ロボットアームの受動関節を利用した人の位置決め補助に関する研究

Robots are used to provide help in unsafe, repetitive and dreary situations. This paper concentrates on a robotic arm which can be utilized for crossing of the dead wire structure to the jumper cable of an electrical transmission line. In order to achieve a good positional accuracy of the end-effector, the robotic arm is modeled and analyzed. Denavit-Hartenberg (DH) representation is used for the kinematic modeling and Lagrangian-Euler (LE) method for the dynamic modeling. Since the kinematic and dynamic modeling of robotic arm is highly nonlinear in nature, the optimum trajectory planning is a challenging issue in almost all obstacle avoidance problems. In trajectory planning, the desired trajectory needs to be followed for end-effector positioning. This paper presents kinematic modeling, dynamic modeling, workspace analysis and trajectory planning of a 5 Degree of freedom (DOF) robotic arm. The robotic arm is designed using SolidWorks 2014 software. The complete analysis of the proposed manipulator is simulated using MATLAB Software.

This paper details a study performed on a new proposed twelve degree-of-freedom dual robot arm, which is very light but capable of handling heavy loads. The proposed robot arm has a higher value for the ratio of the load capacity/robot weight than conventional robot arms, which are actuated by motors with speed reducers, such as a harmonic drives, since it adopts a new type of robot actuator based on a closed chain mechanism. Because of the high value of the ratio of the payload capacity/robot weight, it can be used as a robot arm for mobile robots and for walking robots. Analyses of the design scheme and of the mechanism of the joint actuator used for the robot arm are presented. Also, the control system developed for the robot arm is introduced. The superior characteristics of the new proposed robot arm, handling heavy payloads with light weight links compared to industrial robots, are presented through carrying out various payload capacity tests. Since the robot arm is designed with light links, it has some deflections and these deflections of the links are analyzed using the Finite Element Method (FEM). The results of performance tests are presented to check the correctness of the FEM analysis and to demonstrate the actual capability of handling heavy payloads applied to the robot arm.

This paper is concerned with the identification problem of two degree of freedom robot arm’s joints’ time-varying stiffness under time-varying torque loads. The industrial robot arms can be simplified into series hinged linkage mechanism. The unrestraint dynamic equation of two degrees of freedom robot arm can be obtained by using analytical mechanics method. The model which was established in Pro/E had been imported into ADAMS for simulation. And the simulation consisted of free vibration and forced vibration. Then by choosing limited memory least square method and using the post-processing measured variables, time-varying stiffness could have been identified. Finally, the calculative stiffness was compared to the “real” stiffness which was simulated in ADAMS. The whole process shows that the robot arm’s dynamic model and the method of identification are both effective. DOI: http://dx.doi.org/10.11591/telkomnika.v10i8.1644 Full Text: PDF

To solve the problems of response lag and limited generalization of a single algorithm in traditional control methods for robotic arm trajectory tracking, a hierarchical control architecture is proposed. The upper layer adopts a soft actor critic algorithm optimized by multi actor critics to generate robust trajectories. The lower layer achieves precise tracking through the sparrow search algorithm proportional integral derivative feedforward compensation controller. The results show that the improved soft actor critic algorithm achieves average reward values of 1165 and 1087 in obstacle free scenes, with success rates of 88.65% and 83.54%, respectively, which are superior to other compared algorithms. Meanwhile, the root mean square error of the algorithm in different scenarios is only 0.18 rad/s and 0.24 rad/s, respectively, and the single trajectory time is only 0.68 s and 0.77 s, achieving high-precision and high-efficiency robust trajectory generation. In addition, the sparrow search algorithm proportional integral derivative feedforward compensation controller has the highest degree of joint angle tracking coincidence, and its Z-axis contact force fluctuates around the expected value, with a lower fluctuation range than other methods, ranging from 6.78 N-7.36 N in scenario 1 and 6.52 N-8.13 N in scenario 2. This architecture achieves the synergy of global optimization and precise tracking, suitable for 3-6 axis serial industrial robotic arms, providing important reference for high-precision trajectory tracking of multi degree of freedom robotic arms.

Trajectory optimal control for a robotic arm with a high degree of freedom (DOF) is challenging. The design space for that problem is complex and the search for an optimal solution is demanding. The design of a robotic arm's trajectory is based on solving the inverse kinematics problem, considering additional refinements influenced by factors like total rotating angle, reachability time, minimum execution time, obstacle avoidance, and energy consumption minimization. Due to the complexity of the design space, in this paper, genetic algorithm (GA) optimization and whale optimization algorithm (WOA) have been used to achieve robotic arm trajectory control while maintaining a minimum reachability time. To validate the suggested techniques, a case study was conducted on a 6 DOF KUKA KR 4 R600 robot arm to control subject to its constraints. Sets of consecutive points forming four different paths were inputted to the algorithms. The goal was to reach all these points, in order, with a minimum total reachability time. As a result of this paper, we shown that the whale optimization algorithm provides better performance than the genetic algorithm with a factor of more than 2.5 while satisfying the reachability constraints.

The 4 degree of freedom robot arm of a table tennis robot has a variety of trajectories. In order to improve the response and the success rate of the shots, we used the joint space trajectory planning method to establish a kinematic model with the robot arm joints as variables, and by combining it with the robot arm kinematics, we obtained the relevant parameters for each joint of the robot arm. Simulation tests and physical tests were carried out to obtain a more accurate trajectory of the robot arm.

This paper introduces the isokinetic measurement in randomly applied on the upper arms spasticity patient. Isokinetic is the stroke patient exercise with assist by the medical robotic technologies to therapeutic, diagnostic and laboratory assessment in constant movement. The fatigue of the spasticity patient is ideally vital to understand to make sure the robotic arms is not over drive during exercise. The repetition exercise may cause of medially fatigue. The model propose can predict early fiber muscle action and effect of a range of pulse durations on muscle fatigue. The Spasticity robotic arms was introduced to maximum in medially fatigue can cause damage of the fiber muscle tissue. Flexor Carpi Ulnaris (FCU), Palmanis Longus (PL), Extensor Digitorum (ED) and Extensor Carpi Radials (ECR) is the important muscle body to analyze. The Spasticity Robot Arms (SRA) was design to assists stroke patient in order to understand the capability of user and to provide high impact rehabilitation exercise. The goal of this research is to propose suitable algorithm in order to control multiple degree of freedom (DOF) to achieve a limited number of pre-defined motor synergies. A set of experiments will be conducted on four number of subjects to verify the Fugl Meyer assessment of the proposed algorithm.This paper introduces the isokinetic measurement in randomly applied on the upper arms spasticity patient. Isokinetic is the stroke patient exercise with assist by the medical robotic technologies to therapeutic, diagnostic and laboratory assessment in constant movement. The fatigue of the spasticity patient is ideally vital to understand to make sure the robotic arms is not over drive during exercise. The repetition exercise may cause of medially fatigue. The model propose can predict early fiber muscle action and effect of a range of pulse durations on muscle fatigue. The Spasticity robotic arms was introduced to maximum in medially fatigue can cause damage of the fiber muscle tissue. Flexor Carpi Ulnaris (FCU), Palmanis Longus (PL), Extensor Digitorum (ED) and Extensor Carpi Radials (ECR) is the important muscle body to analyze. The Spasticity Robot Arms (SRA) was design to assists stroke patient in order to understand the capability of user and to provide high impact rehabilitation exercise. The goal ...

In mechanical joints applied to robot arms, one actuator is generally required to drive one joint. For the drive of joints on the musculoskeletal system of animal limbs, in which musculi skeleti are used as actuators, there is a pair of bi-articular muscles for driving two joints simultaneously in addition to a pair of monoarticular muscles. By our study with a simple arm model having a 2 degrees of freedom for two joints, the relationship between the compliances of antagonistic muscless at a joint (the muscle coordinate system) and the elastic ellipse at the end of arm (the task coordinate system) has been clarified in connection with the adjustment of the trajectory at the end of arm, which belongs to the task coordinate system, when the bi-articular muscles are made available and when they are made un-available for comparison. The effect of the bi-articular muscles has thus been proved. Then the fact that the trajectory of the arm can be adjusted by means of both an elastic ellipse and the force at the end of the arm has also been clarified. To verify the above, a 2 degrees of freedom robot arm has been adopted. This arm is equipped with two joints having (3-pairs, 6-muscles) pneumatic rubber artificial muscles used as actuators.

This paper presents a motion coordination of a two-cooperating robot arm when there are unknown system parameters and bounded input disturbances. The order of the model of the two-arm system is reduced. To control this, a force/position control scheme based on an inverse dynamics control scheme is devised. On the top of the control scheme, an adaptive control scheme to take care of parametric uncertainties, and a robust control scheme to compensate coupling forces between two arms and input disturbances are devised. The adaptive and the robust control scheme are derived based on a devised Lyapunov function. The adaptive control algorithm is practical since it does not require the feedback of the second derivative of joint angles and interacting forces. The robust control scheme guarantees that the tracking error of the leader arm and the interacting forces between two arms are confined in a certain region. Numerical examples using dual 3 degree of freedom robot arm are shown.

The aim of this article is the simulation and the control of three degree of freedom robotic arms using brushless DC motors. The two arms are used to maintain the stability of the robot in presence of external disturbances. We used an analytical approach based on the inverse dynamic model to determine the necessary configurations of the arms to stabilize the robot. The control of robotic arm is achieved by IPOS 4808 intelligent servo drives based on the latest DSP technology. We use the (TML) language and C++ to send motions. In this paper we show how to make the links between the PC and the drives also between the drives and the brushless motors. Before starting to send motion commands from the PC, the drive/motor setup using EasySetup was performed. In this paper we use the CAN bus to implement a network between the three IPOS.

To begin the work presents some redundancy resolution schemes for robotic arms, i.e., the techniques for exploiting the redundant degrees of freedom in the solution of the inverse kinematics problem. This is obviously an issue of major relevance for motion planning and control purposes. In particular, task-oriented kinematics and the basic methods for its inversion at the velocity (first-order differential) level are first recalled. This paper focuses on modeling and simulations of the inverse kinematics of an anthropomorphic redundant robotic structure with seven degrees of freedom and a workspace similar to human arm. Also the kinematic model of the robotic arm in the MATLAB and Simulink environment is presented. A method of resolving the redundancy of a seven degrees of freedom robotic arm when a degree of freedom has a known variation is presented. The kinematic analysis and virtual simulation share similar results.

KARES (KAIST Rehabilitation Engineering System) is a rehabilitation robotic system with 6 degrees of freedom robot arm mounted on the powered wheelchair, in order to assist the disabled and the elderly for independent livelihood. Human machine interaction is very important in this system. The direct control of the robot arm takes a high cognitive load on the user's part while physically disabled persons may have difficulties operating joysticks or push buttons for delicate movements. Therefore, a certain degree of autonomy of the robotic system is needed. To perceive the environment, color vision and force/torque sensors are mounted on the end-effector of the robotic arm of KARES. Four basic tasks are tested: picking up a cup from a table, picking up a pen from the floor, moving an object to the user's face, and operating a switch on a wall. These tasks are performed autonomously in the semi-structured environment.

Details of designing and developing a voice guiding system for a robot arm is presented. The features combination technique is investigated and then a hybrid method for classification is applied. Based on research and experimental results, more features will increase the rate of recognition in automatic speech recognition. Thus combining classical components used in ASR system such as Crossing Zero, energy, Mel frequency cepstral coefficients with wavelet transform (to extract meaningful formants parameters) followed by a pipelining ordered classifiers GMM and HMM has contributed in reducing the error rate considerably. To implement the approach on a real-time application, a PC interface was designed to control the movements of a four degree of freedom robot arm by transmitting the orders via RF circuits. The voice command system for the robot is designed and tests showed an Improvement by combining techniques.

This paper proposes a new kinematic structure of a redundant serial robot arm and presents forward and inverse kinematic analysis. This is a new structure developed based on the robot IRB 2400 of ABB. The new structure consists of six revolute joints and two prismatic joints. The proposed robot arm has only seven degrees of freedom because the structure has a constraint between two revolute joints. Two prismatic joints help to expand workspaces of manipulator from small to very large. The paper describes in details about forward and inverse kinematics. Forward kinematics is derived based on DH Convention while inverse kinematics is calculated based on an objective function to minimize motions of a revolute joint and two prismatic joints. The simulation results on Matlab software indicated that the joint positions and velocities of a redundant serial robot arm matched well the trajectories in Cartesian Space.

Generalization ability in tactile sensing for robotic manipulation is a prerequisite to effectively perform tasks in ever-changing environments. In particular, performing dynamic tactile perception is currently beyond the ability of robotic devices. A biomimetic approach to achieve this dexterity is to develop machines combining compliant robotic manipulators with neuroinspired architectures displaying computational adaptation. Here we demonstrate the feasibility of this approach for dynamic touch tasks experimented by integrating our sensing apparatus in a 6 degrees of freedom robotic arm via a soft wrist. We embodied in the system a model of spike-based neuromorphic encoding of tactile stimuli, emulating the discrimination properties of cuneate nucleus neurons based on pathways with differential delay lines. These strategies allowed the system to correctly perform a dynamic touch protocol of edge orientation recognition (ridges from 0 to 40°, with a step of 5°). Crucially, the task was robust to contact noise and was performed with high performance irrespectively of sensing conditions (sensing forces and velocities). These results are a step forward toward the development of robotic arms able to physically interact in real-world environments with tactile sensing.