Search results

The purpose of this study is to provide a novel multi-fingered hand made of hyperelastic material. This kind of hand has the advantage of less mechanical parts, simpler control system. It can greatly cut down the complexity and cost of the hands under conditions of ensuring enough flexibility of grasping.

Based on the principle of virtual work, the equations of pulling force and grasping force are derived. To get the max grasping force, the optimal structural dimensions of the hand are obtained by finite element simulations. Hand’s grasping experiment is conducted.

The factors influencing grasping force and grasping stability are identified, and they are the length between short poles around the knuckles and the height of short poles. Experimental results show that the max strain of knuckles is less than the elastic limit of hyperelastic material, and the presented hand is practicable. The adaptive ability and grasping stability of the presented hand are demonstrated.

A novel multi-fingered hand made of hyperelastic material is presented in this paper. By designing the thickness of every section of a hyperelastic plate, the knuckle sections will bend and other sections of the plate will remain straight, and thus, the multi-fingered hand will grasp.

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.

The purpose of this paper is to present recent work designing a mechanical robotic hand for self‐adaptive grasping, human‐like appearance, which can be used in a humanoid robot. Conventional robotic devices are relatively complex, large, cumbersome and difficult to be installed in a humanoid robot arm. Under‐actuated robot hands use less motors to drive more rotating joints, thus to simplify the mechanical structure, decrease the volume and weight and finally lower the difficulty of control and the cost.

A novel under‐actuated finger mechanism is designed, which is based on a gear‐rack mechanism, spring constraint and an active sleeve middle phalanx. The principle analyses of its self‐adaptive grasp and end power grasping are given. A new multi‐fingered hand named as TH‐3R Hand is designed based on the finger.

The design finger mechanism can be used in a robotic hand to make the hand obtain more degrees of freedom (DOF) with fewer actuators, and good grasping function of shape adaptation, decrease the requirement of control system. TH‐3R Hand has five fingers, 15 DOF. All fingers are similar. TH‐3R Hand has many advantages: it is simple in structure, light in weight, easy to control and low in cost. TH‐3R Hand can passively adapt different shapes and sizes of the grasped object. Experimental studies have demonstrated the self‐adaptation in grasping of the finger.

The implication of this research is that under‐actuated robotic hands are appropriate for the missions of grasping different objects. The limitation of the research to date is that issues of sensors, control, and communication have not yet been addressed.

Key technologies of the under‐actuated finger and TH‐3R Hand, with self‐adaptive grasping, human‐like appearance and low‐cost lightweight, are feasible. These technologies have the potential to make a significant impact.

These results present a self‐adaptive under‐actuated grasp concept and a humanoid robotic hand with under‐actuated gear‐rack mechanism.

The paper aims to discuss a new design methodology for multi-fingered robotic grippers.

Optimization of the compliant mechanism with underactuation.

A new robotic gripper principle without active control.

Design of multi-fingered robotic gripper as a monolithic structure without joints.

Multi-sensor fusion in robotic dexterous hands is a hot research field. However, there is little research on multi-sensor fusion rules. This study aims to introduce a multi-sensor fusion algorithm using a motor force sensor, film pressure sensor, temperature sensor and angle sensor, which can form a consistent interpretation of grasp stability by sensor fusion without multi-dimensional force/torque sensors.

This algorithm is based on the three-finger force balance theorem, which provides a judgment method for the unknown force direction. Moreover, the Monte Carlo method calculates the grasping ability and judges the grasping stability under a certain confidence interval using probability and statistics. Based on three fingers, the situation of four- and five-fingered dexterous hand has been expanded. Moreover, an experimental platform was built using dexterous hands, and a grasping experiment was conducted to confirm the proposed algorithm. The grasping experiment uses three fingers and five fingers to grasp different objects, use the introduced method to judge the grasping stability and calculate the accuracy of the judgment according to the actual grasping situation.

The multi-sensor fusion algorithms are universal and can perform multi-sensor fusion for multi-finger rigid, flexible and rigid-soft coupled dexterous hands. The three-finger balance theorem and Monte Carlo method can better replace the discrimination method using multi-dimensional force/torque sensors.

A new multi-sensor fusion algorithm is proposed and verified. According to the experiments, the accuracy of grasping judgment is more than 85%, which proves that the method is feasible.

Presents both description and overview of the emerging field of biomechanical grippers and shows the prototype of biomechanical gripper called the Presov biomechanical robot gripper. Biomechanical robots and biomechanical grippers belong under biorobotics and bioengineering systems. Basic components of biorobotics include biomechanisms, biocontrol, biointelligence and biosensors. The Presov Biomechanical Robot Gripper is an electrically‐driven, multi‐fingered dextrous gripper, which has many features that conventional industrial robot grippers do not have. This gripper has been developed in the Department of Industrial Robotics of the Technical University in Presov, Slovak Republic.

This study aims to process multi-agent system with kinds of limitations and constraints, and consider the robot in-hand manipulation as a problem of coordination and cooperation of multi-fingered hand.

A cooperative distributed model predictive control (MPC) algorithm is proposed to perform robot in-hand manipulation.

A cooperative distributed MPC approach is formulated for robot in-hand manipulation problem, which enables address complex limitation and constraint conditions in object motion planning, and realizes tracking trajectory of the object more than tracking position of the object.

This method to implement the moving object task uses the kinematic parameters without the knowledge of dynamic properties of the object. The cooperative distributed MPC scheme is designed to guarantee the movement of the object to a desired position and trajectory at algorithmic level.

The purpose of this paper is to introduce the physical structure and the control mechanism of human motor nervous system to the robotic system in a tentative manner to improve the compliance/flexibility/versatility of the robot.

A brief review is focused on the concept of compliance, the compliance-based methods and the application of some compliance-based devices. Combined with the research on the physical structure and the control mechanism of human motor nervous system, a new drive structure and control method is proposed.

Introducing the physical structure and the control mechanism of human motor nervous system can improve the compliance/flexibility/versatility of the robot, without bringing in more complexity or inefficiency to the system, which helps in the assembly automation tasks.

The proposed drive structure and control method are useful to build up a novel, low-cost robotic assembly automation system, which is easy to interact and cooperate with humans.

Underactuated fingers are adapted to generate several grasping modes for different tasks, and coupled fingers and self-adaptive fingers are two important types of them. Aiming to expand the application and increase adaptability of robotic hand, this paper aims to propose a novel grasping model, called coupled and indirectly self-adaptive (CISA) grasping model, which is the combination of coupled finger and indirectly self-adaptive finger.

CISA grasping process includes two stages: first, coupled and then indirectly self-adaptive grasping; thus, it is not only integrated with the good pinching ability of coupled finger but also characterized with the high flexibility of indirectly self-adaptive finger. Furthermore, a CISA hand with linkage-slider, called CISA-LS hand, is designed based on the CISA grasping model, consisting of 1 palm, 5 CISA-LS fingers and 14 degrees of freedom.

To research the grasping behavior of CISA-LS hand, kinematic analysis, dynamic analysis and force analysis of 2-joint CISA-LS finger are performed. Results of grasping experiments for different objects demonstrate the high reliability and stability of CISA-LS hand.

CISA fingers integrate two grasping modes, coupled grasping and indirectly self-adaptive grasping, into one finger. And a double-linkage-slider mechanism is designed as the switch device.

This paper aims to design a novel jaw gripper with human-sized anthropomorphic features to be suitable for precise in-hand posture transitions, such as twisting and re-positioning. The growing demand from traditional high-mix low-volume and new massive customized manufacturing industry requires the robot with configurability and flexibility. In the electronic manufacturing industry particularly, the design of the robotic hand with sufficient dexterity and configuration is important for the robot to accomplish the assembly task reliably and robustly. It is important for the robot to be able to grasp and manipulate a large number of assembly parts or tools.

In this research, a novel jaw-like gripper with human-sized anthropomorphic features is designed for online in-hand precise positioning and twisting. It retains the simplicity feature of traditional industrial grippers and dexterity features of dexterous robotic hands.

The gripper is able to apply suitable gripping force on assembly parts and performs reliable twisting movement within limited time to meet the industrial requirements. Manipulating several cylindrical assembly parts by robot, as an experimental case in this paper, is studied to evaluate its performance. The effectiveness of proposed gripper design and mechanical analysis is proved by the simulation and experimental results.

The main originality of this research is that a novel jaw gripper with human-sized anthropomorphic features is designed to be suitable for precise in-hand posture transitions, such as twisting and re-positioning. With this gripper, the robotic system will be sufficiently flexible to deal with various assembly tasks.