scholarly journals Control and Implementation of 2-DOF Lower Limb Exoskeleton Experiment Platform

2021 ◽  
Vol 34 (1) ◽  
Author(s):  
Zhenlei Chen ◽  
Qing Guo ◽  
Huiyu Xiong ◽  
Dan Jiang ◽  
Yao Yan
Keyword(s):  
Lower Limb ◽  
Degrees Of Freedom ◽  
Position Control ◽  
Interaction Force ◽  
Human Robot Interaction ◽  
Detection Accuracy ◽  
Robot Interaction ◽  
Experiment Platform ◽  
Lower Limb Exoskeleton

AbstractIn this study, a humanoid prototype of 2-DOF (degrees of freedom) lower limb exoskeleton is introduced to evaluate the wearable comfortable effect between person and exoskeleton. To improve the detection accuracy of the human-robot interaction torque, a BPNN (backpropagation neural networks) is proposed to estimate this interaction force and to compensate for the measurement error of the 3D-force/torque sensor. Meanwhile, the backstepping controller is designed to realize the exoskeleton's passive position control, which means that the person passively adapts to the exoskeleton. On the other hand, a variable admittance controller is used to implement the exoskeleton's active follow-up control, which means that the person's motion is motivated by his/her intention and the exoskeleton control tries best to improve the human-robot wearable comfortable performance. To improve the wearable comfortable effect, serval regular gait tasks with different admittance parameters and step frequencies are statistically performed to obtain the optimal admittance control parameters. Finally, the BPNN compensation algorithm and two controllers are verified by the experimental exoskeleton prototype with human-robot cooperative motion.

scholarly journals Human-Robot Interaction with Robust Prediction of Movement Intention Surpasses Manual Control

2020 ◽  
Author(s):  
Sebastijan Veselic ◽  
Claudio Zito ◽  
Dario Farina
Keyword(s):  
Degrees Of Freedom ◽  
Linear Time ◽  
Open Loop ◽  
Human Robot Interaction ◽  
Manual Control ◽  
Reach To Grasp ◽  
Robot Interaction ◽  
Loop Control ◽  
User Awareness ◽  
Improving Accuracy

Designing robotic assistance devices for manipulation tasks is challenging. This work aims at improving accuracy and usability of physical human-robot interaction (pHRI) where a user interacts with a physical robotic device (e.g., a human operated manipulator or exoskeleton) by transmitting signals which need to be interpreted by the machine. Typically these signals are used as an open-loop control, but this approach has several limitations such as low take-up and high cognitive burden for the user. In contrast, a control framework is proposed that can respond robustly and efficiently to intentions of a user by reacting proactively to their commands. The key insight is to include context- and user-awareness in the controller, improving decision making on how to assist the user. Context-awareness is achieved by creating a set of candidate grasp targets and reach-to grasp trajectories in a cluttered scene. User-awareness is implemented as a linear time-variant feedback controller (TV-LQR) over the generated trajectories to facilitate the motion towards the most likely intention of a user. The system also dynamically recovers from incorrect predictions. Experimental results in a virtual environment of two degrees of freedom control show the capability of this approach to outperform manual control. By robustly predicting the user’s intention, the proposed controller allows the subject to achieve superhuman performance in terms of accuracy and thereby usability.

scholarly journals Modelling and Control of a 2-DOF Robot Arm with Elastic Joints for Safe Human-Robot Interaction

2021 ◽  
Vol 8 ◽  
Author(s):  
Hua Minh Tuan ◽  
Filippo Sanfilippo ◽  
Nguyen Vinh Hao
Keyword(s):  
Control Algorithm ◽  
Position Control ◽  
Low Cost ◽  
Dynamic Environment ◽  
Human Robot Interaction ◽  
Robot Arm ◽  
Control Loop ◽  
Robot Interaction ◽  
Elastic Joint ◽  
Elastic Joints

Collaborative robots (or cobots) are robots that can safely work together or interact with humans in a common space. They gradually become noticeable nowadays. Compliant actuators are very relevant for the design of cobots. This type of actuation scheme mitigates the damage caused by unexpected collision. Therefore, elastic joints are considered to outperform rigid joints when operating in a dynamic environment. However, most of the available elastic robots are relatively costly or difficult to construct. To give researchers a solution that is inexpensive, easily customisable, and fast to fabricate, a newly-designed low-cost, and open-source design of an elastic joint is presented in this work. Based on the newly design elastic joint, a highly-compliant multi-purpose 2-DOF robot arm for safe human-robot interaction is also introduced. The mechanical design of the robot and a position control algorithm are presented. The mechanical prototype is 3D-printed. The control algorithm is a two loops control scheme. In particular, the inner control loop is designed as a model reference adaptive controller (MRAC) to deal with uncertainties in the system parameters, while the outer control loop utilises a fuzzy proportional-integral controller to reduce the effect of external disturbances on the load. The control algorithm is first validated in simulation. Then the effectiveness of the controller is also proven by experiments on the mechanical prototype.

scholarly journals HUMANOID LOCOMOTION MANIPULATED USING DYNAMIC FINGER GESTURES

2013 ◽  
pp. 170-173
Author(s):  
HARI KRISHNAN R ◽  
VALLIKANNU A. L
Keyword(s):  
Human Computer Interaction ◽  
Degrees Of Freedom ◽  
Motion Tracking ◽  
Human Robot Interaction ◽  
Robot Interaction ◽  
Hand Motion ◽  
Computer Interaction

The fundamental technologies for Human-Computer Interaction are Hand motion tracking and Gesture Identification. The same technology has been adapted for Human-Robot Interaction. This paper discusses a natural methodology for Human-Robot Interaction. In the proposed system, the accelerometers at the fingers, tracks specific gestures. These gestures are identified by the controller, which in turn controls the actuators that results in Humanoid walking. The Humanoid under consideration has 8 Degrees of Freedom.

scholarly journals Multi-connection load compensation and load information calculation for an upper-limb exoskeleton based on a six-axis force/torque sensor

2019 ◽  
Vol 16 (4) ◽  
pp. 172988141986318 ◽  
Author(s):  
Xin Wang ◽  
Qiuzhi Song ◽  
Shitong Zhou ◽  
Jing Tang ◽  
Kezhong Chen ◽  
...  
Keyword(s):  
Upper Limb ◽  
Interaction Force ◽  
Center Of Gravity ◽  
Human Robot Interaction ◽  
Whole Body ◽  
Torque Sensor ◽  
Robot Interaction ◽  
End Effector ◽  
Load Compensation ◽  
Upper Limb Exoskeleton

In this article, a method of multi-connection load compensation and load information calculation for an upper-limb exoskeleton is proposed based on a six-axis force/torque sensor installed between the exoskeleton and the end effector. The proposed load compensation method uses a mounted sensor to measure the force and torque between the exoskeleton and load of different connections and adds a compensator to the controller to compensate the component caused by the load in the human–robot interaction force, so that the human–robot interaction force is only used to operate the exoskeleton. Therefore, the operator can manipulate the exoskeleton with the same interaction force to lift loads of different weights with a passive or fixed connection, and the human–robot interaction force is minimized. Moreover, the proposed load information calculation method can calculate the weight of the load and the position of its center of gravity relative to the exoskeleton and end effector accurately, which is necessary for acquiring the upper-limb exoskeleton center of gravity and stability control of whole-body exoskeleton. In order to verify the effectiveness of the proposed method, we performed load handling and operational stability experiments. The experimental results showed that the proposed method realized the expected function.

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