3,074 research outputs found

    Human-robot collaborative assembly in cyber-physical production: Classification framework and implementation

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    The production industry is moving towards the next generation of assembly, which is conducted based on safe and reliable robots working in the same workplace alongside with humans. Focusing on assembly tasks, this paper presents a review of human-robot collaboration research and its classification works. Aside from defining key terms and relations, the paper also proposes means of describing human-robot collaboration that can be relied on during detailed elaboration of solutions. A human-robot collaborative assembly system is developed with a novel and comprehensive structure, and a case study is presented to validate the proposed framework. © 2017

    Symbiotic Navigation in Multi-Robot Systems with Remote Obstacle Knowledge Sharing

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    Large scale operational areas often require multiple service robots for coverage and task parallelism. In such scenarios, each robot keeps its individual map of the environment and serves specific areas of the map at different times. We propose a knowledge sharing mechanism for multiple robots in which one robot can inform other robots about the changes in map, like path blockage, or new static obstacles, encountered at specific areas of the map. This symbiotic information sharing allows the robots to update remote areas of the map without having to explicitly navigate those areas, and plan efficient paths. A node representation of paths is presented for seamless sharing of blocked path information. The transience of obstacles is modeled to track obstacles which might have been removed. A lazy information update scheme is presented in which only relevant information affecting the current task is updated for efficiency. The advantages of the proposed method for path planning are discussed against traditional method with experimental results in both simulation and real environments

    Social Cognition for Human-Robot Symbiosis—Challenges and Building Blocks

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    The next generation of robot companions or robot working partners will need to satisfy social requirements somehow similar to the famous laws of robotics envisaged by Isaac Asimov time ago (Asimov, 1942). The necessary technology has almost reached the required level, including sensors and actuators, but the cognitive organization is still in its infancy and is only partially supported by the current understanding of brain cognitive processes. The brain of symbiotic robots will certainly not be a “positronic” replica of the human brain: probably, the greatest part of it will be a set of interacting computational processes running in the cloud. In this article, we review the challenges that must be met in the design of a set of interacting computational processes as building blocks of a cognitive architecture that may give symbiotic capabilities to collaborative robots of the next decades: (1) an animated body-schema; (2) an imitation machinery; (3) a motor intentions machinery; (4) a set of physical interaction mechanisms; and (5) a shared memory system for incremental symbiotic development. We would like to stress that our approach is totally un-hierarchical: the five building blocks of the shared cognitive architecture are fully bi-directionally connected. For example, imitation and intentional processes require the “services” of the animated body schema which, on the other hand, can run its simulations if appropriately prompted by imitation and/or intention, with or without physical interaction. Successful experiences can leave a trace in the shared memory system and chunks of memory fragment may compete to participate to novel cooperative actions. And so on and so forth. At the heart of the system is lifelong training and learning but, different from the conventional learning paradigms in neural networks, where learning is somehow passively imposed by an external agent, in symbiotic robots there is an element of free choice of what is worth learning, driven by the interaction between the robot and the human partner. The proposed set of building blocks is certainly a rough approximation of what is needed by symbiotic robots but we believe it is a useful starting point for building a computational framework

    Knowledge Representation for Robots through Human-Robot Interaction

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    The representation of the knowledge needed by a robot to perform complex tasks is restricted by the limitations of perception. One possible way of overcoming this situation and designing "knowledgeable" robots is to rely on the interaction with the user. We propose a multi-modal interaction framework that allows to effectively acquire knowledge about the environment where the robot operates. In particular, in this paper we present a rich representation framework that can be automatically built from the metric map annotated with the indications provided by the user. Such a representation, allows then the robot to ground complex referential expressions for motion commands and to devise topological navigation plans to achieve the target locations.Comment: Knowledge Representation and Reasoning in Robotics Workshop at ICLP 201

    RAF | A framework for symbiotic agencies in robotic – aided fabrication

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    The research presented in this paper utilizes industrial robotic arms and new material technologies to model and explore a different conceptual framework for ‘robotic-aided fabrication’ based on material formation processes, collaboration, and feedback loops. Robotic-aided fabrication as a performative design process needs to develop and demonstrate itself through projects that operate at a discrete level, emphasizing the role of the different agents and prioritizing their relationships over their autonomy. It encourages a process where the robot, human and material are not simply operational entities but a related whole. In the pre-actual state of this agenda, the definition and understanding of agencies and the inventory of their relations is more relevant than their implementation. Three test scenarios are described using human designers, phase-changing materials, and a six-axis industrial robotic arm with an external sensor. The common thread running through the three scenarios is the facilitation of interaction within a digital fabrication process. The process starts with a description of the different agencies and their potentiality before any relation is formed. Once the contributions of each agent are understood they start to form relations with different degrees of autonomy. A feedback loop is introduced to create negotiation opportunities that can result in a rich and complex design process. The paper concludes with speculation on the advantages and possible limitations of semi-organic design methods through the emergence of patterns of interaction between the material, machine and designer resulting in new vistas towards how design is conceived, developed, and realised

    A human-oriented design process for collaborative robotics

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    The potential of collaborative robotics often does not materialize in an efficient design of the human-robot collaboration. Technology-oriented approaches are no longer enough in the Industry 4.0 era. This work proposes a set of methods to support manufacturing engineers in the human-oriented design process of integrated production systems to obtain satisfactory performance in the mass customization paradigm, without impacting the safety and health of workers. It founds the design criteria definition on five main pillars (safety, ergonomics, effectiveness, flexibility, and costs), favors the consideration of different design alternatives, and leads their selection. The dynamic impact of the design choices on the various elements of the system prevails over the static design constraints. The method has been experimented in collaboration with the major kitchen manufacturer in Italy, which introduced a collaborative robotics cell in the drawers' assembly line. It resulted in a more balanced production line (10% more), a verified risk minimization (RULA score reduced from 5 to 3 and OCRA score from 13.30 to 5.70), and a greater allocation of operators to high added value activities
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