Passivity-based Adaptive Force-Impedance Control for Modular Multi-Manual Object Manipulation

PurposeThe aim of this paper is to present the non‐model‐based multiple impedance control (NMIC) law for object manipulation tasks, which can be implemented with reasonable limited on‐line computations.Design/methodology/approachThe multiple impedance control (MIC) is a model‐based algorithm that enforces a designated impedance on all cooperating manipulators, and the manipulated object itself. In this paper, the MIC law is modified to be implemented without using system dynamics. Therefore, this modified MIC law is a quick and more realistic algorithm for implementation in cooperating robotic systems, and so is called NMIC. Developing the NMIC law, error analysis shows that under the NMIC law all participating manipulators, and the manipulated object exhibit the same designated impedance behavior. Next, the proposed NMIC law is applied on an object manipulation task with three cooperating PUMA 560 manipulators while two of them are equipped with a remote compliant centre.FindingsDeveloping the NMIC law, error analysis shows that under the NMIC law all participating manipulators, and the manipulated object exhibit the same designated impedance behavior. The obtained results show good tracking performance even in the presence of impacts due to contact with an obstacle, and also system flexibility.Practical implicationsThe obtained results show good tracking performance even in the presence of impacts due to contact with an obstacle, and also system flexibility. These results reveal the merits of NMIC law as a non‐model‐based algorithm for object manipulation tasks, which can be implemented with reasonable limited on‐line computations.Originality/valueThe proposed NMIC law is applied on an object manipulation task with three cooperating PUMA 560 manipulators while two of them are equipped with a remote compliant centre.

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Mechanical Impedance Control of Cooperative Robot During Object Manipulation Based on External Force Estimation Using Recurrent Neural Network

Unmanned Systems ◽

10.1142/s230138502050017x ◽

2020 ◽

Vol 08 (03) ◽

pp. 239-251

Author(s):

Misaki Hanafusa ◽

Jun Ishikawa

Keyword(s):

Neural Network ◽

External Force ◽

Recurrent Neural Network ◽

Inverse Dynamics ◽

Impedance Control ◽

Mechanical Impedance ◽

Object Manipulation ◽

Force Estimation ◽

Dynamics Model ◽

Compliant Motion

This paper proposes a compliant motion control for human-cooperative robots to absorb collision force when persons accidentally touch the robots even while the robot is manipulating an object. In the proposed method, an external force estimator, which can distinguish the net external force from the object manipulation force, is realized using an inverse dynamics model acquired by a recurrent neural network (RNN). By implementing a mechanical impedance control to the estimated external force, the robot can quickly and precisely carry the object keeping the mechanical impedance control functioned and can generate a compliant motion to the net external force only when the person touches it during manipulation. Since the proposed method estimates the external force from the generalized force based on the learned inverse dynamics, it is not necessary to install any sensors on the manipulated object to measure the external force. This allows the robot to detect the collision even when the person touches anywhere on the manipulated object. The RNN inverse dynamics model is evaluated by the leave-one-out cross-validation and it was found that it works well for unknown trajectories excluded from the learning process. Although the details were omitted due to the limitation of the page length, similar to the simulations, the RNN inverse dynamics model was evaluated using unknown trajectories in the six degree-of-freedom experiments, and it has been verified that it functions properly even for the unknown trajectories. Finally, the validity of the proposed method has been confirmed by experiments in which a person touches a robot while it is manipulating an object with six degrees of freedom.

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Which impedance strategy is the most effective for cooperative object manipulation?

Industrial Robot the international journal of robotics research and application ◽

10.1108/ir-08-2016-0216 ◽

2017 ◽

Vol 44 (2) ◽

pp. 198-209 ◽

Cited By ~ 2

Author(s):

Payam Zarafshan ◽

Reza Larimi ◽

S. Ali A. Moosavian ◽

Bruno Siciliano

Keyword(s):

Conceptual Model ◽

Degrees Of Freedom ◽

Impedance Control ◽

Object Manipulation ◽

Robotic System ◽

Control Algorithms ◽

Practical Implementation ◽

Content Type ◽

Manipulation Task ◽

Cooperative Object Manipulation

Purpose The purpose of this paper is to present a comparison study of cooperative object manipulation control algorithms. To this end, a full comprehensive survey of the existing control algorithms in this field is presented. Design/methodology/approach Cooperative manipulation occurs when manipulators are mechanically coupled to the object being manipulated, and the manipulators may not be treated as an isolated system. The most important and basic impedance control (IC) strategies for an assumed cooperative object manipulation task are the Augmented Object Model (AOM) control and the multiple impedance control (MIC) which are found based on the IC, where the former is designed based on the object movement, and the latter is designed based on the whole robot movement. Thus, the basis of these two algorithms are fully studied. Findings The results are fully analyzed, and it is practically verified that the MIC algorithm has the better performance. In fact, the results reveal that the MIC system could successfully perform the object manipulation task, as opposed to the AOM controller: for the same controller gains, the MIC strategy showed better performance than the AOM strategy. This means that because there is no control on the robot base with the AOM algorithm, the object manipulation task cannot be satisfactorily performed whenever the desired path is not within the robot work space. On the other hand, with the MIC algorithm, satisfactory object manipulation is achieved for a mobile robotic system in which the robot base, the manipulator endpoints and the manipulated object shall be moved. Practical implications A simple conceptual model for cooperative object manipulation is considered, and a suitable setup is designed for practical implementation of the two ICs. Originality/value The basis of these two aspects or these two algorithms is fully studied and compared which is the foundation of this paper. For this purpose, a case study is considered, in which a space free-flying robotic system, which contains two 2-degrees of freedom planar cooperative manipulators, is simulated to manipulate an object using the above control strategies. The system also includes a rotating antenna and camera as its third and fourth arm. Finally, a simple conceptual model for cooperative object manipulation is considered, and a suitable setup is designed for practical implementation of the two ICs.

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