Interactive manipulation between a human and a humanoid: When robots control human arm motion

Adorno,; Bo, Bo; Fraisse,

doi:10.1109/iros.2011.6048554

Cited by 2 publications

(5 citation statements)

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“…Inverse kinematics techniques have been developed using dual quaternions for six-dof manipulators (Aydin and Kucuk, 2006; Sariyildiz and Temeltas, 2009) and compared to other methods (Sariyildiz et al, 2011). They are also used in the context of cooperative control of multiple manipulators: several robotic manipulators (Adorno et al, 2010) or a robotic manipulator interacting with a human arm (Adorno et al, 2011). In Pham et al (2010), they develop a control law using dual quaternion to control simultaneously the position and orientation of a robotic manipulator.…”

Section: Discussionmentioning

confidence: 99%

3D kinematics using dual quaternions: theory and applications in neuroscience

Leclercq¹,

Lefèvre²,

Blohm³

2013

Front. Behav. Neurosci.

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In behavioral neuroscience, many experiments are developed in 1 or 2 spatial dimensions, but when scientists tackle problems in 3-dimensions (3D), they often face problems or new challenges. Results obtained for lower dimensions are not always extendable in 3D. In motor planning of eye, gaze or arm movements, or sensorimotor transformation problems, the 3D kinematics of external (stimuli) or internal (body parts) must often be considered: how to describe the 3D position and orientation of these objects and link them together? We describe how dual quaternions provide a convenient way to describe the 3D kinematics for position only (point transformation) or for combined position and orientation (through line transformation), easily modeling rotations, translations or screw motions or combinations of these. We also derive expressions for the velocities of points and lines as well as the transformation velocities. Then, we apply these tools to a motor planning task for manual tracking and to the modeling of forward and inverse kinematics of a seven-dof three-link arm to show the interest of dual quaternions as a tool to build models for these kinds of applications.

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Section: Discussionmentioning

confidence: 99%

3D kinematics using dual quaternions: theory and applications in neuroscience

Leclercq¹,

Lefèvre²,

Blohm³

2013

Front. Behav. Neurosci.

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“…16 Analogously, the differential FKM of the human arm is given by vecẋ T H = J x T Hθ H , in which θ H is the vector of joint variables of the human arm, and J x T H is the analytic Jacobian of the human arm. 13 Proposition 1. The unified differential FKM for the human-robot interaction system is given by…”

Section: Kinematic Modeling Of the Human-robot Interaction Systemmentioning

confidence: 99%

“…In previous works, we presented preliminary development of kinematic modeling and control for pHRI, 12 as well as preliminary development regarding FES control of the human arm. 13 In the present paper, we unified the kinematic modeling and control of the interaction system from a more rigorous theoretical point of view. This development is important because we are able to show that complex interactions, when appropriately modeled, can be controlled using established control laws.…”

Section: Contributions and Organization Of The Papermentioning

confidence: 99%

“…For the purposes of this paper, all the reasoning is done by assuming that the pose of the human hand is already given with respect to the common frame, and the methodology to obtain such pose is presented in previous works. 12,13 The motion tracker used in this work, the Easytrack 500 (Atracsys, Switzerland), is composed of linear cameras and can track and estimate, every 100 ms, the pose of a marker equipped with infrared LEDs. In the first two experiments, the marker was placed on the subject's wrist or hand, as shown in Figs.…”

Section: General Experimental Setupmentioning

confidence: 99%

“…If the robot mirrors the person, the person can drive the robot hand to the right grasp position while positioning his own hand. By using the variable task parameter x task d defined in Adorno et al (2011), 13 the robot behaves as follows: whenever the subject moves his hand vertically or horizontally, the robot will try to place its hand at the same place as the subject's hand. However, when the subject moves the hand backward, the robot will also move its hand backward.…”

Section: Human Holds Complete Control: Mirrored Movements Followed Bymentioning

confidence: 99%

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Kinematic modeling and control for human-robot cooperation considering different interaction roles

2014

Self Cite

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SUMMARYThis paper presents a novel approach for the description of physical human-robot interaction (pHRI) tasks that involve two-arm coordination, and where tasks are described by the relative pose between the human hand and the robot hand. We develop a unified kinematic model that takes into account the human-robot system from a holistic point of view, and we also propose a kinematic control strategy for pHRI that comprises different levels of shared autonomy. Since the kinematic model takes into account the complete human-robot interaction system and the kinematic control law is closed loop at the interaction level, the kinematic constraints of the task are enforced during its execution. Experiments are performed in order to validate the proposed approach, including a particular case where the robot controls the human arm by means of functional electrical stimulation (FES), which may potentially provide useful solutions for the interaction between assistant robots and impaired individuals (e.g., quadriplegics and hemiplegics).

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Interactive manipulation between a human and a humanoid: When robots control human arm motion

Cited by 2 publications

References 5 publications

3D kinematics using dual quaternions: theory and applications in neuroscience

3D kinematics using dual quaternions: theory and applications in neuroscience

Kinematic modeling and control for human-robot cooperation considering different interaction roles

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