Design and modeling for a kind of humanoid dexterous hand with elastic palm

With dexterous hands, robots can improve the work scope and work ability significantly. As palms of the existing multi-hand robots are made of steel plates that have small contact area, the robots cannot grab firmly. In this study, a new five-fingered dexterous robot hand is developed. Having flexible palm with 17 degree of freedoms （ DOFs）, the hand can grasp more stably and firm- ly. First, the forward kinematics and inverse kinematics of the fingers and the hand are calculated. Then, the connection between the force exerting on the end effectors and the torque exerting on the joint is set up, laying the foundation for the following control. Finally, through the analysis and sim- ulation of the position, velocity and acceleration, the trajectory planning has a better performance.

MANIPULATION KINEMATICS ON DEXTEROUS HANDS CONSIDERING PURE ROLLING CONTACTS AS PASSIVE JOINTS

The manipulation and constraint equations are established by considering the pure rolling motion in a dexterous hand as two passive joints. According to mapping relation among the motion of the system, the differential kinematics and mobility are studied. The minimal structure for realizing the task motion of the object is obtained, and the conditions for dexterous manipulation are presented. Finally, some rolling manipulations are used as examples to demonstrate the applicability of approach proposed.

Design and fabrication of a gecko-inspired surface for improving the grasping ability of a humanoid dexterous hand

Many studies have examined the design,fabrication and characteristics of gecko-inspired adhesives,but applied research on gecko-inspired surfaces in humanoid dexterous hands is relatively scarce.Here,a wedged slanted structure with a curved substrate suitable for humanoid dexterous fingers was designed and manufactured via ultraprecision machining and replica molding.The adhesion and friction properties of the wedged slanted structure show obvious anisotropic characteristics in the gripping and releasing directions,and the influence of structural parameters and motion parameters on the adhesion and friction was systematically studied.The humanoid dexterous fingers with gecko-inspired surfaces greatly increased the grasping force limit(increase to 4.02 times)based on the grasping of measuring cups with different volumes of water and improved the grasping stability based on the picking up of smooth steel balls of different diameters.This study shows that this process,based on ultraprecision machining and replica molding,is a green,high-efficiency,and low-cost method to fabricate large-area biomimetic surfaces that has potential applications in dexterous humanoid hands to improve grasping ability,stability and adaptability.

An Adaptive Hand Exoskeleton for Teleoperation System

Teleoperation can assist people to complete various complex tasks in inaccessible or high-risk environments,in which a wearable hand exoskeleton is one of the key devices.Adequate adaptability would be available to enable the master hand exoskeleton to capture the motion of human fingers and reproduce the contact force between the slave hand and its object.This paper presents a novel finger exoskeleton based on the cascading four-link closed-loop kinematic chain.Each finger has an independent closed-loop kinematic chain,and the angle sensors are used to obtain the finger motion including the flexion/extension and the adduction/abduction.The cable tension is changed by the servo motor to transmit the contact force to the fingers in real time.Based on the finger exoskeleton,an adaptive hand exoskeleton is consequently developed.In addition,the hand exoskeleton is tested in a master-slave system.The experiment results show that the adaptive hand exoskeleton can be worn without any mechanical constraints,and the slave hand can follow the motions of each human finger.The accuracy and the real-time capability of the force reproduction are validated.The proposed adaptive hand exoskeleton can be employed as the master hand to remotely control the humanoid five-fingered dexterous slave hand,thus,enabling the teleoperation system to complete complex dexterous manipulation tasks.

DESIGN OF A NOVEL DEXTEROUS ROBOT HAND

In the robotic community more and more hands are developed. Based on theexperience of HIT Hand and DLR Hand II, a smaller and easier manufactured dexterous robot hand withmultisen-sory function and high integration is jointly developed. The prototype of the hand issuccessfully built. It has 4 fingers in total 13-DOFs (degree of freedom). Each finger has 3-DOFsand 4 joints, the last 2 joints are mechanically coupled by means of four-bar linkage mechanism. Italso has an additional DOF to realize motion of the thumb relative to the palm. The fingertip forcecan reach up to 10 N. Full integration of mechanical body, actuation system, multisensory system andelectronics is a significant feature. DSP based control system is implemented in PCI busarchitecture and the serial communication between the hand and DSP needs only 2 lines.

Cartesian impedance control of dexterous robot hand

Presents a novel compliant motion control for a robot hand using the Cartesian impedance approach based on fingertip force measurements. The fingertip can accurately track desired motion in free space and appear as mechanical impedance in constrained space. In the position based impedance control strategy, any switching mode in contact transition phase is not needed. The impedance parameters can be adjusted in a certain range according to various tasks. In this paper, the analysis of the finger’s kinematics and dynamics is given. Experimental results have shown the effectiveness of this control strategy.

Design and control of integrated pneumatic dexterous robot finger

Based on flexible pneumatic actuator(FPA),bending joint and side-sway joint,a new kind of pneumatic dexterous robot finger was developed.The finger is equipped with one five-component force sensor and four contactless magnetic rotary encoders.Mechanical parts and FPAs are integrated,which reduces the overall size of the finger.Driven by FPA directly,the joint output torque is more accurate and the friction and vibration can be effectively reduced.An improved adaptive genetic algorithm(IAGA) was adopted to solve the inverse kinematics problem of the redundant finger.The statics of the finger was analyzed and the relation between fingertip force and joint torque was built.Finally,the finger force/position control principle was introduced.Tracking experiments of fingertip force/position were carried out.The experimental results show that the fingertip position tracking error is within ±1 mm and the fingertip force tracking error is within ±0.4 N.It is also concluded from the theoretical and experimental results that the finger can be controlled and it has a good application prospect.

Anthropomorphic Control of a Dexterous Artificial Hand via Task Dependent Temporally Synchronized Synergies

Despite the recent influx of increasingly dexterous prostheses, there remains a lack of sufficiently intuitive control methods to fully utilize this dexterity. As a solution to this problem, a control framework is proposed which allows the control of an arbitrary number of Degrees of Freedom （DOF） through a single electromyogram （EMG） control input. Initially, the joint motions of nine test subjects were recorded while grasping and catching a cylinder. Inherent differences emerged depending upon whether the cylinder was grasped or caught. These data were used to form a distinct synergy for each task, described as the families of parametric functions of time that share a mutual time vector. These two Temporally Synchronized Synergies （TSS） were derived to reflect the task dependent control strategies adopted by the initial participants. These synergies were then mapped to a dexterous artificial hand that was subsequently controlled by two subjects with transradial amputations. The EMG signals from these subjects were used to replace the time vector shared by the synergies, enabling the subjects to perform both tasks with a dexterous artificial hand using only a single EMG input. After a ten minute training period, the subjects learned to use the dexterous artificial hand to grasp and catch the cylinder with 100.0% and 65.0% average success rates, respectively.

The Development of a Two-finger Dexterous Bionic Hand with Three Grasping Patterns-NWAFU Hand

Bionic inspiration from human thumb and index finger was the drive to design a high-performance two-finger dexterous hand.The size of each phalanx and the motion range of each joint in the human thumb and index finger were summarized,and the features of three grasping patterns were described in detail.Subsequently,a two-finger dexterous bionic hand with 6 Degrees of Freedom(DoFs)was developed.Both the mechanical thumb and index finger were made up of three rigid phalanx links and three mechanical rotation joints.Some grasp-release tests validated that the bionic hand can perform three grasping patterns:power grasp,precision pinch and lateral pinch.The grasping success rates were high under the following cases:(1)when power grasping was used to grasp a ring with external diameter 20 mm-140 mm,a cylinder with mass<500 g,or objects with cylinder,sphere or ellipsoid shape;(2)when the precision pinch was used to grasp thin or small objects;(3)when the lateral pinch was used to grasp low length-to-width ratio of objects.The work provided a method for developing two-fimger bionic hand with three grasping patterns,and further revealed the linkage between the difference in fimger structure and size and the hand manipulation dexterity.

Combined Use of FSR Sensor Array and SVM Classifier for Finger Motion Recognition Based on Pressure Distribution Map

For controlling dexterous prosthetic hand with a high number of active Degrees of Freedom （DOF）, it is necessary to reliably extract control volitions of finger motions from the human body. In this study, a large variety of finger motions are discriminated based on the diversities of the pressure distribution produced by the mechanical actions of muscles on the forearm. The pressure distribution patterns corresponding to the motions were measured by sensor array which is composed of 32 Force Sensitive Resistor （FSR） sensors. In order to map the pressure patterns with different finger motions, a multiclass classifier was designed based on the Support Vector Machine （SVM） algorithm. The multi-subject experiments show that it is possible to identify as many as seventeen different finger motions, including individual finger motions and multi-finger grasping motions, with the accuracy above 99% in the in-session validation. Further, the cross-session validation demonstrates that the performance of the proposed method is robust for use if the FSR array is not reset. The results suggest that the proposed method has great application prospects for the control of multi-DOF dexterous hand prosthesis.

Flexible Robotic Grasping Strategy with Constrained Region in Environment

Grasping is a significant yet challenging task for the robots. In this paper, the grasping problem for a class of dexterous robotic hands is investigated based on the novel concept of constrained region in environment, which is inspired by the grasping operations of the human beings. More precisely, constrained region in environment is formed by the environment, which integrates a bio-inspired co-sensing framework. By utilizing the concept of constrained region in environment, the grasping by robots can be effectively accomplished with relatively low-precision sensors. For the grasping of dexterous robotic hands, the attractive region in environment is first established by model primitives in the configuration space to generate offline grasping planning. Then, online dynamic adjustment is implemented by integrating the visual sensory and force sensory information, such that the uncertainty can be further eliminated and certain compliance can be obtained. In the end, an experimental example of BarrettHand is provided to show the effectiveness of our proposed grasping strategy based on constrained region in environment.