116 research outputs found

    Progress and Prospects of the Human-Robot Collaboration

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    International audienceRecent technological advances in hardware designof the robotic platforms enabled the implementationof various control modalities for improved interactions withhumans and unstructured environments. An important applicationarea for the integration of robots with such advancedinteraction capabilities is human-robot collaboration. Thisaspect represents high socio-economic impacts and maintainsthe sense of purpose of the involved people, as the robotsdo not completely replace the humans from the workprocess. The research community’s recent surge of interestin this area has been devoted to the implementation of variousmethodologies to achieve intuitive and seamless humanrobot-environment interactions by incorporating the collaborativepartners’ superior capabilities, e.g. human’s cognitiveand robot’s physical power generation capacity. In fact,the main purpose of this paper is to review the state-of-thearton intermediate human-robot interfaces (bi-directional),robot control modalities, system stability, benchmarking andrelevant use cases, and to extend views on the required futuredevelopments in the realm of human-robot collaboration

    Accelerating Surgical Robotics Research: A Review of 10 Years With the da Vinci Research Kit

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    Robotic-assisted surgery is now well-established in clinical practice and has become the gold standard clinical treatment option for several clinical indications. The field of robotic-assisted surgery is expected to grow substantially in the next decade with a range of new robotic devices emerging to address unmet clinical needs across different specialities. A vibrant surgical robotics research community is pivotal for conceptualizing such new systems as well as for developing and training the engineers and scientists to translate them into practice. The da Vinci Research Kit (dVRK), an academic and industry collaborative effort to re-purpose decommissioned da Vinci surgical systems (Intuitive Surgical Inc, CA, USA) as a research platform for surgical robotics research, has been a key initiative for addressing a barrier to entry for new research groups in surgical robotics. In this paper, we present an extensive review of the publications that have been facilitated by the dVRK over the past decade. We classify research efforts into different categories and outline some of the major challenges and needs for the robotics community to maintain this initiative and build upon it

    Automatic extraction of constraints in manipulation tasks for autonomy and interaction

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    Tasks routinely executed by humans involve sequences of actions performed with high dexterity and coordination. Fully specifying these actions such that a robot could replicate the task is often difficult. Furthermore the uncertainties introduced by the use of different tools or changing configurations demand the specification to be generic, while enhancing the important task aspects, i.e. the constraints. Therefore the first challenge of this thesis is inferring these constraints from repeated demonstrations. In addition humans explaining a task to another person rely on the person's ability to apprehend missing or implicit information. Therefore observations contain user-specific cues, alongside knowledge on performing the task. Thus our second challenge is correlating the task constraints with the user behavior for improving the robot's performance. We address these challenges using a Programming by Demonstration framework. In the first part of the thesis we describe an approach for decomposing demonstrations into actions and extracting task-space constraints as continuous features that apply throughout each action. The constraints consist of: (1) the reference frame for performing manipulation, (2) the variables of interest relative to this frame, allowing a decomposition in force and position control, and (3) a stiffness gain modulating the contribution of force and position. We then extend this approach to asymmetrical bimanual tasks by extracting features that enable arm coordination: the master--slave role that enables precedence, and the motion--motion or force--motion coordination that facilitates the physical interaction through an object. The set of constraints and the time-independent encoding of each action form a task prototype, used to execute the task. In the second part of the thesis we focus on discovering additional features implicit in the demonstrations with respect to two aspects of the teaching interactions: (1) characterizing the user performance and (2) improving the user behavior. For the first goal we assess the skill of the user and implicitly the quality of the demonstrations by using objective task--specific metrics, related directly to the constraints. We further analyze ways of making the user aware of the robot's state during teaching by providing task--related feedback. The feedback has a direct influence on both the teaching efficiency and the user's perception of the interaction. We evaluated our approaches on robotic experiments that encompass daily activities using two 7 degrees of freedom Kuka LWR robotic arms, and a 53 degrees of freedom iCub humanoid robot

    Vision Sensor based Action Recognition for Improving Efficiency and Quality under the Environment of Industry 4.0

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    In the environment of industry 4.0, human beings are still an important influencing factor of efficiency and quality which are the core of product life cycle management. Hence, monitoring and analyzing humans\u27 actions are essential. This paper proposes a vision sensor based method to evaluate the accuracy of operators\u27 actions. Each action of operators is recognized in real time by a Convolutional Neural Network (CNN) based classification model in which hierarchical clustering is introduced to minimize the effects of action uncertainty. Warnings are triggered when incorrect actions occur in real time and applications of action analysis of workers on a reducer assembling line show the effectiveness of the proposed method. The research is expected to provide a guidance for operators to correct their actions to reduce the cost of quality defects and improve the efficiency of workforce
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