Physical human-robot interaction estimation based control scheme for a hydraulically actuated exoskeleton designed for power amplification

2018 ◽  
Vol 19 (9) ◽  
pp. 1076-1085 ◽  
Author(s):  
Yi Long ◽  
Zhi-jiang Du ◽  
Wei-dong Wang ◽  
Long He ◽  
Xi-wang Mao ◽  
...  
Keyword(s):  
Human Robot Interaction ◽  
Robot Interaction ◽  
Power Amplification ◽  
Control Scheme ◽  
Hydraulically Actuated

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.

Unified Robot Control Scheme for Cooperative Motion, Autonomous Motion and Contact Reaction

2011 ◽  
Vol 23 (4) ◽  
pp. 557-566 ◽  
Author(s):  
Vincent Duchaine ◽  
◽  
Clément Gosselin ◽  
Keyword(s):  
Robot Control ◽  
Human Robot Interaction ◽  
Future Generations ◽  
Admittance Control ◽  
Robot Interaction ◽  
Modes Of Operation ◽  
Cooperative Motion ◽  
Control Scheme ◽  
Industrial Manipulators ◽  
Autonomous Motion

While the majority of industrial manipulators currently in use only need to performautonomousmotion, future generations of cooperative robots will also have to execute cooperative motion and intelligently react to contacts. These extended behaviours are essential to enable safe and effective physical Human-Robot Interaction (pHRI). However, they will inevitably result in an increase of the controller complexity. This paper presents a single variable admittance control scheme that handles the three modes of operation, thereby minimizing the complexity of the controller. First, the adaptative admittance controller previously proposed by the authors for cooperative motion is recalled. Then, a novel implementation of variable admittance control for the generation of smooth autonomous motion including reaction to collisions anywhere on the robot is presented. Finally, it is shown how the control equations for these three modes of operation can be simply unified into a unique control scheme.

Design and Validation of a Talking Face for the iCub

2015 ◽  
Vol 12 (03) ◽  
pp. 1550026 ◽  
Author(s):  
Alberto Parmiggiani ◽  
Marco Randazzo ◽  
Marco Maggiali ◽  
Giorgio Metta ◽  
Frederic Elisei ◽  
...  
Keyword(s):  
Speech Intelligibility ◽  
Mechanical Design ◽  
Humanoid Robots ◽  
Human Robot Interaction ◽  
Mcgurk Effect ◽  
Elastic Tissue ◽  
Robot Interaction ◽  
Control Scheme ◽  
Recent Developments ◽  
Talking Face

Recent developments in human–robot interaction show how the ability to communicate with people in a natural way is of great importance for artificial agents. The implementation of facial expressions has been found to significantly increase the interaction capabilities of humanoid robots. For speech, displaying a correct articulation with sound is mandatory to avoid audiovisual illusions like the McGurk effect (leading to comprehension errors) as well as to enhance the intelligibility in noisy conditions. This work describes the design, construction and testing of an animatronic talking face developed for the iCub robot. This talking head has an articulated jaw and four independent lip movements actuated by five motors. It is covered by a specially designed elastic tissue cover whose hemlines at the lips are attached to the motors via connecting linkages. The mechanical design and the control scheme have been evaluated by speech intelligibility in noise (SPIN) perceptual tests that demonstrate an absolute 10% intelligibility gain provided by the jaw and lip movements over the audio-only display.

A Control Scheme for Physical Human-Robot Interaction Coupled with an Environment of Unknown Stiffness

2020 ◽  
Vol 100 (1) ◽  
pp. 165-182 ◽  
Author(s):  
Hsieh-Yu Li ◽  
Audelia G. Dharmawan ◽  
Ishara Paranawithana ◽  
Liangjing Yang ◽  
U-Xuan Tan
Keyword(s):  
Human Robot Interaction ◽  
Robot Interaction ◽  
Control Scheme

Workload in Human-Robot Interaction: A Review of Manipulations and Outcomes

2009 ◽  
Author(s):  
Matthew S. Prewett ◽  
Kristin N. Saboe ◽  
Ryan C. Johnson ◽  
Michael D. Coovert ◽  
Linda R. Elliott
Keyword(s):  
Human Robot Interaction ◽  
Robot Interaction

Biomimetic, sociable robots for human-robot interaction

2010 ◽  
Author(s):  
Eleanore Edson ◽  
Judith Lytle ◽  
Thomas McKenna
Keyword(s):  
Human Robot Interaction ◽  
Robot Interaction

The role and relationship of mindreading and social attunement in HRI – position statements of interdisciplinary researchers. Workshop HRI'20

2020 ◽  
Author(s):  
Agnieszka Wykowska ◽  
Jairo Pérez-Osorio ◽  
Stefan Kopp
Keyword(s):  
Mental States ◽  
Human Robot Interaction ◽  
Human Interaction ◽  
Artificial Agents ◽  
The Novel ◽  
Robot Interaction ◽  
Novel Coronavirus ◽  
Relationship Of ◽  
The Relationship

This booklet is a collection of the position statements accepted for the HRI’20 conference workshop “Social Cognition for HRI: Exploring the relationship between mindreading and social attunement in human-robot interaction” (Wykowska, Perez-Osorio & Kopp, 2020). Unfortunately, due to the rapid unfolding of the novel coronavirus at the beginning of the present year, the conference and consequently our workshop, were canceled. On the light of these events, we decided to put together the positions statements accepted for the workshop. The contributions collected in these pages highlight the role of attribution of mental states to artificial agents in human-robot interaction, and precisely the quality and presence of social attunement mechanisms that are known to make human interaction smooth, efficient, and robust. These papers also accentuate the importance of the multidisciplinary approach to advance the understanding of the factors and the consequences of social interactions with artificial agents.

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