scholarly journals Stiffness Adjustment for a Single-Link Robot Arm Driven by Series Elastic Actuator in Muscle Training

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 65029-65039 ◽  
Author(s):  
Siqi Li ◽  
Jian Li ◽  
Guihua Tian ◽  
Hongcai Shang
2021 ◽  
pp. 095745652110307
Author(s):  
Kangping Gao ◽  
Xinxin Xu ◽  
Ning Shi ◽  
Shengjie Jiao

In the process of drilling and coring by the rock-breaking rig, the drill rod is affected by the intermittent impact force, which reduces the efficiency of the rig to break the rock and increases the cost of the drilling and coring. Therefore, it is very important to improve the impact resistance of the drill pipe during the rock-breaking process. To achieve this goal, a flexible design of the drill pipe was carried out, and a dynamical model of the drilling rig based on a series elastic actuator was established. Considering the dynamic performance of the system, a torque feedforward link is introduced and a control model based on the force source is established. The influence of the equivalent inertia of the transmission system and the series elastic actuator damping coefficient on the system stability was analyzed by drawing the frequency domain characteristic curve of the system. By using the control and Simulink simulation software, the electromechanical simulation of the model is carried out, and the torque step tracking response of the system is obtained. A torque feedforward link is introduced to establish the control model of the system based on force source. Through dynamic simulation software ADAMS, dynamic and static impact simulation experiments were carried out on the system. The results show that when a force of 200 N is applied to the output end of the drill pipe in the tangential direction, the maximum moments received by the joint under static and dynamic environments are 34.1 N·m and 57.9 N·m, respectively. When the impact force disappears, the time required for the flexible drill pipe to reach a stable state is only 0.15 s, which verifies that the series elastic actuator–based drill pipe model can alleviate the impact of the external environment and protect the internal structure of the rig.


2021 ◽  
pp. 1-33
Author(s):  
Ozan Kaya ◽  
Gokce Burak Taglioglu ◽  
Seniz Ertugrul

Abstract In recent years, robotic applications have been improved for better object manipulation and collaboration with human. With this motivation, the detection of objects has been studied with serial elastic parallel gripper by simple touching in case of no visual data available. A series elastic gripper, capable of detecting geometric properties of objects is designed using only elastic elements and absolute encoders instead of tactile or force/torque sensors. The external force calculation is achieved by employing an estimation algorithm. Different objects are selected for trials for recognition. A Deep Neural Network model is trained by synthetic data extracted from STL file of selected objects . For experimental set-up, the series elastic parallel gripper is mounted on a Staubli RX160 robot arm and objects are placed in pre-determined locations in the workspace. All objects are successfully recognized using the gripper, force estimation and the DNN model. The best DNN model capable of recognizing different objects with the average prediction value ranging from 71% to 98%. Hence the proposed design of gripper and the algorithm achieved the recognition of selected objects without need for additional force/torque or tactile sensors.


Sign in / Sign up

Export Citation Format

Share Document