Human Features-Based Variable Admittance Control for Improving HRI and Performance in Power-Assisted Heavy Object Manipulation

2019 ◽  
Author(s):  
S. M. Mizanoor Rahman
Keyword(s):  
Object Manipulation ◽  
Admittance Control ◽  
Heavy Object ◽  
And Performance

scholarly journals Calibrating intuitive and natural human–robot interaction and performance for power-assisted heavy object manipulation using cognition-based intelligent admittance control schemes

2018 ◽  
Vol 15 (4) ◽  
pp. 172988141877319 ◽  
Author(s):  
S M Mizanoor Rahman ◽  
Ryojun Ikeura
Keyword(s):  
Predictive Control ◽  
Optimization Algorithm ◽  
Weight Perception ◽  
Robotic System ◽  
Human Robot Interaction ◽  
Admittance Control ◽  
Robot Interaction ◽  
Heavy Object ◽  
Control Scheme ◽  
And Performance

In the first step, a one degree of freedom power assist robotic system is developed for lifting lightweight objects. Dynamics for human–robot co-manipulation is derived that includes human cognition, for example, weight perception. A novel admittance control scheme is derived using the weight perception–based dynamics. Human subjects lift a small-sized, lightweight object with the power assist robotic system. Human–robot interaction and system characteristics are analyzed. A comprehensive scheme is developed to evaluate the human–robot interaction and performance, and a constrained optimization algorithm is developed to determine the optimum human–robot interaction and performance. The results show that the inclusion of weight perception in the control helps achieve optimum human–robot interaction and performance for a set of hard constraints. In the second step, the same optimization algorithm and control scheme are used for lifting a heavy object with a multi-degree of freedom power assist robotic system. The results show that the human–robot interaction and performance for lifting the heavy object are not as good as that for lifting the lightweight object. Then, weight perception–based intelligent controls in the forms of model predictive control and vision-based variable admittance control are applied for lifting the heavy object. The results show that the intelligent controls enhance human–robot interaction and performance, help achieve optimum human–robot interaction and performance for a set of soft constraints, and produce similar human–robot interaction and performance as obtained for lifting the lightweight object. The human–robot interaction and performance for lifting the heavy object with power assist are treated as intuitive and natural because these are calibrated with those for lifting the lightweight object. The results also show that the variable admittance control outperforms the model predictive control. We also propose a method to adjust the variable admittance control for three degrees of freedom translational manipulation of heavy objects based on human intent recognition. The results are useful for developing controls of human friendly, high performance power assist robotic systems for heavy object manipulation in industries.

NAO Robots Collaboration for Object Manipulation

2013 ◽  
Vol 332 ◽  
pp. 218-223 ◽  
Author(s):  
Alina Ninett Panfir ◽  
Răzvan Boboc ◽  
Gheorghe Leonte Mogan
Keyword(s):  
Object Manipulation ◽  
Humanoid Robots ◽  
New Method ◽  
Successful Implementation ◽  
Manufacturing Environment ◽  
Complex Operation ◽  
And Performance ◽  
The Impact ◽  
Specific Scenario

This paper proposes a new method of collaboration within a team of twoindividual NAO robots that should execute together a complex operation. The Naorobots are developed so as not only to act individually, but also to cooperatewith other robots if they cannot accomplish the operation alone. This paperpresents a case study demonstrating the integration of the humanoid roboticsplatform Nao within a cooperation application. This specific scenario ofinterest takes place in a small simulated manufacturing environment; while thetask being the storage of a big object, with different shape and weight. Thisscenario is used to observe the impact and performance that this particularteam of humanoid robots has in an industrial environment.Finally we present the successful implementation of robot – robot cooperationcapabilities inspired by human behaviour.

On the capability of wheeled mobile robots for heavy object manipulation considering dynamic stability constraints

2017 ◽  
Vol 41 (2) ◽  
pp. 101-123 ◽  
Author(s):  
Khalil Alipour ◽  
Parisa Daemi ◽  
Arman Hassanpour ◽  
Bahram Tarvirdizadeh
Keyword(s):  
Mobile Robots ◽  
Dynamic Stability ◽  
Object Manipulation ◽  
Wheeled Mobile Robots ◽  
Heavy Object

scholarly journals Walking Strategies and Performance Evaluation for Human-Exoskeleton Systems under Admittance Control

Sensors ◽  
2020 ◽  
Vol 20 (15) ◽  
pp. 4346 ◽  
Author(s):  
Chiawei Liang ◽  
Tesheng Hsiao
Keyword(s):  
Performance Evaluation ◽  
Energy Consumption ◽  
Reaction Force ◽  
Sufficient Conditions ◽  
Estimation Algorithm ◽  
Walking Distance ◽  
Control Law ◽  
Admittance Control ◽  
Communication Module ◽  
And Performance

Lower-limb exoskeletons as walking assistive devices have been intensively investigated in recent decades. In these studies, intention detection and performance evaluation are important topics. In our previous studies, we proposed a disturbance observer (DOB)-based torque estimation algorithm and an admittance control law to shape the admittance of the human-exoskeleton system (HES) and comply with the user’s walking intention. These algorithms have been experimentally verified under the condition of no ground reaction force (GRF) in our previous studies. In this paper, we devised and integrated with the exoskeleton control system a sensing and communication module on each foot to measure and compensate for GRF. Rigorous theoretical analysis was performed and the sufficient conditions for the robust stability of the closed-loop system were derived. Then, we conducted level ground assistive walking repeatedly with different test subjects and exhaustive combinations of admittance parameters. In addition, we proposed two tractable and physically insightful performance indices called normalized energy consumption index (NECI) and walking distance in a fixed period of time to quantitatively evaluate the performance for different admittance parameters. We also compared the energy consumption for users walking with and without the exoskeleton. The results show that the proposed admittance control law reduces the energy consumption of the user during level ground walking.

scholarly journals Admittance control for physical human–robot interaction

2018 ◽  
Vol 37 (11) ◽  
pp. 1421-1444 ◽  
Author(s):  
Arvid QL Keemink ◽  
Herman van der Kooij ◽  
Arno HA Stienen
Keyword(s):  
High Performance ◽  
Controller Design ◽  
Design Guidelines ◽  
Human Robot Interaction ◽  
Physical Interaction ◽  
Admittance Control ◽  
Interaction Control ◽  
Force Signal ◽  
And Performance ◽  
The Stability

This paper presents an overview of admittance control as a method of physical interaction control between machines and humans. We present an admittance controller framework and elaborate control scheme that can be used for controller design and development. Within this framework, we analyze the influence of feed-forward control, post-sensor inertia compensation, force signal filtering, additional phase lead on the motion reference, internal robot flexibility, which also relates to series elastic control, motion loop bandwidth, and the addition of virtual damping on the stability, passivity, and performance of minimal inertia rendering admittance control. We present seven design guidelines for achieving high-performance admittance controlled devices that can render low inertia, while aspiring coupled stability and proper disturbance rejection.

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