CNR), Italy Alessandro Umbrico Institute for Cognitive Sciencre and Technologies (ISTC) National Research Council (CNR), Italy Manuel Beschi Department of Industrial and Mechanical Engineering University of Brescia, Italy Program Committee ****************** Cosmin Copot, University of Antwerp, Belgium Martina Lippi, University of ROMA TRE, Italy Sotiris Makris, LMS, University of Patras, Greece Andrea Orlandini, National Research Council of Italy (CNR-ISTC), Italy Simone Pasinetti, University of Brescia, Italy Nicola Pedrocchi, National Research Council of Italy (CNR-STIIMA), Italy José Saenz, Fraunhofer IFF, Germany Alberto Tellaeche, University of Deusto, Spain — --------------------------------------------------------------------------------- Dr. Alessandro Umbrico, PhD National Research Council of Italy Institute for Cognitive Science and Technology E-mail: alessandro.umbr...@istc.cnr.it WebSite: http://www.istc.cnr.it/people/alessandro-umbrico Linkedin: http://it.linkedin.com/in/alessandroumbrico/ --------------------------------------------------------------------------------- —
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