974 resultados para robotics manipulators


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At the crossing between motor control neuroscience and robotics system theory, the paper presents a rhythmic experiment that is amenable both to handy laboratory implementation and simple mathematical modeling. The experiment is based on an impact juggling task, requiring the coordination of two upper-limb effectors and some phase-locking with the trajectories of one or several juggled objects. We describe the experiment, its implementation and the mathematical model used for the analysis. Our underlying research focuses on the role of sensory feedback in rhythmic tasks. In a robotic implementation of our experiment, we study the minimum feedback that is required to achieve robust control. A limited source of feedback, measuring only the impact times, is shown to give promising results. A second field of investigation concerns the human behavior in the same impact juggling task. We study how a variation of the tempo induces a transition between two distinct control strategies with different sensory feedback requirements. Analogies and differences between the robotic and human behaviors are obviously of high relevance in such a flexible setup. © 2008 Elsevier Ltd. All rights reserved.

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Robotics researchers increasingly agree that ideas from biology and self-organization can strongly benefit the design of autonomous robots. Biological organisms have evolved to perform and survive in a world characterized by rapid changes, high uncertainty, indefinite richness, and limited availability of information. Industrial robots, in contrast, operate in highly controlled environments with no or very little uncertainty. Although many challenges remain, concepts from biologically inspired (bio-inspired) robotics will eventually enable researchers to engineer machines for the real world that possess at least some of the desirable properties of biological organisms, such as adaptivity, robustness, versatility, and agility.

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Locomotion has been one of the frequently used case studies in hands-on curricula in robotics education. Students are usually instructed to construct their own wheeled or legged robots from modular robot kits. In the development process of a robot students tend to emphasize on the programming part and consequently, neglect the design of the robot's body. However, the morphology of a robot (i.e. its body shape and material properties) plays an important role especially in dynamic tasks such as locomotion. In this paper we introduce a case study of a tutorial on soft-robotics where students were encouraged to focus solely on the morphology of a robot to achieve stable and fast locomotion. The students should experience the influence material properties exert on the performance of a robot and consequently, extract design principles. This tutorial was held in the context of the 2012 Summer School on Soft Robotics at ETH Zurich, which was one of the world's first courses specialized in the emerging field. We describe the tutorial set-up, the used hardware and software, the students assessment criteria as well as the results. Based on the high creativity and diversity of the robots built by the students, we conclude that the concept of this tutorial has great potentials for both education and research. © 2013 IEEE.

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There has been an increasing interest in applying biological principles to the design and control of robots. Unlike industrial robots that are programmed to execute a rather limited number of tasks, the new generation of bio-inspired robots is expected to display a wide range of behaviours in unpredictable environments, as well as to interact safely and smoothly with human co-workers. In this article, we put forward some of the properties that will characterize these new robots: soft materials, flexible and stretchable sensors, modular and efficient actuators, self-organization and distributed control. We introduce a number of design principles; in particular, we try to comprehend the novel design space that now includes soft materials and requires a completely different way of thinking about control. We also introduce a recent case study of developing a complex humanoid robot, discuss the lessons learned and speculate about future challenges and perspectives.

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There has been an increasing interest in the use of unconventional materials and morphologies in robotic systems because the underlying mechanical properties (such as body shapes, elasticity, viscosity, softness, density and stickiness) are crucial research topics for our in-depth understanding of embodied intelligence. The detailed investigations of physical system-environment interactions are particularly important for systematic development of technologies and theories of emergent adaptive behaviors. Based on the presentations and discussion in the Future Emerging Technology (fet11) conference, this article introduces the recent technological development in the field of soft robotics, and speculates about the implications and challenges in the robotics and embodied intelligence research. © Selection and peer-review under responsibility of FET11 conference organizers and published by Elsevier B.V.

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New robotics is an approach to robotics that, in contrast to traditional robotics, employs ideas and principles from biology. While in the traditional approach there are generally accepted methods (e. g., from control theory), designing agents in the new robotics approach is still largely considered an art. In recent years, we have been developing a set of heuristics, or design principles, that on the one hand capture theoretical insights about intelligent (adaptive) behavior, and on the other provide guidance in actually designing and building systems. In this article we provide an overview of all the principles but focus on the principles of ecological balance, which concerns the relation between environment, morphology, materials, and control, and sensory-motor coordination, which concerns self-generated sensory stimulation as the agent interacts with the environment and which is a key to the development of high-level intelligence. As we argue, artificial evolution together with morphogenesis is not only "nice to have" but is in fact a necessary tool for designing embodied agents.

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THERE ARE MANY different kinds of robots: factory automation systems that weld and assemble car engines; machines that place chocolates into boxes; medical devices that support surgeons in operations requiring high-precision manipulation; cars that drive automatically over long distances; vehicles for planetary exploration; mechanisms for powerline or oil platform inspection; toys and educational toolkits for schools and universities; service robots that deliver meals, clean floors, or mow lawns; and "companion robots" that are real partners for humans and share our daily lives. In a sense, all these robots are inspired by biological systems; it's just a matter of degree. A driverless vehicle imitates animals moving autonomously in the world.© 2012 ACM.

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水下机械手作为水下机器人通用作业工具得到广泛地应用,目前水下机械手的主要操作方式为主从方式。虽然主从方式具有操作直观,灵活的特点,但难于完成需要精确定位,轨迹控制的水下作用,如海洋石油钻井平台导管架的检查作用。为了扩展水下机器人的作业能力,提高水下作业智能化程度,沈阳自动化所承担国家863课题“水下虚拟遥操作与监控机械手系统”关键技术的研究工作。作者参加了此课题的研究工作,以Schilling水下机械手为研究对象,深入研究机械手的作用功能,对机械手的逆运动学,焊缝空间轨迹规划作了深入的研究,形成本文阐述的主要内容。由于Schilling水下机械手各关节之间的连接参数中存在多个偏距,其运动学逆解不能简单由解析方式给出。机械手进行控制与轨迹规划等操作必须找到一种快速求解的方法。本篇文章得出一种基于信赖域法的机械手运动学逆解算法。由于该算法具有收敛速度快的特点,故可以被应用于在线求解机械手运动学逆解;由于没有直接求解二阶导数,故不存在奇异解的问题。经理论分析和实验证明该方法在解决水下监控机械手在线跟踪水下结构物空间轨迹的技术问题具有较好的效果。作为课题的实际应用背景的导管架焊缝曲面为一复杂的空间曲面。为了实现课题的研究目标,本课题不仅要求解焊缝的轨迹,而且要给出其法线方向。对于这样一个问题,用空间解析几何和微分几何方法是很难求解的,本文给出了一种基于B样条参数曲面及曲面求交的方法,具有速度快,通用性强的优点。

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In this paper, a disturbance controller is designed for making robotic system behave as a decoupled linear system according to the concept of internal model. Based on the linear system, the paper presents an iterative learning control algorithm to robotic manipulators. A sufficient condition for convergence is provided. The selection of parameter values of the algorithm is simple and easy to meet the convergence condition. The simulation results demonstrate the effectiveness of the algorithm..

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Compliant motion occurs when the manipulator position is constrained by the task geometry. Compliant motion may be produced either by a passive mechanical compliance built in to the manipulator, or by an active compliance implemented in the control servo loop. The second method, called force control, is the subject of this report. In particular, this report presents a theory of force control based on formal models of the manipulator, and the task geometry. The ideal effector is used to model the manipulator, and the task geometry is modeled by the ideal surface, which is the locus of all positions accessible to the ideal effector. Models are also defined for the goal trajectory, position control, and force control.

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The Vision Flashes are informal working papers intended primarily to stimulate internal interaction among participants in the A.I. Laboratory's Vision and Robotics group. Many of them report highly tentative conclusions or incomplete work. Others deal with highly detailed accounts of local equipment and programs that lack general interest. Still others are of great importance, but lack the polish and elaborate attention to proper referencing that characterizes the more formal literature. Nevertheless, the Vision Flashes collectively represent the only documentation of an important fraction of the work done in machine vision and robotics. The purpose of this report is to make the findings more readily available, but since they are not revised as presented here, readers should keep in mind the original purpose of the papers!