多指手协调操作中内力的计算

机器人多指手协调操作物体时,合理地确定手指对被操作物体的作用力是必要的.本文将手指尖与被操作物体之间接触模拟为具有摩擦的点接触,对由多指手与被操作物体组成的这样一个速度较低的系统作了静力分析,并对多指手操作物体时的操作力作了合理的分配,提出基于力矩最小的内力的最优计算方法,在计算中,充分考虑到手指只能推而不能拉物体这一实事.最后,以4个手指操作一个圆柱形物体为例.对操作过程作了图形仿真.     

具有滚动接触的多指手操作运动学及其算法

研究多指手滚动操作的运动学及其算法.简要介绍了滚动接触运动方程,根据接触的 运动学约束,建立了描述物体与关节速度关系的关节--物体运动方程,并给出物体与手指表 面间相对角速度的表达式.得到的关节--物体运动方程、相对角速度表达式和接触运动方程 构成了形式简洁的滚动操作运动学方程.结合对方程的分析,进一步给出了多指手滚动操作物 体跟踪期望的运动轨迹时,关节运动轨迹的生成算法.     

含弧形自由度仿人灵巧手掌的机构设计

提出了一种人手掌的简化模型,根据该模型,设计了仿人灵巧手掌的机构,使得只作为仿人灵巧手手指及其控制部件机架的手掌形成弧形自由度参加手部动作,提高了仿人灵巧手通用性、灵活性和抓持物体的适应性。经优化设计和仿真,机构完全符合灵巧手进行运动时手掌的运动要求。     

三指机器人手的运动学研究

本文研究了指端与物体间为纯滚动接触时三指9关节机器人手操作物体的运动学问题,建立了手指关节运动与物体运动之间的位置关系、速度关系和加速度关系,给出了9个节间的运动约束条件。     

基于非完整运动规划的多指手灵巧操作

灵巧操作是多指手操作的一个重要方面,探讨实现这种操作的纯滚动方法.首先利 用纯滚动的非完整特性,进行非完整运动的最优路径规划,然后根据规划结果应用多指手操 作运动学方程确定手指的运动.为多指手灵巧操作的实现提供了一条途径.     

具有运动耦合关节的灵巧手运动学反解

研究了具有运动耦合关节的灵巧手手指的运动学反解问题.由于关节运动耦合导致某些关节角得不到解析解,需采用数值解.为提高数值迭代速度,将多变量的数值迭代转换为单变量的迭代.仿真实验结果表明,文中提出的方法能够满足灵巧手的主从操作系统的实时性操作要求.     

一种虚拟环境温度触觉再现仿真系统设计

分析了温度触觉感知特性,提出了手指和物体接触时各自表面的温度变化过程,结合单热源温度触觉再现装置设计了一种基于三维力反馈手控器的虚拟环境温度触觉再现仿真系统。手控器可控制虚拟手的动作,对虚拟物体进行温度和力的感知。仿真系统中能再现手指与不同热属性物体接触时的温度变化和力变化,且视觉效果逼真,体现了温度触觉再现的实时性和有效性。     

四指机器人灵巧手在哈尔滨问世

由哈尔滨工业大学机器人研究所与德国宇航中心合作开发的具有多种传感功能的新一代机器人灵巧手在哈尔滨问世。该灵巧手有4个手指，13个自由度，其中每个手指有4个关节、3个自由度，拇指另有一个开合的自由度：灵巧手共有机械零件600多个．表面粘贴的电子元器件1600多个，传感器89个：手的尺寸略大于人手，整体重量1．8千克。灵巧手可以弹出美妙的音乐，可以轻松地抓起饮料瓶．也可以灵活地做出“OK”的手势。到目前为止．已经有5套仿人灵巧手销往德国。     

机器人多指手灵巧抓持规划

抓持规划是机器人灵巧手要完成预期任务所面临的一个重要问题．本文采用主从操作方式进行灵巧手的指尖抓持规划，由人手决定抓持接触点的位置， 灵巧手通过调整其手掌的位置和姿态保证各手指在人手指定的位置上抓持物体．根据灵巧手的操作特点，提出以关节灵活度来描述关节运动各向同性的能力，并据此定义灵巧手操作灵活度，作为灵巧手抓持位形性能的评价指标．以最大操作灵活度作为优化目标函数，寻求最优的抓持性能．同时，借鉴人手的抓持经验，通过主从操作方式，建立从人手到灵巧手的运动映射关系，从而为手掌位置优化问题提供合理的初值．仿真实验结果说明了文中方法的有效性．     

多指手操作:运动学算法和实验

本文探讨了多指手的运动学操作问题，即给出被抓物体所要运动的轨迹，如何用多指手进行操作以实现物体的运动，也即怎样根据物体的运动来确定各手指的运动．我们提出和考察了三种运动学操作算法：广义逆算法、接触轨迹控制算法和抓持优化算法．每种算法各有其特点，可根据具体的操作任务加以采用，甚至可综合用于复杂操作任务的不同阶段．在实验系统ＨＫＵＳＴＨＡＮＤ上以两指手操作蓝球的实验实现了这些算法，考察了其可行性和有效性．     

A differential-geometric approach for 2D and 3D object grasping and manipulation

This article presents an expository work on a differential-geometric treatment of fundamental problems of 2D and 3D object grasping and manipulation by a pair of robot fingers with multi-joints under holonomic or nonholonomic constraints. First, Lagrange’s equation of motion of a fingers-object system whose motion is confined to a vertical plane is derived under holonomic constraints when rolling contacts between finger-ends and object surfaces are permitted. Then, a class of control signals called “blind grasping” and constructed without knowing the object kinematics or using any external sensing like vision or tactile sensation is shown to realize stable object grasping in a dynamic sense. Stability of motion and its convergence to an equibrium manifold are treated on the basis of differential geometry of solution trajectories of the closed-loop dynamics on the constraint manifolds. Second, a mathematical model of 3D object grasping and manipulation by a pair of multi-joint robot fingers is derived under the assumption that spinning motion of rotation around the opposing axis between contact points does no more arise. It is shown that, differently from the 2D case, the instantaneous axis of rotation of the object is time-varying, which induces a nonholonomic constraint expressed as a linear differential equation of rotational motion of the pinched object. It is shown that there is a class of control signals constructed without knowing the object kinematics or using external sensings that can realize “blind grasping” in a dynamic sense. Finally, it is shown that the proposed differential geometric treatment of stability can naturally cope with redundancy resolution problems of surplus degrees-of-freedom (d.f.) of the overall fingers-object system, which is closely related to Bernstein’s d.f. problem.     

Learning Motion of Dexterous Manipulation For A Pair of Multi‐DOF Fingers With Soft‐TIPS

This paper shows that a pair of dual multi‐DOF fingers with soft‐tips can learn iteratively a desired periodic motion of manipulation of an object if sensory feedback signals are designed adequately. It is shown that dynamics of the overall fingers and object system satisfy passivity but residual error dynamics for a given periodic posture of the object and a fixed value of contact force satisfy output‐dissipativity only in an approximate sense. Numerical simulation results are presented which show that the pair of fingers manipulating an object is capable of learning iteratively a variety of dexterous motions with a good performance.     

Dexterous manipulation of an object by means of multi‐DOF robotic fingers with soft tips

This article analyzes the dynamics of motion of various setups of two multiple degree‐of‐freedom (DOF) fingers that have soft tips, in fine manipulation of an object, and shows performances of their motions via computer simulation. A mathematical model of these dynamics is described as a system of nonlinear differential equations expressing motion of the overall fingers‐object system together with algebraic constraints due to tight area contacts between the finger‐tips and surfaces of the object. First, problems of (1) dynamic, stable grasping and (2) regulation of the object rotational angle by means of a setup of dual two‐DOF fingers, are treated. Second, the problem of regulating the position of the object mass center by means of a pair of two‐DOF and three‐DOF fingers is considered. Third, a set of dual three‐DOF fingers is treated, in order to let it perform a sophisticated task, which is specified by a periodic pattern of the object posture and a constant internal force. In any case, there exist sensory‐motor coordinations, which are described by analytic feedback connections from sensing to actions at finger joints. In the cases of setpoint control problems, convergences of motion to secure grasping together with the specified object rotational angle and/or the specified object mass center position, are proved theoretically. A constraint stabilization method (CSM) is used for solving numerically the differential algebraic equations to show performances of the proposed sensory‐feedback schemes. © 2002 Wiley Periodicals, Inc.     

Dynamic Capturing Strategy for a 2-D Stick-Shaped Object Based on Friction Independent Collision

This paper proposes dynamic capturing strategies where a 2D stick-shaped object with both translational and rotational velocity is completely stopped by two robotic fingers. We first show the fingertip position and the object orientation for generating a desired velocity of the object under the friction independent collision. Once the object results in a pure translational motion whose direction is perpendicular to the longitudinal axis of object, it is guaranteed that two fingers can always capture the object irrespective of friction coefficient. By using this nature, we show both 2-step and 3-step capturing strategies for a 2D stick-shaped object whose width is negligibly small. The 3-step capturing strategy can guide the object in an arbitrary direction, while the 2-step one can do it only in a particular direction. The proposed strategies are demonstrated by experiments for verifying our idea.     

Intelligent control of multi-fingered hands

This paper is concerned with intelligent control for grasping and manipulation of an object by multi-fingered robot hands with rigid or soft hemispheric finger ends that induce rolling contacts with the object. Even in the case of 2D motion like pinching by means of a pair of multi-degrees of freedom robot fingers, there arises an interesting family of Lagrange’s equations of motion with many geometric constraints, which are under-actuated, redundant, and non-holonomic in some sense. Regardless of underactuation of dynamics, it is possible to find a class of sensory feedback signals that realize secure grasp of an object together with control of object orientation. In regard to the secure grasping, a problem of force/torque closure for 2D objects in a dynamic sense plays a crucial role. It is shown that proposed sensory feedback signals satisfying the dynamic force/torque closure can be constructed without knowing object kinematic parameters and location of the mass center. To prove the convergence of motion of the overall fingers–object system under the circumstance of redundancy of joints, new concepts called “stability on a manifold” and “asymptotic stability on a manifold” are introduced. Based on the results found for intelligent control of robotic hands, the last two sections attempt to discuss why human multi-fingered hands can become so dexterous at grasping and object manipulation.     

High Precision Constrained Grasping with Cooperative Adaptive Handcontrol

A method for high precision constrained object manoeuvering for non-redundant rigid multifinger hands is proposed. A passivity-based adaptive cooperative control scheme carries out compensation of all uncertain inertial and dynamic friction forces to guarantee asymptotic tracking of all contact forces and joint position-orientation trajectories over orthogonal force- and position-based impedance error manifolds. Optimal internal and external force trajectories are obtained to minimize the contact forces onto the constrained object while exerting a given desired contact force onto the environment. The simulation study of two robot fingers manipulating a constrained object for combined fast and slow velocity regimes shows that when the dynamic friction compensation is turned on tracking errors decrease tenfold.     

Dynamics and Stability of Blind Grasping of a 3-Dimensional Object under Non-holonomic Constraints

A mathematical model expressing the motion of a pair of multi-DOF robot fingers with hemi-spherical ends, grasping a 3-D rigid object with parallel flat surfaces, is derived, together with non-holonomic constraints. By referring to the fact that humans grasp an object in the form of precision prehension, dynamically and stably by opposable forces, between the thumb and another finger (index or middle finger), a simple control signal constructed from finger-thumb opposition is proposed, and shown to realize stable grasping in a dynamic sense without using object information or external sensing (this is called "blind grasp" in this paper). The stability of grasping with force/torque balance under non-holonomic constraints is analyzed on the basis of a new concept named "stability on a manifold". Preliminary simulation results are shown to verify the validity of the theoretical results.     

Qualitative detection of motion by a moving observer

Two complementary methods for the detection of moving objects by a moving observer are described. The first is based on the fact that, in a rigid environment, the projected velocity at any point in the image is constrained to lie on a 1-D locus in velocity space whose parameters depend only on the observer motion. If the observer motion is known, an independently moving object can, in principle, be detected because its projected velocity is unlikely to fall on this locus. We show how this principle can be adapted to use partial information about the motion field and observer motion that can be rapidly computed from real image sequences. The second method utilizes the fact that the apparent motion of a fixed point due to smooth observer motion changes slowly, while the apparent motion of many moving objects such as animals or maneuvering vehicles may change rapidly. The motion field at a given time can thus be used to place constraints on the future motion field which, if violated, indicate the presence of an autonomously maneuvering object. In both cases, the qualitative nature of the constraints allows the methods to be used with the inexact motion information typically available from real-image sequences. Implementations of the methods that run in real time on a parallel pipelined image processing system are described.