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.

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.

scholarly journals A variable admittance control strategy for stable physical human–robot interaction

2019 ◽  
Vol 38 (6) ◽  
pp. 747-765 ◽  
Author(s):  
Federica Ferraguti ◽  
Chiara Talignani Landi ◽  
Lorenzo Sabattini ◽  
Marcello Bonfè ◽  
Cesare Fantuzzi ◽  
...  
Keyword(s):  
Human Robot Interaction ◽  
Admittance Control ◽  
Robot Interaction ◽  
Interaction Control ◽  
Human Arm ◽  
Industrial Operations ◽  
Novel Method ◽  
The Stability ◽  
Stability Issues ◽  
Human Robot Collaboration

Admittance control allows a desired dynamic behavior to be reproduced on a non-backdrivable manipulator and it has been widely used for interaction control and, in particular, for human–robot collaboration. Nevertheless, stability problems arise when the environment (e.g. the human) the robot is interacting with becomes too stiff. In this paper, we investigate the stability issues related to a change of stiffness of the human arm during the interaction with an admittance-controlled robot. We propose a novel method for detecting the rise of instability and a passivity-preserving strategy for restoring a stable behavior. The results of the paper are validated on two robotic setups and with 50 users performing two tasks that emulate industrial operations.

scholarly journals State-Transition Modeling of Human–Robot Interaction for Easy Crowdsourced Robot Control

Sensors ◽  
2020 ◽  
Vol 20 (22) ◽  
pp. 6529
Author(s):  
Masaya Iwasaki ◽  
Mizuki Ikeda ◽  
Tatsuyuki Kawamura ◽  
Hideyuki Nakanishi
Keyword(s):  
User Interface ◽  
Social Presence ◽  
Robot Control ◽  
State Transition ◽  
Human Robot Interaction ◽  
Sales Promotion ◽  
Robot Interaction ◽  
Sensor Information ◽  
Transition Modeling ◽  
First Time

Robotic salespeople are often ignored by people due to their weak social presence, and thus have difficulty facilitating sales autonomously. However, for robots that are remotely controlled by humans, there is a need for experienced and trained operators. In this paper, we suggest crowdsourcing to allow general users on the internet to operate a robot remotely and facilitate customers’ purchasing activities while flexibly responding to various situations through a user interface. To implement this system, we examined how our developed remote interface can improve a robot’s social presence while being controlled by a human operator, including first-time users. Therefore, we investigated the typical flow of a customer–robot interaction that was effective for sales promotion, and modeled it as a state transition with automatic functions by accessing the robot’s sensor information. Furthermore, we created a user interface based on the model and examined whether it was effective in a real environment. Finally, we conducted experiments to examine whether the user interface could be operated by an amateur user and enhance the robot’s social presence. The results revealed that our model was able to improve the robot’s social presence and facilitate customers’ purchasing activity even when the operator was a first-time user.

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