939 resultados para robot kinematics


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Background: The high demanding computational requirements necessary to carry out protein motion simulations make it difficult to obtain information related to protein motion. On the one hand, molecular dynamics simulation requires huge computational resources to achieve satisfactory motion simulations. On the other hand, less accurate procedures such as interpolation methods, do not generate realistic morphs from the kinematic point of view. Analyzing a protein's movement is very similar to serial robots; thus, it is possible to treat the protein chain as a serial mechanism composed of rotational degrees of freedom. Recently, based on this hypothesis, new methodologies have arisen, based on mechanism and robot kinematics, to simulate protein motion. Probabilistic roadmap method, which discretizes the protein configurational space against a scoring function, or the kinetostatic compliance method that minimizes the torques that appear in bonds, aim to simulate protein motion with a reduced computational cost. Results: In this paper a new viewpoint for protein motion simulation, based on mechanism kinematics is presented. The paper describes a set of methodologies, combining different techniques such as structure normalization normalization processes, simulation algorithms and secondary structure detection procedures. The combination of all these procedures allows to obtain kinematic morphs of proteins achieving a very good computational cost-error rate, while maintaining the biological meaning of the obtained structures and the kinematic viability of the obtained motion. Conclusions: The procedure presented in this paper, implements different modules to perform the simulation of the conformational change suffered by a protein when exerting its function. The combination of a main simulation procedure assisted by a secondary structure process, and a side chain orientation strategy, allows to obtain a fast and reliable simulations of protein motion.

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This article introduces an unsupervised neural architecture for the control of a mobile robot. The system allows incremental learning of the plant during robot operation, with robust performance despite unexpected changes of robot parameters such as wheel radius and inter-wheel distance. The model combines Vector associative Map (VAM) learning and associate learning, enabling the robot to reach targets at arbitrary distances without knowledge of the robot kinematics and without trajectory recording, but relating wheel velocities with robot movements.

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The elimination of all external incisions is an important step in reducing the invasiveness of surgical procedures. Natural Orifice Translumenal Endoscopic Surgery (NOTES) is an incision-less surgery and provides explicit benefits such as reducing patient trauma and shortening recovery time. However, technological difficulties impede the widespread utilization of the NOTES method. A novel robotic tool has been developed, which makes NOTES procedures feasible by using multiple interchangeable tool tips. The robotic tool has the capability of entering the body cavity through an orifice or a single incision using a flexible articulated positioning mechanism and once inserted is not constrained by incisions, allowing for visualization and manipulations throughout the cavity. Multiple interchangeable tool tips of the robotic device initially consist of three end effectors: a grasper, scissors, and an atraumatic Babcock clamp. The tool changer is capable of selecting and switching between the three tools depending on the surgical task using a miniature mechanism driven by micro-motors. The robotic tool is remotely controlled through a joystick and computer interface. In this thesis, the following aspects of this robotic tool will be detailed. The first-generation robot is designed as a conceptual model for implementing a novel mechanism of switching, advancing, and controlling the tool tips using two micro-motors. It is believed that this mechanism achieves a reduction in cumbersome instrument exchanges and can reduce overall procedure time and the risk of inadvertent tissue trauma during exchanges with a natural orifice approach. Also, placing actuators directly at the surgical site enables the robot to generate sufficient force to operate effectively. Mounting the multifunctional robot on the distal end of an articulating tube provides freedom from restriction on the robot kinematics and helps solve some of the difficulties otherwise faced during surgery using NOTES or related approaches. The second-generation multifunctional robot is then introduced in which the overall size is reduced and two arms provide 2 additional degrees of freedom, resulting in feasibility of insertion through the esophagus and increased dexterity. Improvements are necessary in future iterations of the multifunctional robot; however, the work presented is a proof of concept for NOTES robots capable of abdominal surgical interventions.

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An algorithm to improve the accuracy and stability of rigid-body contact force calculation is presented. The algorithm uses a combination of analytic solutions and numerical methods to solve a spring-damper differential equation typical of a contact model. The solution method employs the recently proposed patch method, which especially suits the spring-damper differential equations. The resulting semi-analytic solution reduces the stiffness of the differential equations, while performing faster than conventional alternatives.

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This paper considers the question of designing a fully image-based visual servo control for a class of dynamic systems. The work is motivated by the ongoing development of image-based visual servo control of small aerial robotic vehicles. The kinematics and dynamics of a rigid-body dynamical system (such as a vehicle airframe) maneuvering over a flat target plane with observable features are expressed in terms of an unnormalized spherical centroid and an optic flow measurement. The image-plane dynamics with respect to force input are dependent on the height of the camera above the target plane. This dependence is compensated by introducing virtual height dynamics and adaptive estimation in the proposed control. A fully nonlinear adaptive control design is provided that ensures asymptotic stability of the closed-loop system for all feasible initial conditions. The choice of control gains is based on an analysis of the asymptotic dynamics of the system. Results from a realistic simulation are presented that demonstrate the performance of the closed-loop system. To the author's knowledge, this paper documents the first time that an image-based visual servo control has been proposed for a dynamic system using vision measurement for both position and velocity.

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The practice of robotics and computer vision each involve the application of computational algorithms to data. The research community has developed a very large body of algorithms but for a newcomer to the field this can be quite daunting. For more than 10 years the author has maintained two open-source MATLAB® Toolboxes, one for robotics and one for vision. They provide implementations of many important algorithms and allow users to work with real problems, not just trivial examples. This new book makes the fundamental algorithms of robotics, vision and control accessible to all. It weaves together theory, algorithms and examples in a narrative that covers robotics and computer vision separately and together. Using the latest versions of the Toolboxes the author shows how complex problems can be decomposed and solved using just a few simple lines of code. The topics covered are guided by real problems observed by the author over many years as a practitioner of both robotics and computer vision. It is written in a light but informative style, it is easy to read and absorb, and includes over 1000 MATLAB® and Simulink® examples and figures. The book is a real walk through the fundamentals of mobile robots, navigation, localization, arm-robot kinematics, dynamics and joint level control, then camera models, image processing, feature extraction and multi-view geometry, and finally bringing it all together with an extensive discussion of visual servo systems.

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This paper is concerned with the unsupervised learning of object representations by fusing visual and motor information. The problem is posed for a mobile robot that develops its representations as it incrementally gathers data. The scenario is problematic as the robot only has limited information at each time step with which it must generate and update its representations. Object representations are refined as multiple instances of sensory data are presented; however, it is uncertain whether two data instances are synonymous with the same object. This process can easily diverge from stability. The premise of the presented work is that a robot's motor information instigates successful generation of visual representations. An understanding of self-motion enables a prediction to be made before performing an action, resulting in a stronger belief of data association. The system is implemented as a data-driven partially observable semi-Markov decision process. Object representations are formed as the process's hidden states and are coordinated with motor commands through state transitions. Experiments show the prediction process is essential in enabling the unsupervised learning method to converge to a solution - improving precision and recall over using sensory data alone.

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A coverage algorithm is an algorithm that deploys a strategy as to how to cover all points in terms of a given area using some set of sensors. In the past decades a lot of research has gone into development of coverage algorithms. Initially, the focus was coverage of structured and semi-structured indoor areas, but with time and development of better sensors and introduction of GPS, the focus has turned to outdoor coverage. Due to the unstructured nature of an outdoor environment, covering an outdoor area with all its obstacles and simultaneously performing reliable localization is a difficult task. In this paper, two path planning algorithms suitable for solving outdoor coverage tasks are introduced. The algorithms take into account the kinematic constraints of an under-actuated car-like vehicle, minimize trajectory curvatures, and dynamically avoid detected obstacles in the vicinity, all in real-time. We demonstrate the performance of the coverage algorithm in the field by achieving 95% coverage using an autonomous tractor mower without the aid of any absolute localization system or constraints on the physical boundaries of the area.

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[EU]Lan honen gaia SCARA errobot motaren mugimendu gaitasunen analisia egitea da, eta ibilbideen sorkuntzarako metodoekin batera software grafiko batean inplementatzea mugimenduaren simulazioa egin ahal izateko. Errobot serieen zinematikaren oinarrizko ezagutzatik hasita, mota konkretu batetara aplikatu egiten da eta honek aurkezten dituen berezitasunak garatu egiten dira, bi helburutara bideratuta: SCARA errobotaren mugimendu gaitasunak ezagutzea. Ibilbideen sorkuntzarako metodo baten inplementazioa. Hasteko, gaiaren egoera aztertu da, aplikazio nagusien eta ibilbide moten informazioa batzeko. Halaber ibilbideen sorkuntzarako metodoak arakatu dira, erabilera honetarako aproposena aurkitzeko. Jarraian, errobotaren analisia burutu da, ohizko erreminta matematikoak erabiliz, funtsezkoak diren lan eremua eta kokapen singularrak lortzeko. Ostean, software grafikoa garatu da mugimendu gaitasun hauek simulatzeko. Ohiko aplikazioetan oinarritutako ibilbideak sortzeko aukerak gehitu dira. Amaitzeko, oztopoak saihesten dituen ibilbideen sorkuntzarako metodoa inplementatu da, “pick and place” ibilbide motaren barruan.

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设计了一种能够使蛇形机器人运动更灵巧、奇异点更少和运动能力更强的机构 ,对具有三个自由度的新型蛇形机器人单元进行了改进 ,在单元上增加被动轮机构 ,使其具有万向机构的特点。该单元不仅能够用被动轮驱动机器人运动 ,而且增加了类似于主动轮的驱动机构 ,克服了被动轮驱动能力弱的缺点 ,增强了机器人的运动能力。在分析非完整约束的基础上 ,对蛇形机器人的运动学和冗余度进行分析 ,提出了控制该类蛇形机器人运动的分解矩阵方法和分组交替运动法。

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本文首先介绍了视觉伺服的一般原理 .然后提出了一种模型无关的无定标视觉伺服控制方法 ,在这种方法中不需要机器人模型和摄像机模型 ,应用方差最小化的原理推导出了模型无关的无定标视觉伺服控制律 .此外还给出了图像雅可比矩阵的递推公式 .文章最后通过一个轨线跟踪的仿真实验验证了算法的正确性和有效性

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提出一种面向操作手装配系统的快速碰撞检测算法。该算法以机器人运动学和空间解析几何为基础 ,将判断机械手手臂与障碍物是否发生碰撞问题转化为直线段与有界平面是否存在公共点的简单解析几何问题 ,并以 PU MA5 6 0操作手为例对算法加以说明。该算法不仅适用于静态的障碍物已知的环境 ,而且适用于障碍物运动规律已知的动态环境 ,减少了碰撞检测占用的时间 ,提高了路径规划的效率

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Formation of autonomous mobile robots to an arbitrary geometric pattern in a distributed fashion is a fundamental problem in formation control. This paper presents a new fully distributed, memoryless (oblivious) algorithm to the formation control problem via distributed optimization techniques. The optimization minimizes an appropriately defined difference function between the current robot distribution and target geometric pattern. The optimization processes are performed independently by individual robots in their local coordinate system. A movement strategy derived from the results of the distributed optimizations guarantees that every movement makes the current robot configuration approaches the target geometric pattern until the final pattern is reached.

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This thesis presents a new structure of robust adaptive controller applied to mobile robots (surface mobile robot) with nonholonomic constraints. It acts in the dynamics and kinematics of the robot, and it is split in two distinct parts. The first part controls the robot dynamics, using variable structure model reference adaptive controllers. The second part controls the robot kinematics, using a position controller, whose objective is to make the robot to reach any point in the cartesian plan. The kinematic controller is based only on information about the robot configuration. A decoupling method is adopted to transform the linear model of the mobile robot, a multiple-input multiple-output system, into two decoupled single-input single-output systems, thus reducing the complexity of designing the controller for the mobile robot. After that, a variable structure model reference adaptive controller is applied to each one of the resulting systems. One of such controllers will be responsible for the robot position and the other for the leading angle, using reference signals generated by the position controller. To validate the proposed structure, some simulated and experimental results using differential drive mobile robots of a robot soccer kit are presented. The simulator uses the main characteristics of real physical system as noise and non-linearities such as deadzone and saturation. The experimental results were obtained through an C++ program applied to the robot soccer kit of Microrobot team at the LACI/UFRN. The simulated and experimental results are presented and discussed at the end of the text

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