Search results

The purpose of this paper is to present the design and implementation of a new manipulator with six joints driven by a single DC motor.

The manipulator consists of several modules, each of which has the twisting and pivoting degrees of freedom. Two clutches and one brake are mounted to control each joint. A clutch model based on PWM control is built to compute the average velocity of each clutch. Two parameters are involved in the model: PWM frequency and duty ratio. PWM frequency is limited by the natural frequencies of structure with all postures. The theoretical duty ratio should be adjusted according to the clutch model. Two experiments – line tracking and arc tracking – are carried out to verify the effectiveness of the control system.

The study has designed a manipulator with six joints driven by a single DC motor which powers all the modules through a main shaft and several clutches. In the manipulator, all the modules are supplied with a constant speed input and provide a bi‐directional variable output. Experimental results show the clutch model built for the manipulator can be applied to the joint control of all multi‐joint manipulators.

The paper describes a dexterous and light‐weight manipulator driven by a single motor and designed with bi‐directional joints.

The purpose of this paper is to propose a control algorithm to improve the backdrivability performance of minimally invasive surgical robotic arms, so that precise manual manipulations of robotic arms can be performed in the preoperative operation.

First, the flexible-joint dynamic model of the 3-degree of freedom remote center motion (RCM) mechanisms of minimally invasive surgery (MIS) robot is derived and its dynamic parameters and friction parameters are identified. Next, the angular velocities and angular accelerations of joints are estimated in real time by the designed Kalman filter. Finally, a control algorithm based on Kalman filter is proposed to enhance the backdrivability of RCM mechanisms by compensating for the internally generated gravitational, frictional and inertial resistances experienced during the positioning and orientating.

The parameter identification for RCM mechanisms can be experimentally evaluated from comparison between the measured torques and the reconstructed torques. The accuracy and convergence of the real-time estimation of angular velocity and acceleration of the joint by the designed Kalman filter can be verified from corresponding simulation experiments. Manual adjustment experiments and animal experiments validate the effectiveness of the proposed backdrivability control algorithm.

The backdrivability control algorithm presented in this paper is a universal method to enhance the manual operation performance of robots, which can be used not only in the medical robot preoperative manual manipulation but also in robot haptic interaction, industrial robot direct teaching and active rehabilitation training of rehabilitation robot and so on.

Compared with other backdrivability design methods, the proposed algorithm achieves good backdrivability for RCM mechanisms without using force sensors and accelerometers. In addition, this paper presents a new static friction compensation approach for a joint moving with very low velocity.

The purpose of this paper is to study the dynamic modeling and controller design for the series element actuator (SEA) joints. The robot equipped with SEA joints is a strong coupling, nonlinear, highly flexible system, which can prevent itself from damaging by the accidental impact and the people to be injured by the robot.

Based on the torque source model, the authors built a dynamic model for the SEA joint. To improve the accuracy of this model, the authors designed an elastic element into the joint and implemented the vector control for the joint motor. A control method of combined PD controller and back-stepping was proposed. Moreover, the torque control could be transformed into position control by stiffness transformation.

The established model and the proposed method are verified by the position and torque control experiments. The experimental results show that the dynamic model of the SEA joint is accurate and the proposed control strategies for the SEA joint are reasonable and feasible.

The main contribution of the paper is as follows: designing an elastic element with high linearity to improve the model accuracy of the SEA joint. The control strategy-based back-stepping method for the SEA joint is proposed to increase the robustness of the controller.

This paper aims to deal with the development of a novel lower limb exoskeleton to assist disabled people in stair ascending.

For this purpose, a novel design of a mixture of motors and cables has been proposed for users to wear them easily and show the application of the system in stair climbing.

One of the prominences of this study is the provided robot design where four joints are actuated with only two motors; each motor actuates either the knees or ankles. Another advantage of the designed system is that with motors placed in a backpack, the knee braces can be worn under clothes to be concealed. Finally, the system performance is evaluated using electromyography (EMG) signals showing 28 per cent reduction in energy consumption of related muscles.

This investigation deals with the development of a novel lower limb exoskeleton to assist disabled people in stair ascending.

Manipulators are often subjected to joint flexibility caused by various causes in industrial applications, such as shaft windup, harmonic drives and bearing deformation. However, many industrial robots are only equipped with motor-side encoders because link-side encoders and torque transducers are expensive. Because of joint flexibility and resulted slow response rate, control performance of these manipulators is very limited. Based on this, the purpose of this paper is to use easy-to-install and cheap accelerometers to improve control performance of such manipulators.

First, a novel tip-acceleration feedback method is proposed to avoid amplifications of approximation errors caused by inversion of the Jacobian matrix. Then, a new control scheme, consisting an artificial neural network, a proportional-derivative (PD) controller and a reference model, is proposed to track motor-side position and suppress link-side vibration.

By using the proposed tip-acceleration feedback method, each link’s vibration can be suppressed correlatively. Through the networks, smaller motor-side tracking errors can be obtained and unknown dynamics can be compensated. Tracking and convergence performance of the network-based system can be improved by using the additional PD controller.

The originality is based on using accelerometers to improve link-side vibration suppression and control performance of flexible-joint manipulators. The previously used methods need expensive link-side sensors or accurate robot model, which is unavailable for many industrial robots only equipped with motor-side encoders. The report proposed a novel acceleration feedback method and used networks to solve such problems.

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 purpose of this paper is to present a novel and accurate coordination control method of dual‐arm modular robot based on position feedback using 3D motion measurement system – Optotrak3020. The end‐position accuracy of dual‐arm modular robot can be improved obviously.

By means of Optotrak3020, the actual end‐position of dual‐arm modular robot is acquired and then returned to the robotic controllers, so the corresponding position error compensation is implemented. Through a 3D simulation and experiment of dual‐arm modular robot for tracking a trajectory of plane right triangle, the feasibility and validity of this control strategy are verified.

The coordination control of dual‐arm modular robot based on position feedback can be accomplished by means of Optotrak3020. The dual‐arm modular robot can accurately accomplish the task of positioning or tracking a reference trajectory.

This real‐time position feedback control method with high control accuracy can be implemented on a PowerCube dual‐arm modular robot system. This method also can be applied to other dual‐arm robot systems, such as mobile robot with dual‐arm, humanoid robot.

The coordination control method of dual‐arm modular robot is presented based on end‐position feedback using Optotrak3020 motion measurement system. The platforms of simulation, communication and experiment are developed, respectively.

The purpose of this paper is to introduce a new manipulator structure to configure power‐assist devices in order to protect the operator from suffering musculoskeletal disorders. The mechanical structure and the control system along with their main features are presented.

The new structure was designed under the criterion of minimizing the torques required for handling payloads up to 75 kg as well as to configure a system to be controlled easily.

A new structure based on electrical AC motors and capable of handling high payloads exerting low motor torque is provided.

The paper describes how application of the criterion of minimizing the required torques to handle heavy payload produced a new manipulator structure. This structure is patent protected.

This paper aims to design a neural controller based on radial basis function networks (RBFN) for electrically driven robots subjected to constrained inputs.

It is assumed that the electrical motors have limitations on the applied voltages from the controller. Due to the universal approximation property of RBFN, uncertainties including un-modeled dynamics and external disturbances are represented with this powerful neural network. Then, the lumped uncertainty including the nonlinearities imposed by actuator saturation is introduced and a mathematical model suitable for model-free control is presented. Based on the closed-loop equation, a Lyapunove function is defined and the stability analysis is performed. It is assumed that the electrical motors have limitations on the applied voltages from the controller.

A comparison with a similar controller shows the superiority of the proposed controller in reducing the tracking error. Experimental results on a SCARA manipulator actuated by permanent magnet DC motors have been presented to guarantee its successful practical implementation.

The novelty of this paper in comparison with previous related works is improving the stability analysis by involving the actuator saturation in the design procedure. It is assumed that the electrical motors have limitations on the applied voltages from the controller. Thus, a comprehensive approach is adopted to include the saturated and unsaturated areas, while in previous related works these areas are considered separately. Moreover, a performance evaluation has been carried out to verify satisfactory performance of transient response of the controller.

At present, the majority of industrial robots are not well suited to the specific needs of the food industry. Additionally, the high cost of robotic systems means that it is currently difficult for food manufacturers to financially justify the use of this technology. This paper aims to examine the unique requirements of the food industry with regards to robot manipulator design and outlines the design features of a low‐cost robotic arm developed specifically for use in food production.

Considerations for the design of the robot arm in addition to industrial requirements for hygienic design, low cost, fast pick and place speed, safety for operation alongside human workers and ease of reprogramming are discussed in detail.

A successful manipulator design must consider functional requirements relevant to food production from the very outset of the design process. The principal three requirements are those of ease of cleaning, speed and low cost.

The availability of low‐cost industrial robots specifically designed for food production might encourage a wider adoption of robotics and automation in the food industry and would benefit food manufacturers by reducing production costs and increasing competitiveness in what is becoming an increasingly difficult market.

This paper is of value to engineers and researchers developing robotic manipulators for use in the food industry.