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Uncontrolled Manifold Reference Feedback Control of Multi-Joint Robot Arms.

Togo S, Kagawa T, Uno Y - Front Comput Neurosci (2016)

Bottom Line: The target UCM is a subspace of joint angles whose variability does not affect the hand position.As a result, the UCM reference feedback control could quantitatively reproduce the difference of the mean value for the end hand position between the initial postures, the peaks of the bell-shape tangential hand velocity, the sum of the squared torque, the mean value for the torque change, the variance components, and the index of synergy as well as the human subjects.We concluded that UCM reference feedback control can reproduce human-like joint coordination.

View Article: PubMed Central - PubMed

Affiliation: Cognitive Mechanisms Laboratories, Advanced Telecommunications Research Institute InternationalKyoto, Japan; Japan Society for the Promotion of ScienceTokyo, Japan.

ABSTRACT
The brain must coordinate with redundant bodies to perform motion tasks. The aim of the present study is to propose a novel control model that predicts the characteristics of human joint coordination at a behavioral level. To evaluate the joint coordination, an uncontrolled manifold (UCM) analysis that focuses on the trial-to-trial variance of joints has been proposed. The UCM is a nonlinear manifold associated with redundant kinematics. In this study, we directly applied the notion of the UCM to our proposed control model called the "UCM reference feedback control." To simplify the problem, the present study considered how the redundant joints were controlled to regulate a given target hand position. We considered a conventional method that pre-determined a unique target joint trajectory by inverse kinematics or any other optimization method. In contrast, our proposed control method generates a UCM as a control target at each time step. The target UCM is a subspace of joint angles whose variability does not affect the hand position. The joint combination in the target UCM is then selected so as to minimize the cost function, which consisted of the joint torque and torque change. To examine whether the proposed method could reproduce human-like joint coordination, we conducted simulation and measurement experiments. In the simulation experiments, a three-link arm with a shoulder, elbow, and wrist regulates a one-dimensional target of a hand through proposed method. In the measurement experiments, subjects performed a one-dimensional target-tracking task. The kinematics, dynamics, and joint coordination were quantitatively compared with the simulation data of the proposed method. As a result, the UCM reference feedback control could quantitatively reproduce the difference of the mean value for the end hand position between the initial postures, the peaks of the bell-shape tangential hand velocity, the sum of the squared torque, the mean value for the torque change, the variance components, and the index of synergy as well as the human subjects. We concluded that UCM reference feedback control can reproduce human-like joint coordination. The inference for motor control of the human central nervous system based on the proposed method was discussed.

No MeSH data available.


Related in: MedlinePlus

Concept of UCM reference feedback control. (A) Schematic diagram of the task coordination and joint angles in the horizontal plane. For the one-dimensional target-tracking task, the hand is moved from the start position to the end position tracking the target hand position along the X-axis while variability along the Y-axis is allowed. (B) Schema of UCM reference feedback control. UCMt denotes the target UCM at time t. The configuration of the joint angles is disturbed at time t, and deviates from the target UCM at time t + 1. Through the UCM reference feedback control method, the disturbed joint angles converge to the target UCM at time t + 2. (C) Block diagram of UCM reference feedback control. The UCM reference feedback controller is given the target hand trajectory xd, and calculates the unique reference joint angles θd* within the target UCM so as to minimize the cost function. Then, the inverse dynamics of the arm generates the input torque τ using the current joint condition θ and  and reference joint angles θd*. The upper (pseudo) loop represents the visual feedback loop while the lower loop represents the somatosensory feedback.
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Figure 1: Concept of UCM reference feedback control. (A) Schematic diagram of the task coordination and joint angles in the horizontal plane. For the one-dimensional target-tracking task, the hand is moved from the start position to the end position tracking the target hand position along the X-axis while variability along the Y-axis is allowed. (B) Schema of UCM reference feedback control. UCMt denotes the target UCM at time t. The configuration of the joint angles is disturbed at time t, and deviates from the target UCM at time t + 1. Through the UCM reference feedback control method, the disturbed joint angles converge to the target UCM at time t + 2. (C) Block diagram of UCM reference feedback control. The UCM reference feedback controller is given the target hand trajectory xd, and calculates the unique reference joint angles θd* within the target UCM so as to minimize the cost function. Then, the inverse dynamics of the arm generates the input torque τ using the current joint condition θ and and reference joint angles θd*. The upper (pseudo) loop represents the visual feedback loop while the lower loop represents the somatosensory feedback.

Mentions: In this study, the common controlled object in the simulation and measurement experiments is a three-link arm consisting of an upper arm, forearm, and hand. The common task is a tracking task of the one-dimensional target of the hand in the horizontal plane (Figure 1A). Thus, the joint angles and hand position correspond to the motor elements and the performance variable in the UCM concept. Only the lateral position of the target is considered so that the relationship between the target and motor elements is considered redundant. The task coordinates (X- and Y-axes) and joint angles (θs, θe, and θw) are defined in Figure 1A.


Uncontrolled Manifold Reference Feedback Control of Multi-Joint Robot Arms.

Togo S, Kagawa T, Uno Y - Front Comput Neurosci (2016)

Concept of UCM reference feedback control. (A) Schematic diagram of the task coordination and joint angles in the horizontal plane. For the one-dimensional target-tracking task, the hand is moved from the start position to the end position tracking the target hand position along the X-axis while variability along the Y-axis is allowed. (B) Schema of UCM reference feedback control. UCMt denotes the target UCM at time t. The configuration of the joint angles is disturbed at time t, and deviates from the target UCM at time t + 1. Through the UCM reference feedback control method, the disturbed joint angles converge to the target UCM at time t + 2. (C) Block diagram of UCM reference feedback control. The UCM reference feedback controller is given the target hand trajectory xd, and calculates the unique reference joint angles θd* within the target UCM so as to minimize the cost function. Then, the inverse dynamics of the arm generates the input torque τ using the current joint condition θ and  and reference joint angles θd*. The upper (pseudo) loop represents the visual feedback loop while the lower loop represents the somatosensory feedback.
© Copyright Policy
Related In: Results  -  Collection

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Show All Figures
getmorefigures.php?uid=PMC4940408&req=5

Figure 1: Concept of UCM reference feedback control. (A) Schematic diagram of the task coordination and joint angles in the horizontal plane. For the one-dimensional target-tracking task, the hand is moved from the start position to the end position tracking the target hand position along the X-axis while variability along the Y-axis is allowed. (B) Schema of UCM reference feedback control. UCMt denotes the target UCM at time t. The configuration of the joint angles is disturbed at time t, and deviates from the target UCM at time t + 1. Through the UCM reference feedback control method, the disturbed joint angles converge to the target UCM at time t + 2. (C) Block diagram of UCM reference feedback control. The UCM reference feedback controller is given the target hand trajectory xd, and calculates the unique reference joint angles θd* within the target UCM so as to minimize the cost function. Then, the inverse dynamics of the arm generates the input torque τ using the current joint condition θ and and reference joint angles θd*. The upper (pseudo) loop represents the visual feedback loop while the lower loop represents the somatosensory feedback.
Mentions: In this study, the common controlled object in the simulation and measurement experiments is a three-link arm consisting of an upper arm, forearm, and hand. The common task is a tracking task of the one-dimensional target of the hand in the horizontal plane (Figure 1A). Thus, the joint angles and hand position correspond to the motor elements and the performance variable in the UCM concept. Only the lateral position of the target is considered so that the relationship between the target and motor elements is considered redundant. The task coordinates (X- and Y-axes) and joint angles (θs, θe, and θw) are defined in Figure 1A.

Bottom Line: The target UCM is a subspace of joint angles whose variability does not affect the hand position.As a result, the UCM reference feedback control could quantitatively reproduce the difference of the mean value for the end hand position between the initial postures, the peaks of the bell-shape tangential hand velocity, the sum of the squared torque, the mean value for the torque change, the variance components, and the index of synergy as well as the human subjects.We concluded that UCM reference feedback control can reproduce human-like joint coordination.

View Article: PubMed Central - PubMed

Affiliation: Cognitive Mechanisms Laboratories, Advanced Telecommunications Research Institute InternationalKyoto, Japan; Japan Society for the Promotion of ScienceTokyo, Japan.

ABSTRACT
The brain must coordinate with redundant bodies to perform motion tasks. The aim of the present study is to propose a novel control model that predicts the characteristics of human joint coordination at a behavioral level. To evaluate the joint coordination, an uncontrolled manifold (UCM) analysis that focuses on the trial-to-trial variance of joints has been proposed. The UCM is a nonlinear manifold associated with redundant kinematics. In this study, we directly applied the notion of the UCM to our proposed control model called the "UCM reference feedback control." To simplify the problem, the present study considered how the redundant joints were controlled to regulate a given target hand position. We considered a conventional method that pre-determined a unique target joint trajectory by inverse kinematics or any other optimization method. In contrast, our proposed control method generates a UCM as a control target at each time step. The target UCM is a subspace of joint angles whose variability does not affect the hand position. The joint combination in the target UCM is then selected so as to minimize the cost function, which consisted of the joint torque and torque change. To examine whether the proposed method could reproduce human-like joint coordination, we conducted simulation and measurement experiments. In the simulation experiments, a three-link arm with a shoulder, elbow, and wrist regulates a one-dimensional target of a hand through proposed method. In the measurement experiments, subjects performed a one-dimensional target-tracking task. The kinematics, dynamics, and joint coordination were quantitatively compared with the simulation data of the proposed method. As a result, the UCM reference feedback control could quantitatively reproduce the difference of the mean value for the end hand position between the initial postures, the peaks of the bell-shape tangential hand velocity, the sum of the squared torque, the mean value for the torque change, the variance components, and the index of synergy as well as the human subjects. We concluded that UCM reference feedback control can reproduce human-like joint coordination. The inference for motor control of the human central nervous system based on the proposed method was discussed.

No MeSH data available.


Related in: MedlinePlus