scholarly journals Exoscarne: Assistive Strategies for an Industrial Meat Cutting System Based on Physical Human-Robot Interaction

2021 ◽  
Vol 11 (9) ◽  
pp. 3907
Author(s):  
Harsh Maithani ◽  
Juan Antonio Corrales Ramon ◽  
Laurent Lequievre ◽  
Youcef Mezouar ◽  
Matthieu Alric
Keyword(s):  
Degrees Of Freedom ◽  
Impedance Control ◽  
Human Robot Interaction ◽  
Meat Industry ◽  
Robot Interaction ◽  
Industrial Project ◽  
Intent Prediction ◽  
Amplification Strategy ◽  
Cutting System ◽  
Prediction Strategy

Musculoskeletal disorders of the wrist are common in the meat industry. A proof of concept of a physical human-robot interaction (pHRI)-based assistive strategy for an industrial meat cutting system is demonstrated which can be transferred to an exoskeleton later. We discuss how a robot can assist a human in pHRI, specifically in the context of an industrial project i.e for the meat cutting industry. We developed an impedance control-based system that enables a KUKA LWR robot to provide assistive forces to a professional butcher while simultaneously allowing motion of the knife (tool) in all degrees of freedom. We developed two assistive strategies—a force amplification strategy and an intent prediction strategy—and integrated them into an impedance controller.

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 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.

Impedance control of a cable-driven SEA with mixed H2/H∞ synthesis

2017 ◽  
Vol 37 (3) ◽  
pp. 296-303 ◽  
Author(s):  
Ningbo Yu ◽  
Wulin Zou
Keyword(s):  
Control Strategy ◽  
Control Method ◽  
Impedance Control ◽  
Low Frequency ◽  
Human Robot Interaction ◽  
Control Input ◽  
Robot Interaction ◽  
Content Type ◽  
Series Elastic Actuator ◽  
Series Elastic

Purpose This paper aims to present an impedance control method with mixed H2/H∞ synthesis and relaxed passivity for a cable-driven series elastic actuator to be applied for physical human–robot interaction. Design/methodology/approach To shape the system’s impedance to match a desired dynamic model, the impedance control problem was reformulated into an impedance matching structure. The desired competing performance requirements as well as constraints from the physical system can be characterized with weighting functions for respective signals. Considering the frequency properties of human movements, the passivity constraint for stable human–robot interaction, which is required on the entire frequency spectrum and may bring conservative solutions, has been relaxed in such a way that it only restrains the low frequency band. Thus, impedance control became a mixed H2/H∞ synthesis problem, and a dynamic output feedback controller can be obtained. Findings The proposed impedance control strategy has been tested for various desired impedance with both simulation and experiments on the cable-driven series elastic actuator platform. The actual interaction torque tracked well the desired torque within the desired norm bounds, and the control input was regulated below the motor velocity limit. The closed loop system can guarantee relaxed passivity at low frequency. Both simulation and experimental results have validated the feasibility and efficacy of the proposed method. Originality/value This impedance control strategy with mixed H2/H∞ synthesis and relaxed passivity provides a novel, effective and less conservative method for physical human–robot interaction control.

Intention-Driven Variable Impedance Control for Physical Human-Robot Interaction

2021 ◽  
Author(s):  
Yingxin Huo ◽  
Xiang Li ◽  
Xuan Zhang ◽  
Dong Sun
Keyword(s):  
Impedance Control ◽  
Human Robot Interaction ◽  
Robot Interaction

scholarly journals Human-Robot Interaction and Demonstration Learning Mode Based on Electromyogram Signal and Variable Impedance Control

2018 ◽  
Vol 2018 ◽  
pp. 1-11
Author(s):  
Rui Wu ◽  
He Zhang ◽  
Tao Peng ◽  
Le Fu ◽  
Jie Zhao
Keyword(s):  
Impedance Control ◽  
Gain Scheduling ◽  
Human Robot Interaction ◽  
Physical Interaction ◽  
Learning From Demonstration ◽  
Robot Interaction ◽  
End Effector ◽  
Demonstration Experiment ◽  
2D Space ◽  
Control Interaction

In this research, properties of variable admittance controller and variable impedance controller were simulated by MATLAB firstly, which reflected the good performance of these two controllers under trajectory tracking and physical interaction. Secondly, a new mode of learning from demonstration (LfD) that conforms to human intuitive and has good interaction performances was developed by combining the electromyogram (EMG) signals and variable impedance (admittance) controller in dragging demonstration. In this learning by demonstration mode, demonstrators not only can interact with manipulator intuitively, but also can transmit end-effector trajectories and impedance gain scheduling to the manipulator for learning. A dragging demonstration experiment in 2D space was carried out with such learning mode. Experimental results revealed that the designed human-robot interaction and demonstration mode is conducive to demonstrators to control interaction performance of manipulator directly, which improves accuracy and time efficiency of the demonstration task. Moreover, the trajectory and impedance gain scheduling could be retained for the next learning process in the autonomous compliant operations of manipulator.

Unified Virtual Guides Framework for Path Tracking Tasks

Robotica ◽  
2019 ◽  
Vol 38 (10) ◽  
pp. 1807-1823 ◽  
Author(s):  
Leon Žlajpah ◽  
Tadej Petrič
Keyword(s):  
Control Algorithm ◽  
Degrees Of Freedom ◽  
Path Tracking ◽  
Human Robot Interaction ◽  
Task Space ◽  
Admittance Control ◽  
Unified Framework ◽  
Robot Interaction ◽  
Tracking Tasks ◽  
Selection Of

SUMMARYIn this paper, we propose a novel unified framework for virtual guides. The human–robot interaction is based on a virtual robot, which is controlled by the admittance control. The unified framework combines virtual guides, control of the dynamic behavior, and path tracking. Different virtual guides and active constraints can be realized by using dead-zones in the position part of the admittance controller. The proposed algorithm can act in a changing task space and allows selection of the tasks-space and redundant degrees-of-freedom during the task execution. The admittance control algorithm can be implemented either on a velocity or on acceleration level. The proposed framework has been validated by an experiment on a KUKA LWR robot performing the Buzz-Wire task.

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