Human to humanoid motion conversion for dual-arm manipulation tasks

Tomić, Marija; Chevallereau, Christine; Jovanović, Kosta; Potkonjak, Veljko; Rodić, Aleksandar

doi:10.1017/s0263574718000309

Cited by 15 publications

(19 citation statements)

References 32 publications

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“…The influence of each criterion separately and the combination of the criteria in the IKs algorithm without using the weight coefficients were earlier presented in article. 28 In some cases, the best imitation is obtained with the combination of all criterion functions. The similarity of the recorded actors' motion and motions obtained for different values of weight coefficients for the "rotation of the canoe paddles" task is represented through the value of the fitness function.…”

Section: Discussionmentioning

confidence: 99%

“…The trajectories of hands in the Cartesian space, which are used to specify the task, are calculated using the results of the imitation algorithm. The detailed explanation of the imitation algorithm and human motion data recording by means of the ART motion capture system are detailed in the study by Tomić et al 28 Characterization of human motion using an inverse optimal control approach In this section, an inverse optimal control approach is defined in order to characterize human motion.…”

Section: Characteristics Of Human Motion Joint Activation Ergonomy mentioning

confidence: 99%

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Toward optimal mapping of human dual-arm motion to humanoid motion for tasks involving contact with the environment

Tomić

Jovanović

Chevallereau

et al. 2018

International Journal of Advanced Robotic Systems

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In this article, we explore human motion skills in the dual-arm manipulation tasks that include contact with equipment with the final aim to generate human-like humanoid motion. Human motion is analyzed using the optimization approaches starting with the assumption that human motion is optimal. A combination of commonly used optimization criteria in the joint space with the weight coefficients is considered: minimization of kinetic energy, minimization of joint velocities, minimization of the distance between the current and ergonomic positions, and maximization of manipulability. The contribution of each criterion for seven different dual-arm manipulation tasks to provide the most accurate imitation of the human motion is given via suggested inverse optimization approach calculating values of weight coefficients. The effects on actors' body characteristics and the characteristics of the environment (involved equipment) on the choice of criterion functions are additionally analyzed. The optimal combination of weight coefficients calculated by the inverse optimization approach is used in our inverse kinematics algorithm to transfer human motion skills to the motion of the humanoid robots. The results show that the optimal combination of weight coefficients is able to generate human-like humanoid motions rather than individual one of the considered criterion functions. The recorded human motion and the motion of the humanoid robot ROMEO, obtained with the strategy used by human and defined by our inverse optimal control approach, for the tasks "opening/closing a drawer" are assessed visually and quantitatively.

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Section: Discussionmentioning

confidence: 99%

Section: Characteristics Of Human Motion Joint Activation Ergonomy mentioning

confidence: 99%

Toward optimal mapping of human dual-arm motion to humanoid motion for tasks involving contact with the environment

Tomić

Jovanović

Chevallereau

et al. 2018

International Journal of Advanced Robotic Systems

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“…The observation process usually relies on either marker-based or markerless visual capture systems or dynamic capture systems to acquire human motions. In a marker-based visual capture system, markers must be placed on the demonstrators to indicate the positions of their body parts [10][11][12][13][14], whereas a markerless visual capture system can directly extract 2D or 3D information from video frames [15][16][17][18][19][20]. The imitation system presented in [21] obtained motion data using the Xsens MVN dynamic capture system (Enschede, The Netherlands), which offers high precision but is inconvenient and expensive.…”

Section: Introductionmentioning

confidence: 99%

“…To this end, several analytical methods have been exploited [13,14,19,20,[25][26][27][28][29]. In addition to the positions of the end effectors, other information such as the positions of the joints is obtained in these methods.…”

Section: Introductionmentioning

confidence: 99%

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Real-Time Whole-Body Imitation by Humanoid Robots and Task-Oriented Teleoperation Using an Analytical Mapping Method and Quantitative Evaluation

et al. 2018

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Due to the limitations on the capabilities of current robots regarding task learning and performance, imitation is an efficient social learning approach that endows a robot with the ability to transmit and reproduce human postures, actions, behaviors, etc., as a human does. Stable whole-body imitation and task-oriented teleoperation via imitation are challenging issues. In this paper, a novel comprehensive and unrestricted real-time whole-body imitation system for humanoid robots is designed and developed. To map human motions to a robot, an analytical method called geometrical analysis based on link vectors and virtual joints (GA-LVVJ) is proposed. In addition, a real-time locomotion method is employed to realize a natural mode of operation. To achieve safe mode switching, a filter strategy is proposed. Then, two quantitative vector-set-based methods of similarity evaluation focusing on the whole body and local links, called the Whole-Body-Focused (WBF) method and the Local-Link-Focused (LLF) method, respectively, are proposed and compared. Two experiments conducted to verify the effectiveness of the proposed methods and system are reported. Specifically, the first experiment validates the good stability and similarity features of our system, and the second experiment verifies the effectiveness with which complicated tasks can be executed. At last, an imitation learning mechanism in which the joint angles of demonstrators are mapped by GA-LVVJ is presented and developed to extend the proposed system.

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Safety in a Human Robot Interactive: Application to Haptic Perception

Guda

Chablat

Chevallereau

2020

Virtual, Augmented and Mixed Reality. Design and Interaction

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Usually, traditional haptic interfaces, such as Virtuose 6DOF [1], are used in the design phases by engineers [2]. Such interfaces are safe. However, the user can apply a force/torque but cannot really feel textures and appreciate material quality. These interfaces have a limited workspace, low stiffness and are very expensive. New haptic interfaces using an industrial robots or a cobot (robots specially designed to work in Human-Robot environments) can be used as a haptic interface with intermittent contacts [3,4]. For application considered in this paper, the cobot carries several specimens of texture on its end-effector, to allow contact between a finger of the user and the robot.Safety is an important aspect in Human Robot Interactions (HRI) [5], even with the use of cobots, because contacts are expected. The purpose of this paper is to introduce a new methodology to define the basic placement of the robot in relation to the human body and for the planning and control of movements during HRIs to ensure safety.

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Human to humanoid motion conversion for dual-arm manipulation tasks

Cited by 15 publications

References 32 publications

Toward optimal mapping of human dual-arm motion to humanoid motion for tasks involving contact with the environment

Toward optimal mapping of human dual-arm motion to humanoid motion for tasks involving contact with the environment

Real-Time Whole-Body Imitation by Humanoid Robots and Task-Oriented Teleoperation Using an Analytical Mapping Method and Quantitative Evaluation

Safety in a Human Robot Interactive: Application to Haptic Perception

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