Multifingered robot hands: Control for grasping and manipulation

This paper presents a tele-control system constructed from a multi-fingered robot hand and operator. The angle of the robot hand is controlled by the angle of the operator’s finger, and the operator feels the environmental force, as detected by the robot hand, constituting so-called bilateral master/slave control.

This paper proposes an intelligent massage control system by using multi-fingered robot hand with hybrid impedance control, which is able to create the movement and the force of robot such as the human's massage. Therefore, the various massage points, such as the change of the stiffness of human skin muscle, can be controlled by using impedance control method. The hybrid impedance control is comprised of the two methods of the position-based and the force-based impedance control were applied. The position-based impedance control is used to control the lateral position of massage on the human skin muscle. On the other hand, the force-based impedance control is used to control the force of the vertical direction on human skin muscle. This paper also gives the identification of human skin muscle through robot perception of impedance to decide the parameter of impedance controller. The control strategy using impedance control to implement an adaptive control system is presented, when human condition is changed with soft and hard skin muscle. Effectiveness of massage control system by using multi- fingered robot hand with hybrid impedance control is demonstrator through actual massage experiments of pushing and rubbing motion.

This paper proposes an intelligent massage control system that uses a multi-fingered robot hand with hybrid impedance control, which is able to recreate the movement and force of a human massage therapist. Therefore, various massage points, such as changes in the stiffness of human skin muscle, can be controlled by using an impedance control method. A hybrid impedance control, comprised of position-based and force-based control methods, was developed. The position-based impedance control is used to control the lateral position of massage on the human skin muscle. On the other hand, the force-based impedance control is used to control the force of the vertical direction on human skin muscle. This paper also identifies human skin muscle through robot perception of impedance to decide on the parameters of the impedance controller. A strategy using impedance control to implement an adaptive control system is presented, under the conditions of both soft and hard skin and muscle. The effectiveness of this massage control system using a multi-fingered robot hand with hybrid impedance control is demonstrated through realistic massage experiments involving pushing and rubbing motions.

This paper presents a tele-control system constructed from a multi-fingered robot hand and operator. The angle of the robot hand is controlled by the angle of the operator's finger, and the operator feels the environmental force, as detected by the robot hand, constituting so-called bilateral master/slave control. In the experiments, the operator grasped the object in spite of Round Trip Time (RTT) as Osec, 0.56sec, using a multi-fingered humanoid robot hand by master/slave control feeling fingertip force. However, with increases in the RTT, the operation became more difficult. We also analyzed the stability of the master site and the slave site by frequency characteristics. The results showed that this system was unstable. However, grasping by tele-control with a communication delay was demonstrated.

Dynamic Modeling and Control of a Multi-Fingered Robot Hand for Grasping Task

Hybrid Impedance Control of Human Skin Muscle by Multi-fingered Robot Hand

One of the greatest challenges of humanoid robotics is to provide a robotic systems with autonomous and dextrous skills. Dextrous manipulation skills, for personal and service robots in unstructured environments, are of fundamental importance, in order to accomplish manipulation tasks in human-like ways and to realize a proper and safe cooperation between humans and robots. The contributions presented in this thesis are aimed at modeling and controlling multifingered robotic hands with soft covers for manipulation tasks. The control issue of a hand-arm robotic system involved in grasping tasks, which can interact with the environment or a human, is also addressed. A port-Hamiltonian model of a multifingered robotic hand, with soft-pads on the finger tips, grasping an object has been developed. The port-Hamiltonian framework is based on the description of systems in terms of energy variables, and their interconnection in terms of power ports. Any physical systems can be described by a set of elements storing kinetic or potential energy, a set of energy dissipating elements, and a set of power ports interconnected by power preserving interconnections. The viscoelastic behavior of the contact is described in terms of energy storage and dissipation. Using the concept of power ports, the dynamics of the hand, the contact, and the object are described. The algebraic constraints of the in- terconnected systems are represented by a geometric object, called Dirac structure. This provides a powerful way to describe the non-contact to contact transition and contact viscoelasticity, by using the concept of energy flows and power preserving interconnections. Using the port based model, an Intrinsically Passive Controller (IPC) is used to control the internal forces and the motion of the object. In grasping tasks, in the case that also interaction with the environment or a human is involved, the control issue of a hand-arm robotic system, is addressed. Thecontrol law adopted for the arm is a compliance object-level control, which aims to reduce the interaction forces. The control action is based on the reconstruction of the external load applied to the object, using the force sensors measurement at the fingertips. Force sensing is also used to compute in real time the desired contact forces, able to guarantee the stability of the grasp. The regulation of the grasping forces is in charge of the hand control. In detail, the contents of the thesis are organized as follows. Chapter 1 provides an introduction on grasping and manipulation applications in the context of advanced robotics where the robot has to operate in unstructured environment. Here the relevance of dexterous manipulation skills in performing many di®erent tasks is emphasized. The framework of the research work in this section is introduced, i.e., the activities in the European project DEXMART. A brief description of the research objectives and the key innovations carried out within the DEXMART project are given. Chapter 2 contains an overview on the relations between the designing features of a robotic hand and its anthropomorphism and dexterity. Then the robotic hand built within the DEXMART project is introduced. A detailed description of the mechanical structure and of the actuation system by means of tendons is provided. Moreover, the kinematics, the statics and the dynamics of the hand are derived. The control structure and the control of the interaction in presence of soft contact is analyzed. Chapter 3 presents a port-Hamiltonian model of a multifingered robotic hand, with soft-pads, while grasping and manipulating an object. An introduction to the port-based formulation is provided. For the validation of the model, a simple example modeled in 20-sim simulation software is considered. Simulation results are presented to validate the model and to show the behavior of the system when an IPC based controller is applied. In Chapter 4 the control issue of a hand-arm robotic system involved in grasping tasks, which can interact with the environment or a human, is addressed. An introduction on the combined control of hand-arm systems is given. The proposed control action is based on the reconstruction of the forces appliedto the object, using the measurement at the fingertips, in order to obtain a compliant behavior of the arm and to reduce the interaction forces. A detailed simulation model of the robotic hand has been developed with the aim of testing the control strategies, using the SimMechanics toolbox of MATLAB. Simulation tests in MATLAB/SimMechanics environment demonstrate the effectiveness of the proposed approach. Chapter 5 contains concluding remarks and proposals for further investigations.

A walking assistance apparatus which can promote gait training for motor palsy patients and outdoor walking for the elderly was developed. Our prototype uses a novel spatial parallel link mechanism and restraint free type of equipment. The apparatus supports complete leg alignment, including the soles of the feet from under the soles with flat steps, and assists walking behavior at the ankle, knee, and hip joints simultaneously without the use of Velcro tape. We proposed the control method according to the purpose of the user. For example, to promote gait training, this apparatus can select the impedance control method. User's legs are assisted along the trajectory with the ideal gait as well as walking. To promote outdoor walking for the elderly, this apparatus can select the torque control method. The apparatus calculates the necessary torques of each joint according to the posture and motion of the apparatus and user. In the case of the impedance control method, by adjusting the natural frequency of the ideal dynamic equation for the flat steps under the soles, the user felt it was easier to walk by frequency entrainment. On the other hand, to promote outdoor walking of the user, this apparatus has to be used not only on the flat ground but also on stairs or slopes with freedom behaviors, and it has to make the user feel comfortable. To address this problem, the torque control method proposed to use real-time acceleration data instead of using the template trajectory. By using this method, the subject could walk on the slope and stairs continuously. Finally, %MVC of the user's EMG while walking equipped with this apparatus was measured, and the influence of the difference using between the impedance and torque control method was confirmed by interviewing the subjects. From the result, the impedance control method assisted the motion of kicking the ground, and the torque control method assisted the motion of raising-up the leg. Therefore, the impedance control method is good for gait training, and the torque control method is good for walk promotion.

A multi-finger robotic hand with an iris mechanism that we previously developed was driven by a single actuator and could grasp an object by wrapping fingers completely around its circumference at multiple points. However, the blades used to grasp objects were within the robotic hand mechanism, so it could only grasp objects small enough to fit within the hollow disk comprising the outer surface of the device body. Furthermore, the hand could not grasp objects smaller than the thickness of the hollow disk. The multi-fingered robotic hand proposed in this study has a new mechanism in which the blades of the iris are placed outside of the hand mechanism, and fingers shaped as equilateral triangular prisms extend perpendicular to the disk of the robotic hand body and are attached to the blade tip. Placing the blade outside the mechanism and adjusting the gear ratios within allows adjustments to the gripping torque and speed. The vertically extended fingers can thus grasp small objects and objects longer than the blade diameter. In this study, we performed geometric and theoretical analyses of the proposed multi-fingered robotic hand. We then fabricated an actual robotic hand, verified the validity of the analyses.

Multi-finger Robotic hands (MFRH) are desired similar to human hands in order to perform stable grasping and fine manipulation of different objects. Their industrial applications including material handling fulfills the requirement of unique end-effector tool empowering specific reach, payloads, and flexibility. The design and control of dexterous and prosthetic robotic hands is of important concern these days. The performance of these hands depends on their mechanical design, prosthetics etc. The mechanical range of movement must be properly controlled and monitored to get the best performance of the robotic hand. In order to obtain the desired outcome from these robotic hands, various design parameters are discussed. The control issues of the multi-finger hand-arm system in order to interact with the human environment are also discussed. The objective of this paper is to evaluate multi-finger robotic hands capable of grasping a large variety of products. An overview of the relations between the designing features for the robotic hand, its anthropomorphism and dexterity is reported. Also, the best known robotic hands developed so far are reviewed emphasizing on their ergonomics and mechanical features. Based on these parameters, a newly designed four fingered tendon actuated robotic hand is discussed along with its mechanical structure.

Thermal modeling of a robotic arm equipped with a multifingered robotic hand (end effector) is considered in this paper. The robotic arm is assumed to move its multifingered hand into and out of a high-temperature medium while gripping an object for a pick and place assembly and heat treatment process. If the rate of heat transfer from robotic hand to robotic arm is small, a lumped-capacitance model can be used to find the transient temperature response of the robotic hand. Different models to approximate the effect of thermal coupling between the robotic hand and robotic arm are discussed. To analyze the effect of heat transfer from robotic hand to robotic arm, transient temperature distribution in one dimension of a rod periodically moving into a hot medium is found numerically. The rod is divided into two parts; the first part simulates the robotic hand and second part simulates the robotic arm. Using different thermal parameters and environmental conditions, transient and quasi-steady state t...

This paper presents a massage motion control system comprised of position control and force control in a multi-fingered robot hand. By making use of an algorithm which converted the desired fingertip trajectory into the desired angle of links in each finger by means of inverse kinematics, the finger position control from the initial position of the multi-fingered robot hand to a target position of the objects for massage was achieved. Its controller was used until the robot hand contacted the objects for massage. After contact was made, the fingertip position control was switched to a force control position needed to apply pressure for the massage. The fingertip forces exerted by an expert human therapist was measured using sheet distribution pressure sensors, and the data obtained was recorded in a computer. After the measurements were taken, the human expert's fingertip force was reproduced by the robot hand. The fingertip force of the robot hand was controlled using feedback obtained with a 6-axis force sensor. To make the force of each fingertip of the four-fingered robot hand track to the fingertip force exerted by the expert human massage therapist, PI servo compensation and a Jacobian matrix were really applied for the human's shoulder. Through simulation and experiments, the usefulness of the proposed control systems was demonstrated.

Various humanoid robots and multi-fingered robot hands are used in research and development. As these robot hands grasp and manipulate an object, the control phase is divided into an “approach phase” and a “manipulation phase.” In the approach phase, a position control method is necessary to control the posture of the robot hand. In the manipulation phase, a force control method is necessary to control the fingertip force of the robot hand. However, it is difficult to control both the force and position of these hands at the same time. In this paper, we propose a grasping force control method based on position control for manipulation. In this proposed method, the finger position is controlled in the direction of the force vector. With this control method, any external force is cancelled and the initial force is kept constant, or the setting force is applied to an object.

Based on inspiration of human grasping activities, a new idea is developed in this paper that grasping forces in a multifingered robotic hand can be regulated and controlled through its compliance by actively coordinating small joint motions in its fingers. According to this idea, a grasping force control model is formulated by means of a compliance model developed by the authors before, and a novel theory is then developed for grasping force control in a multifingered robot hand. The developed theory is expected to lead to a new force control method which could serve as a promising alternative for the active stiffness method. As an application of the developed theory, a two-fingered planar robotic hand is also analyzed, and the simulation results verify the developed theory.

Multifingered hand dexterous manipulation is quite challenging in the domain of robotics. One remaining issue is how to achieve compliant behaviors. In this work, we propose a human-in-the-loop learning-control approach for acquiring compliant grasping and manipulation skills of a multifinger robot hand. This approach takes the depth image of the human hand as input and generates the desired force commands for the robot. The markerless vision-based teleoperation system is used for the task demonstration, and an end-to-end neural network model (i.e., TeachNet) is trained to map the pose of the human hand to the joint angles of the robot hand in real-time. To endow the robot hand with compliant human-like behaviors, an adaptive force control strategy is designed to predict the desired force control commands based on the pose difference between the robot hand and the human hand during the demonstration. The force controller is derived from a computational model of the biomimetic control strategy in human motor learning, which allows adapting the control variables (impedance and feedforward force) online during the execution of the reference joint angles. The simultaneous adaptation of the impedance and feedforward profiles enables the robot to interact with the environment compliantly. Our approach has been verified in both simulation and real-world task scenarios based on a multifingered robot hand, that is, the Shadow Hand, and has shown more reliable performances than the current widely used position control mode for obtaining compliant grasping and manipulation behaviors.