Sensorless External Force Detection Method for Robot Arm Based on Error Compensation Using BP Neural Network

In order to improve the safety performance of the robot, this paper proposes an external force detection method for humanoid robot arm without using joint torque sensors, which can detect the external force of the joint space in real time during the operation of the robot. First, Analyses on the structure of the humanoid robot arm is performed, and the model of robot external force detection is established based on robot dynamics and motor dynamics. Then, the error of detection model is analyzed, and the robot dynamic model error is compensated by using the BP network, in order to obtain more accurate external force detection value of the robot. Experiments show that the method can effectively improve the detection accuracy, and the obtained external force detection data can be applied not only to the collision detection in the static state of the robot, but also to the online collision detection when the robot is running, which can ensure the safe operation of the robot.

The robot's arm used to be limited to manipulation by the industrial manipulator, and most studies on the humanoid robot focus on robots' walking methodologies. Since the multi-DOF (degree of freedom) system, like the humanoid robot's arm, has a high- dimension configuration space that cannot appear geometrically and that has many kinematics and dynamics constraints, the path planning of the system requires much computation and, as such, is very complicated. In this paper, the path planning algorithm was employed for the humanoid robot's (Maru-1) arms. The RRT (rapidly exploring random tree) algorithm, which has been proven to be an efficient approach to multi-arm motion plans, was selected for use in this study. The employed algorithm, with inverse-kinematics analysis, was evaluated in this study using 3D graphic simulation.

In industry 4.0, to increase flexibility of a robotic arm system, high-DOFs (degrees of freedom) robotic arm system is used for different applications. A traditional way of dealing with high-DOFs configuration control is to utilize kinesthetic teaching in Cartesian space by guiding the robot’s end-effector to targets. Usually, the teaching process takes a long time, and the configuration of the robotic arm makes them only workable for specific application needs. This research presents a novel mechanical design of 7-DOFs humanoid robotic arm and an algorithm to generate human-like motions for the anthropometric robotic arm to solve the problem. Because the humanoid robotic arm exists one redundant DOF, in this paper, this extra DOF is utilized to optimize the human-like motion in performing tasks with minimum angle variance, adjusting force transmission with manipulability ellipsoids, and avoiding obstacles in the environment. Finally, a 7-DOFs humanoid robotic arm is designed and used in a task which is typically performed by bartenders, namely, pouring wine into the glass.

With the increasing demand for high-precision dynamic interaction tasks in industrial automation, the 7 DDF robotic arm faces the dual challenges of insufficient kinematic modeling accuracy and inadequate end-effector force compliance in complex interaction tasks. This paper focuses on the Realman RM75 seven-degree-of-freedom robotic arm as the subject of study, enhancing its kinematic modeling through an Modified Denavit-Hartenberg (D-H) parameterization method and arm shape angle parameterization technique. Furthermore, it achieves force-compliant control of the robotic arm based on an admittance control strategy. First, a kinematic model of the robotic arm is developed using a Modified D-H parameter approach combined with an arm angle parameterization method to derive a closed-form solution for inverse kinematics. Second, an admittance control framework is designed to adjust the end-effector pose in real time via a virtual spring-damping system, facilitating compliant control in multi-dimensional force interaction scenarios. The experimental results demonstrate the designed control system can achieve good force compliance control at the end of the robotic arm under the action of external contact forces.

In human-robot collaboration, physical hand-over-hand communication of the human operator’s intention is essential for realizing direct and intuitive cooperation. When an external force acts on a robot hand holding an object, the torque exerted on the finger motor becomes a combination of the grasping torque required to maintain the grasping pose and reaction torque to the external force. To analyze intended interaction, we need to recognize multiple contacts inside and outside the fingertips. In this study, an external force estimation method was developed that uses tactile sensors to measure both grasping and external forces acting on the fingertips of a robot hand. Because a tactile sensor cannot measure all the external force components, it is impossible to directly compute the magnitude and contact angle of an external force. The shear and frictional forces lost during tactile sensing are backwardly estimated according to the difference between the estimated and measured torques. The magnitude and contact angle are computed to estimate external force, which can be used to determine the intention of the user. Simulations based on real sensor responses and experiments were performed to validate the proposed estimation method.

The humanoid robotic arm has a broad prospect in the field of human-machine cooperation, but the large inertia of the current joint robotic arm slows down its response speed and running speed. In this study, a centrally driven humanoid robotic arm is introduced, which has the characteristics of small inertia, good rapidity, and high load. Screw Theory is used to establish the kinematic model and analyze that the robotic arm has no singular configuration in the working range. The geometric method and Monte Carlo method are used to analyze and verify its workspace, which is the basis for the subsequent dynamic analysis and control of the robotic arm.

Recent advancements in sensing technology have led to developments of lighter and smaller control systems for prosthetic and biomedical applications. In this paper, we develop a bio-inspired sensory system for a master-slave force-sensing robotic hand which allow accurate control and provide a natural sense of touch to humanoid robotic hand based on force information derived from a smart glove equipped. The slave robotic hand is fabricated using three-dimensional (3D) printing technology, with servo motors to actuate the hand components. A glove with miniaturised flexible sensors attached serves as the master robotic hand, providing movement and force signals for the slave to emulate. The signals from the force sensors are used to moderate the movement of the slave hand’s fingers, so allowing delicate objects to be handled without the risk of breakage. We show that this is a practical and versatile method to improve robotic handling, and that with careful selection and tuning, it is possible to track the master hand’s applied force to within 0.1 Newtons. The success of this approach will pave the way for the development of novel control systems using low-cost bio-inspired strain and force sensors for prosthetics applications.

The legged locomotion manipulation system (LMS) combines the powerful movement of the legged platform and the operation ability of the robotic manipulation arm, which can replace humans to perform dangerous tasks. This paper focuses on the legged locomotion manipulation system, composed of a quadruped locomotion platform with a six-degree-of-freedom (Dof) robotic arm. After the LMS completes movement tasks and reaches the designated position, the supporting foot point are not moved. The overall kinematics model is established with the parallel kinematics model of the legged LMS and the serial kinematics model of the robotic arm. In whole-body collaborative planning, the goal is to minimize the sum of the squares of all joint torques. With the constraints of whole-body kinematics and statics, dynamics, and stability, the trajectory optimization problem is converted into a nonlinear planning problem. By solving the nonlinear problem, we can get the optimal joint trajectory. Compared with independently planning trajectories of the quadruped locomotion platform and robotic arm, this algorithm can coordinate the motion of the whole joints, optimize the distribution, and reduce the system's power. Simulation experiments verify all algorithms.

Designing a humanoid robot is a complex issue and the exact resemblance of human arm movements has not been achieved in many of the previously developed robots. This paper is going to be much focused on the design of a humanoid robot arm which has a unique approach which has never been developed earlier. Even though all the robots that have been developed using 6-Degrees of Freedom (DOF) and 7-DOF can reach any point in the space, some of the orientation cannot be reached by the end effector plane effectively. So an 8-DOF freedom based robotic arm has been specially designed and developed to resemble the exact movements of the human being. This robot has 3-DOF for shoulder joint, 2-DOF for the elbow joint, and 3-DOF for the wrist with fingers as the end effector. Almost all the robots have only 1-DOF to the elbow joint but here 2-DOF has been proposed to resemble the exact movements of the human being (2-DOF at elbow) to solve the above mentioned problem. Literature reviews and design model are discussed in detail to support the proposal that has been made. Forward and inverse Kinematic relationships are also obtained for the joint link parameter. This humanoid robot arm which has been designed and developed is one of the modules of a human size humanoid robot RALA (Robot based on Autonomous Learning Algorithm).

Based on aging Japanese society, there has been a strong desire for development of rehabilitation devices that patients can use at home. The purpose of this study is to develop a home-based compact, lightweight, flexible, and safe rehabilitation device. In this study, a flexible robot arm for wrist rehabilitation that can be used, while patients hold the top of the robot arm, is proposed and tested. The proposed robot arm consists of three extension type flexible pneumatic actuators (EFPAs) restrained by 22 PET sheets. To achieve suitable bending stiffness of the robot arm, three EFPAs are restrained so as to form a tetrahedral shape. The robot arm can bend toward each radial direction. In this paper, the construction and operational principles of the tested robot arm are described. Additionally, the analytical model of the robot arm for attitude control is also described. In addition, the tracking control using the robot arm for the desired orbit is performed. As a result, the tested robot arm can trace the desired orbit based on the model. It is confirmed that the robot arm has the possibility for application as a wrist rehabilitation device for patients.

With the aging of the population and the increase in the employment cost of the elderly service industry, the elderly service robot has become an important development field. However, the working environment of the service robot is complex, and the robot arm may collide with the environmental obstacles, which will cause damage not only to the obstacles but also to the robot arm and even the served object. In this paper, an improved rapidly exploring random tree algorithm is proposed for path planning of humanoid robotic arm. First, the threshold of random probability sampling is set as the selection criterion of the extension mode. Then the random sampling value and the probability sampling threshold are compared, and the target point is determined as a random point if the random sampling value is within the set threshold value. Otherwise, the new node will be expanded under the joint action of the target gravity and the random point gravity. This is the extension of classification based on random probability. Finally, the breadth-first search is used to smooth the initial exploration path. The simulation results show that the proposed method can effectively reduce the path planning time and path length.

Construction and evaluation of the two different strategies of force-free control of industrial type robot arm is presented in this paper. First, robot arm dynamic model for two link model and basic structure of force-free control method are described. Then two different force-free control architectures are illustrated. Two different force-free control strategies are force-free control by dynamic external torque and force-free control by dynamic torque independent compensation, respectively. Analysis of the each type of force-free control strategy is carried out for the single link and two links perspectives of industrial robot arm configurations by means of simulations under Matlab/Simulink environment. The model characteristics of the force-free control are exploited to discuss the application scenarios. Moreover, analysis of the force-free control is carried out by using real robot parameters throughout the simulations. Since the force-free control deals with external forces applied on the robot arm, it can be used to illustrate the interactive force control between a human and a robot arm by passive motion over an external force.

This paper analyses the torque characteristics of the shoulder and elbow joints of an assistive robotic arm for handling an object. In order to investigate those torque characteristics, we consider a model of a humanoid robot arm and simulate typical object lifting and transferring tasks by using the robot arm. Several simulations will show that the available torque patterns and ranges of the shoulder and elbow joints required for the load effect of an object can be identified earlier in the design process of a robotic arm. As a result, this study is helpful for us to determine effectively the specifications of any actuators employed in the shoulder and elbow joints of various humanoid and robotic arms. It is also valuable for a rehabilitation doctor to determine an adequate exercise prescription for an arm rehabilitation using a load.

According to the high real-time and the high anti-interference which required by the machanical arms of humanoid robot, a distributed controllers for mechanical arms of humanoid robot system based on CAN is developed, to which C8051F041 micro controller is applied as the joint controllers. The circuits of incremental discs and speed detection as well as their applications are designed. The achievement of develop and design on distributed controllers for six degrees of freedom mechanical arms fulfills the trajectory requirement of humanoid robot qualification and the system according to the study design.

Hemiplegics have difficulty conducting various daily tasks because they must perform such tasks using only their unaffected arm. If a robot arm that can replace their missing upper-limb function is made available, it will greatly contribute to an improvement in their lives. To realize such a robot arm, cooperative actions of the robot arm and the unaffected arm are important. The purpose of this research is to develop a "cybernic robot arm" that can provide work support through cooperation with the unaffected arm for realization of upper-limb tasks in the daily life of hemiplegics. The developed system can detect the external force applied to a gripped object using a tactile force sensor embedded in the robot fingers. The system estimates the motion of the unaffected arm and the user's intention regarding its operation based on the external force, and provides a support action in cooperation with the unaffected arm based on the estimated information. In addition, to confirm the applicability of the developed system, we developed a support function for opening tasks that are difficult for hemiplegics to carry out on their own, and conducted an experiment confirming the applicability of the system. The results confirm that the proposed system provides proper support by cooperating with the user's arm, allowing an opening task to be performed. The developed system will support various upper-limb tasks that are difficult for hemiplegics.