Robot Wrist Research Articles

Ergonomic design of a wrist robot

Purpose– The purpose of this paper is to propose a method to avoid hyperstaticity and eventually reduce the magnitude of undesired force/torques. The authors also study the influence of hyperstaticity on human motor control during a redundant task.Design/methodology/approach– Increasing the level of transparency of robotic interfaces is critical to haptic investigations and applications. This issue is particularly important to robotic structures that mimic the human counterpart's morphology and attach directly to the limb. Problems arise for complex joints such as the wrist, which cannot be accurately matched with a traditional mechanical joint. In such cases, mechanical differences between human and robotic joint cause hyperstaticity (i.e. over-constrained) which, coupled with kinematic misalignment, leads to uncontrolled force/torque at the joint. This paper focusses on the prono-supination (PS) degree of freedom of the forearm. The overall force and torque in the wrist PS rotation is quantified by means of a wrist robot.Findings– A practical solution to avoid hyperstaticity and reduce the level of undesired force/torque in the wrist is presented. This technique is shown to reduce 75 percent of the force and 68 percent of the torque. It is also shown an over-constrained mechanism could alter human motor strategies.Practical implications– The presented solution could be taken into account in the early phase of design of robots. It could also be applied to modify the fixation points of commercial robots in order to reduce the magnitude of reaction forces and avoid changes in motor strategy during the robotic therapy.Originality/value– In this paper for the first time the authors study the effect of hyperstaticity on both reaction forces and human motor strategies.

Kinematics analysis and numerical simulation of a novel underactuated robot wrist

The kinematics of robot wrist refers to the motion information of a manipulator, such as positions, velocities, and accelerations. It is very crucial for analysing the behaviour of robot wrist using a suitable kinematics model with a result of many valuable contributions. However, current researches always focus on full-actuated robot wrist. The proposed underactuated robot wrist is a novel mechanism with small volume, lightweight, low cost, low energy consumption, and high flexibility, thus designing a robot wrist with fewer actuators than the degrees of freedom becomes an important issue. This article is devoted to kinematics analysis model of a novel underactuated robot wrist. After the novel understated robot wrist was introduced, the inverse kinematics analysis and forward kinematic analysis of the underactuated robot wrist with numerical simulation based on virtual prototyping were discussed in detail. The verification of the forward kinematic analysis and inverse kinematics analysis is used to demonstrate the proposed methodology.

Pneumatic Manipulator Wrist Structure and PLC Control Design

The robot wrist is used to adjust the orientation of the grasped object (ie posture), a rotary motion of the wrist must be met job requirements. Analysis of the degree of freedom of the wrist, the wrist were driving torque calculation, analysis programmable controller selection methods and working process.

Workspace analysis of a novel underactuated robot wrist based on virtual prototyping

The workspace denotes the work area of a robot, which is an important foundation of designing a robot. As formulating the suitable workspace models for a robot wrist is very crucial for analyzing its behavior, many researches have been focused on it in recent decades with a result of many valuable contributions. However, current researches always focus on rigid and full actuated robot wrist, while the robot wrist is always a multibody system, which can affect the accuracy of workspace analysis and simulation. This paper proposed a model of workspace analysis of a novel underactuated robot wrist based on virtual prototyping. After the conceptual design of a novel underactuated mechanism was introduced, the degree of freedom of the underactuated robot wrist was calculated. Then the detailed design of underactuated robot wrist was done. The whole workspace model of the robot system was then established. It was indicated that the working points in the workspace of the robot were distributed compactly and uniformly, which can meet design requirements with high efficiency. The workspace analysis of underactuated robot wrist and the accuracy analysis of underactuated robot wrist were also put forward. The result was testified by the simulation on Matlab, which demonstrated that the methodology is obviously helpful for robot design.

Tracking and replication of hand movements by teleguided intelligent manipulator robot

SUMMARYIn this paper, a new method is presented that allows an intelligent manipulator robotic system to track a human hand from far distance in 3D space and estimate its orientation and position in real time with the goal of ultimately using the algorithm with a robotic spherical wrist system. In this proposed algorithm, several image processing and morphology techniques are used in conjunction with various mathematical formulas to calculate the hand position and orientation. The proposed technique was tested on Remote teleguided virtual Robotic system. Experimental results show that proposed method is a robust technique in terms of the required processing time of estimation of orientation and position of hand.

Myoelectric Control Techniques for a Rehabilitation Robot

This work examines two different types of myoelectric control schemes for the purpose of rehabilitation robot applications. The first is a commonly used technique based on a Gaussian classifier. It is implemented in real time for healthy subjects in addition to a subject with Central Cord Syndrome CCS. The myoelectric control scheme is used to control three degrees of freedom DOF on a robot manipulator which corresponded to the robot's elbow joint, wrist joint, and gripper. The classes of motion controlled include elbow flexion and extension, wrist pronation and supination, hand grasping and releasing, and rest. Healthy subjects were able to achieve 90% accuracy. Single DOF controllers were first tested on the subject with CCS and he achieved 100%, 96%, and 85% accuracy for the elbow, gripper, and wrist controllers respectively. Secondly, he was able to control the three DOF controller at 68% accuracy. The potential applications for this scheme are rehabilitation and teleoperation. To overcome limitations in the pattern recognition based scheme, a second myoelectric control scheme is also presented which is trained using electromyographic EMG data derived from natural reaching motions in the sagittal plane. This second scheme is based on a time delayed neural network TDNN which has the ability to control multiple DOF at once. The controller tracked a subject's elbow and shoulder joints in the sagittal plane. Results showed an average error of 19° for the two joints. This myoelectric control scheme has the potential of being used in the development of exoskeleton and orthotic rehabilitation applications.

Kinematics and Dynamics of an Asymmetrical Parallel Robotic Wrist

This paper introduces an asymmetrical parallel robotic wrist, which can generate a decoupled unlimited-torsion motion and achieve high positioning accuracy. The kinematics, dexterity, and singularities of the manipulator are investigated to visualize the performance contours of the manipulator. Using the method of Lagrange multipliers and considering all the mobile components, the equations of motion of the manipulator are derived to investigate the dynamic characteristics efficiently. The developed dynamic model is numerically illustrated and compared with its simplified formulation to show its computation accuracy.

The Robot Wrist Sensor Dynamic Mode Building Method Based on Genetic Wavelet Neural Networks

A kind of new dynamic modeling method is presented based on improved genetic algorithm (IGA) and wavelet neural networks (WNN) and the principle of algorithm is introduced for a new type robot wrist force sensor. The dynamic model of the wrist force sensor is set up according to data of the dynamic calibration, where the structure and parameters of wavelet neural networks of the dynamic model are optimized by genetic algorithm. The results show that the proposed method can overcome the shortcomings of easy convergence to the local minimum points of BP algorithm, and the network complexity, the convergence and the generalization ability are well compromised and the training speed and precision of model are increased.

Model of Mechatronics Robots Tool with Controlled Geometry

The paper presents a model of tool with controlled geometry of the active surface. This tool is very suitable for use with an industrial robot, for example, to form polystyrene foam. The tool was built in the form of two discs mounted on axes stepper motors positioned in the frame. This discs combined using two wires with feature a length of a wire compensation system. It was made using the spiral spring. Tool geometry was set by rotating one of the discs at a specific angle (0-180o). After starting the both engines, concurrently at the same direction, surface of tool action is obtained in the form of hyperboloid. To run the tool uses stepper motors connected to a computer equipped with an interface card and specially developed control software. Tool joined to the IRb60 robot wrist can obtain curved surface as a superposition of the kinematics of tool and robot wrist.

Measurement System for the Characterization of Micro-Manipulation Motion and Force

Vascular anastomoses are essential microsurgery tasks that demand levels of manual dexterity and precision barely tenable by even the most practiced and skilled surgeons. Teleoperated robotic micromanipulation devices have the potential to improve the availability and proficiency of procedures involving these anastomoses by enabling precise, repeatable motion while filtering out physiological noise that often hampers manual manipulation. In order to be clinically effective and commercially viable, such robotic microsurgery devices must provide significant improvements in the feasible workspace, motion bandwidth, precision, and dexterity achievable with current manual microsurgery procedures [1]. The research presented here constitutes further steps toward the empirical characterization of manual microsurgery motion and interaction forces, and the development of proper microsurgery robot performance requirements based upon that characterization [2]. We design a multimodal measurement device comprised of an electromagnetic (EM) motion tracking system, three-axis accelerometers, and a high resolution force-torque sensor to precisely record both the motions of microsurgical instruments and the forces applied at the tips of those instruments during a set of experimental anastomosis procedures. In addition to providing force data, this research aims to improve upon previous work by increasing motion tracking fidelity using sensor cross validation. The resulting data will be used inform the design of dexterous robotic micromanipulation system components, including tactile sensors, which enable safe tissue handling and suturing on the sub-millimeter scale, robotic wrists, and microgrippers.

Videooptical Surface Shape and Integrity Estimation in Robots Machining

Paper shows system to surface shape and quality control in machining using industrial robot. To surface control videooptical methods were used. Surface shape was controlled using the special reverse engineering system. To surface roughness measure machined surface reflectivity method was used. Used own constructions non contact system was equipped with red laser light and USB camera. Wrist of robot was equipped with grinding tool. In paper shows some algorithms of presented processes. Shown too examples of experiments results in surface roughness measure in start end of grinding process. First trials of presented system shows possibility to build smart machining system for finishing of surface with unknown shape.

Myoelectrically controlled wrist robot for stroke rehabilitation

BackgroundRobot-assisted rehabilitation is an advanced new technology in stroke rehabilitation to provide intensive training. Post-stroke motor recovery depends on active rehabilitation by voluntary participation of patient’s paretic motor system as early as possible in order to promote reorganization of brain. However, voluntary residual motor efforts to the affected limb have not been involved enough in most robot-assisted rehabilitation for patients after stroke. The objective of this study is to evaluate the feasibility of robot-assisted rehabilitation using myoelectric control on upper limb motor recovery.MethodsIn the present study, an exoskeleton-type rehabilitation robotic system was designed to provide voluntarily controlled assisted torque to the affected wrist. Voluntary intention was involved by using the residual surface electromyography (EMG) from flexor carpi radialis(FCR) and extensor carpi radialis (ECR)on the affected limb to control the mechanical assistance provided by the robotic system during wrist flexion and extension in a 20-session training. The system also applied constant resistant torque to the affected wrist during the training. Sixteen subjects after stroke had been recruited for evaluating the tracking performance and therapeutical effects of myoelectrically controlled robotic system.ResultsWith the myoelectrically-controlled assistive torque, stroke survivors could reach a larger range of motion with a significant decrease in the EMG signal from the agonist muscles. The stroke survivors could be trained in the unreached range with their voluntary residual EMG on the paretic side. After 20-session rehabilitation training, there was a non-significant increase in the range of motion and a significant decrease in the root mean square error (RMSE) between the actual wrist angle and target angle. Significant improvements also could be found in muscle strength and clinical scales.ConclusionsThese results indicate that robot-aided therapy with voluntary participation of patient’s paretic motor system using myoelectric control might have positive effect on upper limb motor recovery.

Dynamic Compensation for Two-Axis Robot Wrist Force Sensors

To improve the dynamic characteristic of two-axis force sensors, a dynamic compensation method is proposed. The two-axis force sensor system is assumed to be a first-order system. The operation frequency of the system is expanded by a digital filter with backward difference network. To filter high-frequency noises, a low-pass filter is added after the dynamic compensation network. To avoid overcompensation, parameters of the proposed dynamic compensation method are defined by trial and error. Step response methods are utilized in dynamic calibration experiments. Compared to experiment data without compensation, the response time of the dynamic compensated data is reduced by 30%~40%. Experiments results demonstrate the effectiveness of our method.

A Comparative Analysis of Speed Profile Models for Wrist Pointing Movements

Following two decades of design and clinical research on robot-mediated therapy for the shoulder and elbow, therapeutic robotic devices for other joints are being proposed: several research groups including ours have designed robots for the wrist, either to be used as stand-alone devices or in conjunction with shoulder and elbow devices. However, in contrast with robots for the shoulder and elbow which were able to take advantage of descriptive kinematic models developed in neuroscience for the past 30 years, design of wrist robots controllers cannot rely on similar prior art: wrist movement kinematics has been largely unexplored. This study aimed at examining speed profiles of fast, visually evoked, visually guided, target-directed human wrist pointing movements. One thousand three-hundred ninety-eight (1398) trials were recorded from seven unimpaired subjects who performed center-out flexion/extension and abduction/adduction wrist movements and fitted with 19 models previously proposed for describing reaching speed profiles. A nonlinear, least squares optimization procedure extracted parameters' sets that minimized error between experimental and reconstructed data. Models' performances were compared based on their ability to reconstruct experimental data. Results suggest that the support-bounded lognormal is the best model for speed profiles of fast, wrist pointing movements. Applications include design of control algorithms for therapeutic wrist robots and quantitative metrics of motor recovery.

Physical Human Interactive Guidance: Identifying Grasping Principles From Human-Planned Grasps

We present a novel and simple experimental method called physical human interactive guidance to study human-planned grasping. Instead of studying how the human uses his/her own biological hand or how a human teleoperates a robot hand in a grasping task, the method involves a human interacting physically with a robot arm and hand, carefully moving and guiding the robot into the grasping pose, while the robot's configuration is recorded. Analysis of the grasps from this simple method has produced two interesting results. First, the grasps produced by this method perform better than grasps generated through a state-of-the-art automated grasp planner. Second, this method when combined with a detailed statistical analysis using a variety of grasp measures (physics-based heuristics considered critical for a good grasp) offered insights into how the human grasping method is similar or different from automated grasping synthesis techniques. Specifically, data from the physical human interactive guidance method showed that the human-planned grasping method provides grasps that are similar to grasps from a state-of-the-art automated grasp planner, but differed in one key aspect. The robot wrists were aligned with the object's principal axes in the human-planned grasps (termed low skewness in this paper), while the automated grasps used arbitrary wrist orientation. Preliminary tests show that grasps with low skewness were significantly more robust than grasps with high skewness (77-93%). We conclude with a detailed discussion of how the physical human interactive guidance method relates to existing methods to extract the human principles for physical interaction.

Analysis of the Movable Cotton Robot Palletizer Working Space Based on Graphing Method

the robot working space is the volume which a reference point on its wrist to be reached. It is an important evaluation index of the robot geometry characters. Firstly, the size of the movable cotton robot palletizer structure is calculated by analyzing its movement, then, its working space is calculated base on graphing method. This method is working as these: a referent point P on the wrist is selected, the space of it reaching will be the volume which is the movable cotton robot palletizer working space, by fixing a limiting position at a robot wrist, the reference point P on the total working space XOY is analyzed by drawing, the geometrical analysis and calculation method are used to acquire the motion curve equation, within XOY plane, the movement of the wrist and two slides is decoupling to calculate the limiting position of the robot wrist movement, at the end, the final movement space of the robot is determined.

The effects of electromechanical wrist robot assistive system with neuromuscular electrical stimulation for stroke rehabilitation

An electromyography (EMG)-driven electromechanical robot system integrated with neuromuscular electrical stimulation (NMES) was developed for wrist training after stroke. The performance of the system in assisting wrist flexion/extension tracking was evaluated on five chronic stroke subjects, when the system provided five different schemes with or without NMES and robot assistance. The tracking performances were measured by range of motion (ROM) of the wrist and root mean squared error (RMSE). The performance is better when both NMES and robot assisted in the tracking than those with either NMES or robot only (P<0.05). The muscle co-contractions in the upper limb measured by EMG were reduced when NMES provided assistance (P<0.05). All subjects also attended a 20-session wrist training for evaluating the training effects (3–5times/week). The results showed improvements on the voluntary motor functions in the hand, wrist and elbow functions after the training, as indicated by the clinical scores of Fugl-Meyer Assessment, Action Research Arm Test, Wolf Motor Function Test; and also showed reduced spasticity in the wrist and the elbow as measured by the Modified Ashworth Score of each subject. After the training, the co-contractions were reduced between the flexor carpi radialis and extensor carpi radialis, and between the biceps brachii and triceps brachii. Assistance from the robot helped improve the movement accuracy; and the NMES helped increase the muscle activation for the wrist joint and suppress the excessive muscular activities from the elbow joint. The NMES–robot assisted wrist training could improve the hand, wrist, and elbow functions.

1A2-M05 ヒューマノイドロボットの擬似的多足歩行における静的安定性に関する研究(ヒューマノイド(2))

This paper describes the development of auxiliary mechanism for a humanoid robot. The auxiliary mechanism is shaped like a stick, that connected to the robot's wrist. This robot can be static walking by using the auxiliary mechanism. We are considered the robot can walk more stably by using the auxiliary mechanism. We have to verify the validity of the auxiliary mechanism, we performed a simulation using the ODE (open dynamics engine). We calculated stability margin using the data obtained by the simulation. Finally, We have evaluated the effectiveness of auxiliary mechanism using the stability margin obtained by calculation.

Development and Control of a Pneumatic Robot Arm for Industrial Fields

We developed a pneumatic robot arm driven by pneumatic actuators as a versatile end effector for material handling systems. The arm consists of a pneumatic hand and pneumatic wrist. The hand can grasp various objects without force sensors or feedback control. Therefore, this study aims to control the wrist motions to expand the hand motion's space. The hand mimics the human hand shape and can grasp objects that have different shapes and mechanical characteristics. The wrist has redundant degrees of freedom. This is useful when the robot moves to avoid obstacles. However, the drive mechanism of the wrist has nonlinearity from a mechanical viewpoint. Also, the pneumatic actuators used as the drive source have hysteresis characteristics. These features make the wrist motions difficult to control. Because the wrist is used in material handling systems, its motions need to be freely controlled. Therefore, in this research, experimental models of the drive system of the pneumatic robot wrist have been constructed. With the constructed models, the control systems were designed through simulations. After that, we attempted to control the wrist motions with the constructed controllers. As a result, the wrist models are coincident with wrist motions. Finally, experimental results were obtained that match the simulation results.

1A2-I01 冗長自由度を有した産業用ロボットの把持戦略 : 重力補償を考慮した手首制御(ロボットハンドの機構と把持戦略(2))

In previous research, we have developed the pneumatic robot arm driven by pneumatic actuators as the versatile end effector of a material handling system. The arm consists of the hand and wrist parts. The hand can grasp various objects without force sensors and feedback control. In industrial fields, the wrist must be able to be controlled with the object held. Therefore we aim to control the wrist motions with the object held. We construct the experimental models of the drive system of the pneumatic robot wrist. We design the control systems using simulations with the constructed models. After that, we try to control the wrist motions with constructed controllers. As a result, we can control the wrist motions with constructed PI controllers. The wrist models are coincident with the motions of the wrist accurately. Therefore, we can get the experimental results that meet the simulation conditions.