Search results

The purpose of this paper is to achieve stable grasping and dexterous in-hand manipulation, the control of the multi-fingered robotic hand is a difficult problem as the hand has many degrees of freedom with various grasp configurations.

To achieve this goal, a novel object-level impedance control framework with optimized grasp force and grasp quality is proposed for multi-fingered robotic hand grasping and in-hand manipulation. The minimal grasp force optimization aims to achieve stable grasping satisfying friction cone constraint while keeping appropriate contact forces without damage to the object. With the optimized grasp quality function, optimal grasp quality can be obtained by dynamically sliding on the object from initial grasp configuration to final grasp configuration. By the proposed controller, the in-hand manipulation of the grasped object can be achieved with compliance to the environment force. The control performance of the closed-loop robotic system is guaranteed by appropriately choosing the design parameters as proved by a Lyapunove function.

Simulations are conducted to validate the efficiency and performance of the proposed controller with a three-fingered robotic hand.

This paper presents a method for robotic optimal grasping and in-hand manipulation with a compliant controller. It may inspire other related researchers and has great potential for practical usage in a widespread of robot applications.

One of the development trends of robots is to enable robots to have the ability of anthropomorphic manipulation. Grasping is the first step of manipulation. For mobile manipulator robots, grasping a target during the movement process is extremely challenging, which requires the robots to make rapid motion planning for arms under uncertain dynamic disturbances. However, there are many situations require robots to grasp a target quickly while they move, such as emergency rescue. The purpose of this paper is to propose a method for target dynamic grasping during the movement of a robot.

An off-line learning from demonstrations method is applied to learn a basic reach model for arm and a motion model for fingers. An on-line dynamic adjustment method of arm speed for active and passive grasping mode is designed.

The experimental results of the robot movement on flat, slope and speed bumps ground show that the proposed method can effectively solve the problem of fast planning under uncertain disturbances caused by robot movement. The method performs well in the task of target dynamic grasping during the robot movement.

The main contribution of this paper is to propose a method to solve the problem of rapid motion planning of the robot arm under uncertain disturbances while the robot is grasping a target in the process of robot movement. The proposed method significantly improves the grasping efficiency of the robot in emergency situations. Experimental results show that the proposed method can effectively solve the problem.

This paper introduces a newly developed knowledge management concept, dynamic intellectual capital (IC), which refers to a company’s ability for self‐renewal. The paper presents how dynamic IC is created in three different knowledge environments – mechanistic, organic and dynamic – and brings out relevant empirical evidence from three case studies of multinational and Chinese firms. The paper concludes that knowledge‐intensive organizations need to master all the three knowledge environments regardless of their different strategic focus. Failures on any environment might form a hindrance for market efficiency. The development of dynamic IC is subject to the firm’s ability to balance both current arena (e.g. realized IC) and potential force (e.g. potential IC). The development of dynamic IC is strongly based on multi‐way communication, which must include both top‐down and bottom‐up as well as cross functional communication. The analysis of tensions, problems and challenges can be a critical step toward a self‐renewing organization in managing such complexity of dynamic IC.

The purpose of this paper is to provide an accurate dynamic model for the flexible cable capture mechanism and to analyze the dynamic characteristics in the capturing process.

The absolute nodal coordinate formulation (ANCF) that based on the continuum mechanics approach is applied in the capture task using flexible cables. An ANCF cable element in which axial and bending strain energy are taken into account is presented to model the flexible cables. The generalized coordinates of ANCF are absolute displacements and slopes and make no small deformation assumptions; therefore, this element has a remarkable superiority in the large rotation and deformation analysis of flexible cables compared to the conventional floating frame of reference formulation (FFRF). The mass matrix of the cable element is constant, which will reduce the degree of non-linearity of the dynamic equations. The contact force between the steel cables and capture rod is calculated by the non-linear contact dynamic model, in which material and geometry properties of contact bodies are considered.

The stress distribution of steel cables is investigated in the numerical studies which show that the closer to the ends of the cable, the larger axial forces and smaller bending moments they will be. The reduction of grasping velocity will lead to a decrease in the contact force and the oversize peak value of contact force is more likely to be avoided when reducing the elastic modulus of steel cables to obtain a greater soft capture capability.

The work shows a practical possibility to improve modeling accuracy of the capture mechanism. Results of the analyses can provide references for the design and analysis of the capture task.

The ANCF is first used in the analysis of the capture task with flexible cables, and some useful results which have not been published before are obtained.

Robotic hands are still a long way from matching the grasping and manipulation capability of their human counterparts, but computer simulation may help us understand this disparity. We present our publicly available simulator, and describe our research projects involving the system including the development of a human hand model derived from experimental measurements.

Unlike other simulation systems, our system was built specifically to analyze grasps. It can import a wide variety of robot designs by using standard descriptions of the kinematics and link geometries. Various components support the analysis of grasps, visualization of results, dynamic simulation of grasping tasks, and grasp planning.

The simulator has been used in several grasping research problems and can be used to plan grasps for an actual robot. With the aid of a vision system, we have shown that these grasps can be executed by a robot.

We are currently developing methods to handle deformable surfaces, tendon driven models, and non‐ideal joints in order to better model human grasping.

This work is part of our current project to create a biomechanically realistic human hand model to better understand what features are most important to mimic in the designs of robotic hands. Such a model will also help clinicians better plan reconstructive hand surgeries.

We describe our publicly available grasping simulator and review experiments performed with it. The paper demonstrates the usefulness of this system as a tool for grasping research.

The application of robots to industrial problems often requires grasping and manipulation of the work piece. The robot is able to perform a task adequately only when it is assigned proper tooling and adequate methods of grasping and handling work pieces. The design of such a task requires an in‐depth knowledge of several interrelated subjects including: gripper design, force, position, stiffness and compliance control and grasp configurations. In this paper, we review the research finding on these subjects in order to present in a concise manner, which can be easily accessed by the designers of robot task, the information reported by the researchers, and identify based on the review, future research directions in these areas.

The objective is to develop a flexible robot assembly system capable of economically switching between a wide range of product assemblies. Towards this goal, this paper introduces grasping as a principle issue in designing for flexibility in a robot system. The task, sensing, and certainty about actions are the primary factors in grasp decisions and not where to grasp the part. Identifying finger features, which satisfy a broad range of tasks reduces the likelihood of re‐tooling, and improves certainty about part location and relative orientation. Aided by the ability to address a broad range of tasks, design rules are established which assimilate grasps to part design.

The purpose of this paper is to design a multi-sensory anthropomorphic prosthetic hand and a grasping controller that can detect the slip and automatically adjust the grasping force to prevent the slip.

To improve the dexterity, sensing, controllability and practicability of a prosthetic hand, a modular and multi-sensory prosthetic hand was presented. In addition, a slip prevention control based on the tactile feedback was proposed to improve the grasp stability. The proposed controller identifies slippages through detecting the high-frequency vibration signal at the sliding surface in real time and the discrete wavelet transform (DWT) was used to extract the eigenvalues to identify slippages. Once the slip is detected, a direct-feedback method of adjusting the grasp force related with the sliding times was used to prevent it. Furthermore, the stiffness of different objects was estimated and used to improve the grasp force control. The performances of the stiffness estimation, slip detection and slip control are experimentally evaluated.

It was found from the experiment of stiffness estimation that the accuracy rate of identification of the hard metal bottle could reach to 90%, while the accuracy rate of identification of the plastic bottles could reach to 80%. There was a small misjudgment rate in the identification of hard and soft plastic bottles. The stiffness of soft plastic bottles, hard plastic bottles and metal bottles were 0.64 N/mm, 1.36 N/mm and 32.55 N/mm, respectively. The results of slip detection and control show that the proposed prosthetic hand with a slip prevention controller can fast and effectively detect and prevent the slip for different disturbances, which has a certain application prospect.

Due to the small size, low weight, high integration and modularity, the prosthetic hand is easily applied to upper-limb amputees. Meanwhile, the method of the slip prevention control can be used for upper-limb amputees to complete more tasks stably in daily lives.

A multi-sensory anthropomorphic prosthetic hand is designed, and a method of stable grasps control based on slip detection by a tactile sensor on the fingertip is proposed. The method combines the stiffness estimation of the object and the real-time slip detection based on DWT with the design of the proportion differentiation robust controller based on a disturbance observer and the force controller to achieve slip prevention and stable grasps. It is verified effectively by the experiments and is easy to be applied to commercial prostheses.

When designing hardware and algorithms for robotic manipulation and grasping, sensory information is typically needed to control the grasping process. This paper presents an overview of the major grasping and manipulation approaches and the more common hardware used to obtain the necessary sensory information.

This paper presents an overview of tactile sensing in intelligent robotic manipulation. The history, the common issues, and applications are reviewed. Sensor performance is briefly discussed and compared to the human tactile sense. Advantages and disadvantages of the most common sensor approaches are discussed. Some examples are given of sensors that are widely available as of today. Eventually, some examples of the state‐of‐the‐art in tactile sensing application are presented.

Although many sensor technologies and strong theoretical models have been developed, there is still much left to be done in intelligent grasping and manipulation. This is partly due to the youth of the field and the complex nature of safe control in uncertain environments. Even though there are impressive results when it comes to specific examples of advanced manipulation, there seems to be room for great improvements of hardware and especially algorithms when it comes to more generic everyday domestic tasks.

This paper presents a review of sensor hardware while also giving a glimpse of the major topics in grasping and manipulation. While better hardware of course is desirable, the major challenges seem to lie in the development and application of grasping and manipulation algorithms.

The purpose of this study is to develop a robotic hand–arm system for on-orbit servicing missions at the Tiangong-2 (TG-2) Space Laboratory.

The hand–arm system is mainly composed of a lightweight arm, a dexterous hand, an electrical cabinet, a global camera, a hand–eye camera and some human–machine interfaces. The 6-DOF lightweight arm and the 15-DOF dexterous hand adopt the modular design philosophy that greatly reduces the design cycle and cost. To reduce the computational burden on the central controller and simplify system maintenance, an electrical system which has a hierarchical structure is introduced.

The prototypical operating experiments completed in TG-2 space laboratory demonstrate the performance of the hand–arm system and lay foundations for the future applications of space manipulators.

The main contributions of this paper are as follows a robotic hand–arm system which can perform on-orbit servicing missions such as grasping the electric drill, screwing the bolt, unscrewing J599 electrical connector has been developed; a variable time step motion plan method is proposed to adjust the trajectories of the lightweight arm to reduce or eliminate the collision force; and a dexterous hand uses the coordinated grasp control based on the object Cartesian stiffness to realize stable grasp. To solve the kinematic mapping from the cyber glove commands to the dexterous hand, a fingertip-position-based method is proposed to acquire precise solutions.