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.     

Rolling on a smooth biparametric surface

In this paper we present a method to calculate the rolling of a rigid convex object on a smooth biparametric surface where a single contact point is maintained during the animation. The object's motion is computed using a prediction-correction schema. The prediction computes the motion of the object rolling on the tangent plane at the current contact point. The next contact point is obtained by projecting the predicted point onto the curved surface. A correction is made according to the local surface curvature. An algorithm which calculates the initial contact point between the surface and the object is given. The rolling of a ball is presented as an example.     

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.     

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.     

Whole-finger manipulation with a two-fingered robot hand

This paper describes a method for whole-finger rolling manipulation using a two-fingered robot hand. 'Whole-finger' refers to the use of the complete phalangeal surface during the manipulation. An example of whole-finger manipulation by the human hand is the rolling of a pen between two fingers. The proposed method is based on a two-dimensional model for modelling an object manipulation and is derived from a study of the movement of the contact line between both fingers. Also, the method uses tactile sensor information to estimate the contact point position together with the local curvature of the object. This whole-finger dexterous manipulation is demonstrated on a prototype two-fingered hand. This 5 d.o.f. hand consists of a tendon driven index and thumb, and is equipped with force and tactile sensors. The dimensions and performance of this device are 'human-sized'. A hybrid force-position control scheme is used. The hierarchical control structure is implemented on a dual transputer system. This paper first describes the kinematic model used for whole-finger manipulation. In the second part, the main emphasis is put on the mechanical design and on the transputer-based control system.     

Redundant grasps,redundant manipulators,and their dual relationships

This article presents a meaningful, practical, and theoretically sound solution that solves the problem of grasping a rigid object with a hand that has redundant (>6) grasping contacts. This is accomplished by introducing compliance at each contact point in such a way as to provide the engineer with the capabilities of object manipulation via controlled forces at the contact points. This method of solution is adapted straight-away to compute the static forces generated in the legs of a redundant in-parallel manipulator that equilibrates a wrench applied to the moving/platform or end-effector. In a way similar to the redundant grasping problem, this is accomplished by introducing the knowledge of the compliances that exist in the legs. The solution thus obtained stems from physical parameters that model the in-parallel manipulator. The in-depth study of the duality between the statics of in-parallel manipulators and the kinematics of serial manipulators reveals a meaningful, practical, and theoretically sound solution for the inverse kinematics of a redundant serial manipulator. This is accomplished by incorporating the knowledge of the compliances that exist or are desired to exist in the joints of the manipulator. (For instance, the torsional compliance in revolute joints or the linear compliance in prismatic joints.) Such information provides a physically meaningful model of the serial manipulator that in turn yields a physically meaningful set of joint increments for a given end-effector twist. © 1992 John Wiley & Sons, Inc.     

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.     

On estimating local shape using contact sensing

In this paper we investigate an exploratory procedure (EP) for determining the local shape or curvature of objects with curved surfaces, using contact sensing by a dexterous robotic agent. The EP is based on rolling a probe (a finger) on the surface of an unknown object. Using the known geometry of the probe tip (fingertip) and the sensed displacement of contact point, we use kinematic equations for two rigid bodies in contact to estimate the curvature of the unknown object at a point. We demonstrate this approach with simulations and analyze its sensitivity to noise caused by sensing and measurement errors. This local information can then be used in the global object shape reconstruction algorithms. © 2000 John Wiley & Sons, Inc.     

On the grasping stability and optimality under external perturbations

There are two types of grasping analysis in robotics research: find the grasping force distributions among the grasping fingers when given the contact points and find a good set of the contact points when given the shape of the object. Each kind of problem is associated with optimality and stability analysis. In this article, we investigate the grasping stability and optimality issues under the influence of external perturbations. A rotation‐displacement geometry model is used in computing the changes of grasping forces under external perturbations. Using these results, we present the concept of perturbation closure, which plays the central role in our analysis. A method for finding the local minimal perturbation resisting forces required for non‐slip contacts is developed based on this concept. A grasp so determined is guaranteed to be stable if the external perturbations do not exceed the threshold. Based on this property, we develop a quantitative measurement that can be used to evaluate the performance of different grasping configurations. One can use this measurement to determine the best grasping configuration from a set of perturbation resisting grasps. This actually gives a method which enables the optimal grasping configuration to be found. Both two‐dimensional and three‐dimensional cases are discussed in detail for determining the perturbation closure, the local minimal perturbation resisting force, and the perturbation resisting grasp. Examples are given at the end of the article to illustrate our idea. ©1999 John Wiley & Sons, Inc.     

Modeling of Viscoelastic Contacts and Evolution of Limit Surface for Robotic Contact Interface

Viscoelastic contact is a type of contact which includes, in addition to linear or nonlinear elastic response, time-dependent response due to relaxation or creep phenomena that govern the contact behavior. The characteristics of the time-dependent relaxation of such a viscoelastic contact are typically exponentially decaying functions, and exponentially growing functions for creep, respectively. Such contacts can be found in anthropomorphic robotic fingers, soft materials, viscoelastic skin with rigid core, and human fingers and feet. In this paper, the nature of viscoelastic contacts is investigated, and the evolution of their friction limit surfaces and of the pressure distributions at the contact interface are studied. Two cases commonly found in robotic grasping and manipulation are discussed. Based on the modeling formulation, it is found that the two important parameters of analysis and modeling for such contacts, i.e., the radius of contact area and the profile of pressure distribution, can be chosen using proposed coupling equations as the viscoelastic contact interface evolves with time. The new contribution of this paper includes a proposal of coupling equations between the two important parameters to describe the viscoelastic contact interface, and a study of the evolution of limit surfaces for viscoelastic contact interface due to temporal dependency, and the implication on grasp stability. It is found from the evolution of limit surfaces that when normal force is applied with typical viscoelastic contacts, grasp becomes more stable as time elapses. The modeling can be applied to the design of fingertips and the analysis of robotic grasping and manipulation involving viscoelastic fingers     

Surface Fairing towards Regular Principal Curvature Line Networks

Freeform surfaces whose principal curvature line network is regularly distributed, are essential to many real applications like CAD modeling, architecture design, and industrial fabrication. However, most designed surfaces do not hold this nice property because it is hard to enforce such constraints in the design process. In this paper, we present a novel method for surface fairing which takes a regular distribution of the principal curvature line network on a surface as an objective. Our method first removes the high‐frequency signals from the curvature tensor field of an input freeform surface by a novel rolling guidance tensor filter, which results in a more regular and smooth curvature tensor field, then deforms the input surface to match the smoothed field as much as possible. As an application, we solve the problem of approximating freeform surfaces with regular principal curvature line networks, discretized by quadrilateral meshes. By introducing the circular or conical conditions on the quadrilateral mesh to guarantee the existence of discrete principal curvature line networks, and minimizing the approximate error to the original surface and improving the fairness of the quad mesh, we obtain a regular discrete principal curvature line network that approximates the original surface. We evaluate the efficacy of our method on various freeform surfaces and demonstrate the superiority of the rolling guidance tensor filter over other tensor smoothing techniques. We also utilize our method to generate high‐quality circular/conical meshes for architecture design and cyclide spline surfaces for CAD modeling.     

Decentralized adaptive coordinated control of multiple robot arms without using a force sensor

This paper presents a distributed adaptive coordinated control method for multiple robot arms grasping a common object. The cases of rigid contact and rolling contact are analyzed. In the proposed controller, the dynamic parameters of both object and robot arms are estimated adaptively. The desired motions of the robot arms are generated by an estimated object reference model. The control method requires only the measurements of the positions and velocities of the object and robot arms, but not the measurements of forces and moments at contact points. The asymptotic convergence of trajectory is proven by the Lyapunov-like Lemma. Experiments involving two robot arms handling a common object are shown.     

虚拟手抓持规则融合策略研究

群体虚拟手抓持规则是虚拟手和虚拟物体进行抓持操作的交互规则,用于判定虚拟手是否能够成功抓持物体。对基于几何的虚拟手抓持规则和基于物理的虚拟手抓持规则分别进行了研究,针对基于几何的虚拟手抓持规则规则简单、仿真效果较差,基于物理模型的虚拟手抓持规则计算复杂、难以实现实时仿真的问题:（1）改进基于几何的虚拟手抓持规则,通过接触点位置、法矢和抓持面法矢制定抓持规则,使其效果逼近力封闭虚拟手抓持规则;（2）利用力封闭计算中抓持接触点和法矢不变的特性,通过内力配比避免了抓持操作中的非线性规划求解,使抓持操作阶段实现实时仿真;（3）通过几何约束进行初始抓持判断-力封闭计算校正-内力配比力封闭计算的策略,实现了完整的抓持过程实时仿真。设计的交互实验说明该抓持规则能实现高沉浸感和实时性的抓持仿真,可以应用到虚拟训练、虚拟装配等仿真平台。     

Manipulation of polygonal objects with two wheeled-tip fingers: Planning in the presence of contact position error

This paper addresses the planning problem of object manipulation using wheeled-tip robots considering the wheel-object contact positioning error. The term wheeled-tip refers to a new mechanism that incorporates active wheels at robot’s fingertips and allows the grasp contact-point to move along the object’s surface. The benefits of unlimited rolling contact is achieved at the cost of contact positioning error that may cause the manipulation to fail. We propose a probabilistic based algorithm for robot motion planning that in addition to being collision free, guarantees the stability of the grasp throughout the planned path. To do so, first we introduce an algorithm that ensures the kinematical stability of the grasp during manipulation by respecting the force closure constraint. Further we extend the algorithm to address the practical uncertainties involved in the position of wheel-object contact points. The proposed algorithms can be employed for manipulators with limited rolling contacts, as well. The algorithms have been tested and the results prove that the planned path can be trusted in uncertain situations.     

A HUMANLIKE GRASPING FORCE PLANNER FOR OBJECT MANIPULATION BY ROBOT MANIPULATORS

Recently robot manipulators have been expected to perform sophisticated tasks such as object manipulation, assembly tasks, or cooperative tasks with human workers. In order to realize these tasks with robot manipulators, it is important to understand the human strategy of object grasping and manipulation. In this study, we have examined how a human being decides the grasping force necessary to manipulate an unknown object in order to apply human object-grasping strategy for robotic systems. Experiments have been performed with several kinds of objects under several kinds of conditions to investigate how much grasping force human subjects generate. Adjustment strategy of human grasping force when the object is manipulated or in contact with an environment is also examined. Neural networks (the desired grasping force planner) that generate the humanlike desired grasping force are then designed for robotic systems. The effectiveness of the proposed desired grasping force planner is evaluated via experiments.     

Slippage control in soft finger grasping and manipulation

Handling objects with robotic soft fingers without considering the odds of slippage are not realistic. Grasping and manipulation algorithms have to be tested under such conditions for evaluating their robustness. In this paper, a dynamic analysis of rigid object manipulation with slippage control is studied using a two-link finger with soft hemispherical tip. Dependency on contact forces applied by a soft finger while grasping a rigid object is examined experimentally. A power-law model combined with a linear viscous damper is used to model the elastic behavior and damping effect of the soft tip, respectively. In order to obtain precise dynamic equations governing the system, two second-order differential equations with variable coefficients have been designed to describe the different possible states of the contact forces accordingly. A controller is designed based on the rigid fingertip model using the concept of feedback linearization for each phase of the system dynamics. Numerical simulations are used to evaluate the performance of the controller. The results reveal that the designed controller shows acceptable performance for both soft and rigid finger manipulation in reducing and canceling slippage. Furthermore, simulations indicate that the applied force in the soft finger manipulation is considerably less than the rigid “one.”.     

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.     

Can bi‐cubic surfaces be class A?

'Class A surface’ is a term in the automotive design industry, describing spline surfaces with aesthetic, non‐oscillating highlight lines. Tensor‐product B‐splines of degree bi‐3 (bicubic) are routinely used to generate smooth design surfaces and are often the de facto standard for downstream processing. To bridge the gap, this paper explores and gives a concrete suggestion, how to achieve good highlight line distributions for irregular bi‐3 tensor‐product patch layout by allowing, along some seams, a slight mismatch of normals below the industry‐accepted tolerance of one tenth of a degree. Near the irregularities, the solution can be viewed as transforming a higher‐degree, high‐quality formally smooth surface into a bi‐3 spline surface with few pieces, sacrificing formal smoothness but qualitatively retaining the shape.     

A brief review of affordance in robotic manipulation research

Abstract

This paper presents a brief review of affordance research in robotics, with special concentrations on its applications in grasping and manipulation of objects. The concept of affordance could be a key to realize human-like advanced manipulation intelligence. First, we discuss the concept of affordance while associating with the applications in robotics. Then, we intensively explore the studies that utilize affordance for robotic manipulation applications, such as object recognition, grasping, and object manipulation including tool-use. They obtain and use affordance by several ways like learning from human, using simulation, and real-world execution. Moreover, we show our current work, which is a cloud database for advanced manipulation intelligence. The database accumulates various data related to manipulation task execution and will be an open platform to leverage various affordance techniques.     

gripper

Grasping of objects has been a challenging task for robots. The complex grasping task can be defined as object contact control and manipulation subtasks. In this paper, object contact control subtask is defined as the ability to follow a trajectory accurately by the fingers of a gripper. The object manipulation subtask is defined in terms of maintaining a predefined applied force by the fingers on the object. A sophisticated controller is necessary since the process of grasping an object without a priori knowledge of the object's size, texture, softness, gripper, and contact dynamics is rather difficult. Moreover, the object has to be secured accurately and considerably fast without damaging it. Since the gripper, contact dynamics, and the object properties are not typically known beforehand, an adaptive critic neural network (NN)-based hybrid position/force control scheme is introduced. The feedforward action generating NN in the adaptive critic NN controller compensates the nonlinear gripper and contact dynamics. The learning of the action generating NN is performed on-line based on a critic NN output signal. The controller ensures that a three-finger gripper tracks a desired trajectory while applying desired forces on the object for manipulation. Novel NN weight tuning updates are derived for the action generating and critic NNs so that Lyapunov-based stability analysis can be shown. Simulation results demonstrate that the proposed scheme successfully allows fingers of a gripper to secure objects without the knowledge of the underlying gripper and contact dynamics of the object compared to conventional schemes.