Iterative virtual guides programming for human-robot comanipulation

Purpose To promote the intuitiveness of collaborative tasks, the negotiation ability of humans with each other has inspired a large amount of studies aimed at reproducing the capacity in physical human-robot interaction (pHRI). This paper aims to promote mutual adaptation in negotiation when both parties possess incomplete information. Design/methodology/approach This paper introduces virtual fixtures into the traditional negotiation mechanism, locally regulating tracking trajectory and impedance parameters in the negotiating phase until the final plan integrates bilateral intentions well. In the strategy, robots convey its task information to humans and offer groups of guide plans for them to choose, on the premise of maximizing the robot’s own profits. Findings Compared with traditional negotiation strategies, humans adapt to robots easily and show lower cognitive load in the method, while the satisfied plan shows better performance for the whole human-robot system. Originality/value In this study, this paper proposes a novel negotiation strategy to facilitate the mutual adaptation of humans and robots in complicated shared tasks, especially when both parties possess incomplete information of tasks.

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“…Several research studies have applied the method to help humans in pHRI tasks (Takubo et al, 2002;Sanchez Restrepo et al, 2017).…”

Section: Trajectory Interpolationmentioning

confidence: 99%

Promoting mutual adaptation in haptic negotiation using adaptive virtual fixture

Hua

Dong

Chen

et al. 2021

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“…13 In this section, we summarize the definition of virtual mechanisms and formalize our implementation of virtual guides via these mechanisms. Our previous work presented this implementation for 3D virtual guides, 40 and we now present it for 6D virtual guides.…”

Section: Virtual Mechanisms As Virtual Guidesmentioning

confidence: 99%

“…As presented in our previous work, 40 we can define the kinematics of the position constraint through PbD and Akima spline interpolation. 44 During the kinesthetic teaching, the user is able to show the cobot the desired trajectory by manually moving its end-effector.…”

Section: Virtual Guides As Position Constraintsmentioning

confidence: 99%

“…For these reasons and the ones outlined in Section 2, we suggest that users program the virtual guides by iteratively modifying them while being assisted by the collaborative robot. In our previous work, 40 we presented a local guide refinement method. The refinement is done directly on the workspace by manually manipulating the cobot end-effector to show a new portion of the guide.…”

Section: Iterative Virtual Guides Programmingmentioning

confidence: 99%

“…For the position constraints, we proposed a solution based on the arc-length. 40 Similarly, since the list of orientations recorded by the cobot is obtained by user demonstrations, we cannot guarantee the normality of J s for the orientation constraints.…”

Section: Parameterizationmentioning

confidence: 99%

See 2 more Smart Citations

Toward an Intuitive and Iterative 6D Virtual Guide Programming Framework for Assisted Human–Robot Comanipulation

Restrepo¹,

Raiola²,

Guerry³

et al. 2020

Robotica

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SUMMARY In human–robot comanipulation, virtual guides are an important tool used to assist the human worker as they constrain the movement of the robot to improve the task accuracy and to avoid undesirable effects, such as collisions with the environment. Consequently, the physical effort and cognitive overload are reduced during accomplishment of comanipulative tasks. However, the construction of virtual guides often requires expert knowledge and modeling of the task, which restricts the usefulness of virtual guides to scenarios with fixed constraints. Moreover, few approaches have addressed the implementation of virtual guides enforcing orientation constraints and, when done, these approaches have treated translation and orientation separately, and consequently there is no synchronization of the translational and rotational motions. To overcome these challenges and enhance the programming flexibility of virtual guides, we present a new framework that allows the user to create 6D virtual guides through XSplines which we define as a combination of Akima splines for the translation component and spherical cubic interpolation of quaternions for the orientation component. For complex tasks, the user is able to initially define a 3D virtual guide and then use this assistance in translational motion to concentrate only on defining the orientations along the path. It is also possible for the user to modify a particular point or portion of a guide while being assisted by it. We demonstrate in an industrial scenario that these innovations provide an intuitive solution to extend the use of virtual guides to 6 degrees of freedom and increase the human worker’s comfort during the programming phase of these guides in an assisted human–robot comanipulation context.

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Co-manipulation with a library of virtual guiding fixtures

et al. 2017

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Virtual guiding fixtures constrain the movements of a robot to task-relevant trajectories, and have been successfully applied to, for instance, surgical and manufacturing tasks. Whereas previous work has considered guiding fixtures for single tasks, in this paper we propose a library of guiding fixtures for multiple tasks, and propose methods for 1) Creating and adding guides based on machine learning; 2) Selecting guides on-line based on probabilistic implementation of guiding fixtures; 3) Refining existing guides based on an incremental learning method. We demonstrate in an industrial task that a library of guiding fixtures provides an intuitive haptic interface for joint human-robot completion of tasks, and improves performance in terms of task execution time, mental workload and errors.

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Iterative virtual guides programming for human-robot comanipulation

Cited by 17 publications

References 30 publications

Promoting mutual adaptation in haptic negotiation using adaptive virtual fixture

Promoting mutual adaptation in haptic negotiation using adaptive virtual fixture

Toward an Intuitive and Iterative 6D Virtual Guide Programming Framework for Assisted Human–Robot Comanipulation

Co-manipulation with a library of virtual guiding fixtures

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