Biomimetic object impedance control for dual-arm cooperative 7-DOF manipulators

Ren, Yi; Liu, Yechao; Jin, Minghe; Hong, Li

doi:10.1016/j.robot.2015.09.018

Cited by 39 publications

(34 citation statements)

References 41 publications

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“…In parallel with the robot finger grasping case, the object's inertial parameters are incorporated in the dynamics of the robots to generate closed-loop models. The closed-loop models are used for solving manipulation problems such as control, trajectory generation, and others [111] [112] [113][114] [90]. Referring to all literature that uses multiple arms and object models is out of the scope of the paper, and an extensive survey has been conducted in [115].…”

Section: Exploitation Of Inertial Parametersmentioning

confidence: 99%

Estimation and exploitation of objects ’ inertial parameters in robotic grasping and manipulation: A survey

Mavrakis

Stolkin

2020

Robotics and Autonomous Systems

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Inertial parameters characterise an object's motion under applied forces, and can provide strong priors for planning and control of robotic actions to manipulate the object. However, these parameters are not available a-priori in situations where a robot encounters new objects. In this paper, we describe and categorise the ways that a robot can identify an object's inertial parameters. We also discuss grasping and manipulation methods in which knowledge of inertial parameters is exploited in various ways. We begin with a discussion of literature which investigates how humans estimate the inertial parameters of objects, to provide background and motivation for this area of robotics research. We frame our discussion of the robotics literature in terms of three categories of estimation methods, according to the amount of interaction with the object: purely visual, exploratory, and fixed-object. Each category is analysed and discussed. To demonstrate the usefulness of inertial estimation research, we describe a number of grasping and manipulation applications that make use of the inertial parameters of objects. The aim of the paper is to thoroughly review and categorise existing work in an important, but under-explored, area of robotics research, present its background and applications, and suggest future directions. Note that this paper does not examine methods of identification of the robot's inertial parameters, but rather the identification of inertial parameters of other objects which the robot is tasked with manipulating.

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Section: Exploitation Of Inertial Parametersmentioning

confidence: 99%

Estimation and exploitation of objects ’ inertial parameters in robotic grasping and manipulation: A survey

Mavrakis

Stolkin

2020

Robotics and Autonomous Systems

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“…where J ci is defined in Equation 5. The matrix J -T ci is known in the literature as the grasp matrix.…”

Section: Dynamics Of the Cooperative Systemmentioning

confidence: 99%

“…For that reason, many researchers have studied the control of multiple robots in the last decades. Position and force control for cooperative robots can be classified in impendace control schemes 4,5 and hybrid position/force control algorithms. For the former, the manipulators share position and force information and the dynamics of the whole system is also required.…”

Section: Introductionmentioning

confidence: 99%

“…2,3 In cooperative tasks that involve dexterous manipulation, it is required to control not only the position and orientation of the object but also the interaction forces. Position and force control for cooperative robots can be classified in impendace control schemes 4,5 and hybrid position/force control algorithms. 6,7 The problem of 2 robots grasping an object that interacts with a rigid environment is addressed in Yao et al 8 The environment is modeled as a time-invariant holonomic constraint, and it is assumed that the object is rigidly attached to the robots' end effector.…”

Section: Introductionmentioning

confidence: 99%

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On the adaptive control of cooperative robots with time‐variant holonomic constraints

Pliego‐Jiménez¹,

Arteaga²

2017

Adaptive Control & Signal

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In this work, we consider the problem of 2 robots handling a rigid object, while model-parameter uncertainties are assumed. It is also assumed that the manipulators can push but not pull the object. Several control schemes proposed in the literature attempt to control the position of the object rather than its orientation. However, many industrial tasks require to move and to rotate the object. To this end, we propose an adaptive hybrid position/force control law based on time-variant holonomic constraints, which allow for object position and orientation control. Our approach guarantees that the force error asymptotically converges to 0; therefore, a stable grasp can be accomplished by means of a proper definition of the desired pushing force. In addition, a dynamic model of the cooperative system based on the load distribution and joint-space orthogonalization principles is developed. Experimental results are presented to validate the proposed dynamic model and control scheme.Consider the following auxiliary theorem: Theorem 2. 31 Let ⊂ ℜ n be a domain containing y = 0 and suppose f(t, y) is piecewise continuous in t and locally Lipschitz in y,J 1 (2, 1) = 11 c(q 11 ), J 1 (2, 2) = 21 c(q 21 ),For the matrix J 2 = J c2 J m2 , we haveJ 2 (2, 1) = 21 c(q 21 ) + 22 c(q 22 ) + ( 32 − r cx2 )c( 2 ) + r cy2 s( 2 ), J 2 (2, 2) = 22 c(q 22 ) + ( 32 − r cx2 )c( 2 ) + r cy2 s( 2 ), J 2 (2, 3) = ( 32 − r cx2 )c( 2 ) + r cy2 s( 2 ), J 2 (3, 1) = 1, J 2 (3, 2) = 1, J 2 (3, 3) = 1.

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“…Although approaches of internal impedance [5] , object impedance [6] and combined multi-layer impedance [7,8] are proposed to achieve desired interaction in the end-effector level and object level, and can be applied without any switching procedure between contact and non-contact case, lack of precision in controlling position of the grasped object and the contact force as compared to hybrid position/force control may limit their application in some situations like surgery, manufacturing, precision welding, etc. [9] .…”

Section: Introductionmentioning

confidence: 99%

Adaptive hybrid position/force control of dual-arm cooperative manipulators with uncertain dynamics and closed-chain kinematics

Ren

Chen

Liu

et al. 2017

Journal of the Franklin Institute

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In this paper, a novel adaptive control for dual-arm cooperative manipulators is proposed to accomplish the hybrid position/force tracking in the presence of dynamic and closed-chain kinematic uncertainties. Self-convergent parameter estimation of the grasped object's centre of mass and contact force estimation are incorporated into this systematic scheme. Moreover, internal force and contact force tracking objectives are achieved simultaneously by incorporating into the position tracking formula with proper null-space projection and rotation transformation. Noisy force derivative signals are not required. This adaptive controller is mathematically derived based on Lyapunov stability analysis. Three sets of simulations corresponding to three different situations are presented to verify the effectiveness and superiority of the proposed controller.

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Biomimetic object impedance control for dual-arm cooperative 7-DOF manipulators

Cited by 39 publications

References 41 publications

Estimation and exploitation of objects ’ inertial parameters in robotic grasping and manipulation: A survey

Estimation and exploitation of objects ’ inertial parameters in robotic grasping and manipulation: A survey

On the adaptive control of cooperative robots with time‐variant holonomic constraints

Adaptive hybrid position/force control of dual-arm cooperative manipulators with uncertain dynamics and closed-chain kinematics

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