Multifingered Robot Hand Compliant Manipulation Based on Vision-Based Demonstration and Adaptive Force Control.

In this work, we focus on improving the robot's dexterous capability by exploiting visual sensing and adaptive force control. TeachNet, a vision-based teleoperation learning framework, is exploited to map human hand postures to a multi-fingered robot hand. We augment TeachNet, which is originally based on an imprecise kinematic mapping and position-only servoing, with a biomimetic learning-based compliance control algorithm for dexterous manipulation tasks. This compliance controller takes the mapped robotic joint angles from TeachNet as the desired goal, computes the desired joint torques. It 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 angle trajectories. The simultaneous adaptation of the impedance and feedforward profiles enables the robot to interact with the environment in a compliant manner. Our approach has been verified in multiple tasks in physics simulation, i.e., grasping, opening-a-door, turning-a-cap, and touching-a-mouse, and has shown more reliable performances than the existing position control and the fixed-gain-based force control approaches.

In this paper, a method of force control applicable to robotic manipulations for manipulators and grippers is presented, with a consideration of the characteristics of objects based on adaptive control, by demonstrating experiments in a gripper system. This adaptive holding control method of a gripper, also applicable to any type of manipulator, whose control is based on the input-output position control due to the high reduction gear at joints, is shown so that it is possible to take into account the characteristics of objects which are brought about in the closed loop dynamics of force and position control. The gripper can hold objects adaptively with less impact forces against objects than before, hence it does not damage objects, unlike conventional grippers. Thus, the range of applicability of force control can be inceased much more with consideration of the characteristics of objects.

In this paper, a force control method for manipulators is presented with consideration given to object dynamics based on the adaptive control. This method for the manipulator system is an extension of the previously proposed method for gripper systems, with additional consideration given to the mass effect at the tip of the manipulator. Since present industrial robotic manipulators commonly employ the input/output position servo control system, one of the purposes of this study is to use the proposed control system to simultaneously control the position of the manipulator, the forces on the manipulator and the forces against given objects. However, it is not easy to control the manipulator, without knowledge of the objects, because the dynamics of the object inevitably comes into the overall feedback control system. Then, it is necessary to adjust the control gains, depending on handling of the objects. For this purpose, a method of the adaptive force control based on the position, and force hybrid control is presented, with consideration given to the static and dynamic characteristics of objects. Some simulations and experiments are carried out for a one-degree-of-freedom manipulator system to adjust pushing and/or holding forces to various objects, whether they be soft or hard, and they showed wider applicability and more flexible manipulation of the conventional servo controlled manipulators.

A position/force control with completely fuzzified adaptive force control system for the single degree of freedom mechanisms is presented. The proposed force control scheme contains are adaptive fuzzy force controller and a subordinated fuzzy velocity controller. By using a second-order referent model, a model reference-based fuzzy adaptation mechanism is able to keep the error between the model and system output responses within the desired limits. The results obtained by computer simulations indicate a stable performance of the force control system for a wide range of environment stiffness variations. The proposed adaptive force control method is efficient in the case of contact with the rough surface or the complex form workpiece.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

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 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.

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.

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.

This paper addresses the problem of achieving exact dynamic force control with manipulators possessing low-level position and/or velocity controllers typically employed in industrial robot arms. Previously reported approaches and experimental results are reviewed. A new adaptive force control algorithm for velocity/position controlled robot arms in contact with surfaces of unknown linear compliance is reported. The controller provably guarantees global asymptotic convergence of force trajectory tracking errors to zero when the robot is under exact or asymptotically exact inner loop velocity control. An additional result which guarantees arbitrarily small force errors for bounded inner loop velocity tracking errors is presented. Comparative experiments show the new adaptive velocity (position) based controller and its nonadaptive counterpart to provide performance superior to that of previously reported position-based force controllers.

This paper addresses the problem of achieving exact dynamic force control with manipulators possessing the low level position and/or velocity controllers typically employed in industrial robot arms. Previously reported approaches and experimental results are reviewed. A new adaptive force control algorithm for velocity/position controlled robot arms in contact with surfaces of unknown linear compliance is reported. The controller provably guarantees global asymptotic convergence of force trajectory tracking errors to zero when the robot is under exact or asymptotically exact inner loop velocity control. An additional result which guarantees arbitrarily small force errors for bounded inner loop velocity tracking errors is presented. Comparative experiments show the new adaptive velocity (position) based controller and its non-adaptive counterpart to provide performance superior to that of previously reported position based force controllers.

The article presents simple methods for the design of adaptive force and position controllers for robot manipulators within the hybrid control architecture. The force controller is composed of an adaptive PID feedback controller, an auxiliary signal, and a force feedforward term, and achieves tracking of desired force setpoints in the constraint directions. The position controller consists of adaptive feedback and feedforward controllers as well as an auxiliary signal, and accomplishes tracking of desired position trajectories in the free directions. The controllers are capable of compensating for dynamic cross‐couplings that exist between the position and force control loops in the hybrid control architecture. The adaptive controllers do not require knowledge of the complex dynamic model or parameter values of the manipulator or the environment. The proposed control schemes are computationally fast and suitable for implementation in online control with high sampling rates. The methods are applied to a two‐link manipulator for simultaneous force and position control. Simulation results confirm that the adaptive controllers perform remarkably well under different conditions.

Multi-finger robotic hands are the main robotic invention for providing assistive movement therapy in hand rehabilitation. In this paper, the concept of task priority is adopted in order to solve the redundancy resolution of a robotic hand. The redundancy parameter has been used to design the inverse kinematic model in order to determine the joint angles when the finger moves to perform the initial subtask of tracing the desired trajectory while considering the secondary subtask of increasing the instantaneous manipulability. Five different human subjects performed the experimentation where the index finger and thumb are allowed to follow the three desired motion trajectories. Markers are placed on the finger joints in order to track the motion and obtain the finger joint angles. Further, the experimental joint angles are compared with those obtained from inverse kinematics. The index finger and thumb behaviour is analysed based on the redundancy resolution scheme. It has been observed that the optimized root-mean-square error remains insignificant of the different subjects performing the motion and the type of motion trajectories adopted for the index finger as well as the thumb. Thereafter, the proposed scheme is applied to a four-finger tendon-actuated robotic hand and it has been observed that the scheme can be applied to solve the redundancies of any robotic hand.

The authors describe adaptive force control based on a disturbance observer. In the proposed method, the control gains of the force controller are adjusted according to the environment which the manipulator contacts. First, a disturbance observer, which estimates disturbance torque imposed on the manipulator, is applied to each joint. By the feedback of the estimated disturbance torque the total system becomes robust against the disturbance torque. Then, the dynamics including the environment are cleared up, and the workspace force controller is described as a second-order system. Therefore, it becomes easier to apply the adaptive control algorithm to the force controller in the observer-based system. A least-squares method is introduced to estimate the unknown parameters of the environment. Experimental results are presented to verify the proposed adaptive force controller. >

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...

Performing retinal vein cannulation (RVC) as a potential treatment for retinal vein occlusion (RVO) without the assistance of a surgical robotic system is very challenging to do safely. The main limitation is the physiological hand tremor of surgeons. Robot-assisted eye surgery technology may resolve the problems of hand tremors and fatigue and improve the safety and precision of RVC. The Steady-Hand Eye Robot (SHER) is an admittance-based robotic system that can filter out hand tremors and enables ophthalmologists to manipulate a surgical instrument inside the eye cooperatively. However, the admittance-based cooperative control mode does not safely minimize the contact force between the surgical instrument and the sclera to prevent tissue damage. In addition, features such as haptic feedback or hand motion scaling, which can improve the safety and precision of surgery, require a teleoperation control framework. This work presents, for the first time in the field of robot-assisted retinal microsurgery research, a registration-free bimanual adaptive teleoperation (BMAT) control framework using SHER 2.0 and SHER 2.1 robotic systems. Both SHERs are integrated with an adaptive force control (AFC) algorithm that dynamically and automatically minimizes the tool-sclera interaction forces, enforcing them within a safe limit. The scleral forces are measured using two fiber Bragg grating (FBG)-based force-sensing tools. The performance of the proposed BMAT control framework is evaluated by comparison with a bimanual adaptive cooperative (BMAC) framework in a vessel-following experiment conducted under a surgical microscope. Experimental results demonstrate the effectiveness of the BMAT control framework in performing a safe bimanual telemanipulation of the eye without over-stretching it, even in the absence of registration between the two robots.