Dynamic two arm hybrid position/force control

Köpf, C.

doi:10.1016/0921-8890(89)90021-3

Cited by 8 publications

(5 citation statements)

References 8 publications

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“…x O (t), ẋO (t), ∀t ∈ [0, τ max ), we conclude the boundedness of d O (x O (t), ẋO (t), t) and d i (q i (t), qi (t), t), ∀t ∈ [0, τ max ). Hence, from (10) and (11), we also obtain the boundedness of d(x(t)). In addition, the continuity of M (x), C(x), g(x) implies their boundedness ∀t ∈ [0, τ max ).…”

Section: B Prescribed Performance Controlmentioning

confidence: 99%

“…Early works develop control architectures where the robotic agents communicate and share information with each other, and completely decentralized schemes, where each agent uses only local information or observers, avoiding potential communication delays (see, indicatively, [1]- [10]). Impedance and hybrid force/position control is the most common methodology used in the related literature [8]- [24], where a desired impedance behavior is imposed potentially with force regulation.…”

Section: Introductionmentioning

confidence: 99%

“…Full model information is employed in the works [1], [7], [9], [10], [13], [15], [17], [23]; [7] employs a velocity estimator, [23] uses a linearized model, and [14], [15] considers kinematic and grasping uncertainties. Adaptive control schemes are developed in [20], where redundancy is used for obstacle avoidance and [27], where the object dynamics are not taken into account; [28] and [29] propose protocols based on graphbased communication by neglecting parts of the overall system dynamics, and [18], [29] consider leader-follower approaches.…”

Section: Introductionmentioning

confidence: 99%

“…O and d ′ i , respectively, ∀i ∈ N . Hence, from(10) and(11), we obtaind(x(t)) ≤ d := d ′ O + i∈N { p…”

mentioning

confidence: 99%

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Robust Cooperative Manipulation Without Force/Torque Measurements: Control Design and Experiments

Verginis

Mastellaro

Dimarogonas

2020

IEEE Trans. Contr. Syst. Technol.

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This paper presents two novel control methodologies for the cooperative manipulation of an object by N robotic agents. Firstly, we design an adaptive control protocol which employs quaternion feedback for the object orientation to avoid potential representation singularities. Secondly, we propose a control protocol that guarantees predefined transient and steadystate performance for the object trajectory. Both methodologies are decentralized, since the agents calculate their own signals without communicating with each other, as well as robust to external disturbances and model uncertainties. Moreover, we consider that the grasping points are rigid, and avoid the need for force/torque measurements. Load distribution is also included via a grasp matrix pseudo-inverse to account for potential differences in the agents' power capabilities. Finally, simulation and experimental results with two robotic arms verify the theoretical findings.

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Section: B Prescribed Performance Controlmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

“…O and d ′ i , respectively, ∀i ∈ N . Hence, from(10) and(11), we obtaind(x(t)) ≤ d := d ′ O + i∈N { p…”

mentioning

confidence: 99%

See 2 more Smart Citations

Robust Cooperative Manipulation Without Force/Torque Measurements: Control Design and Experiments

Verginis

Mastellaro

Dimarogonas

2020

IEEE Trans. Contr. Syst. Technol.

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“…The force control component focuses on controlling the interaction forces between the object and the environment. It ensures that the forces applied to the object are within specified limits, preventing excessive forces that could potentially damage the object or the robots [54,80,88,94,99,125,149,[151][152][153][154].…”

Section: Control Algorithm Variations For Cooperative Resolutionmentioning

confidence: 99%

Cooperative Robot Manipulators Dynamical Modeling and Control: An Overview

Ghorbanpour

2023

Dynamics

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Robot manipulators possess the capability to autonomously execute complex sequences of actions. Their proficiency in handling challenging and hazardous tasks has led to their widespread adoption across diverse sectors, including industry, business, household appliances, rehabilitation, and many more. However, certain tasks prove to be challenging for individual robots, primarily due to constraints in their structure and limited degrees of freedom. Cooperative robot manipulators (CRMs) emerge as a compelling solution when dealing with large, heavy, or flexible payloads. The utilization of CRMs offers a host of benefits, including enhanced manipulation performance achieved through the synergy of sensing and actuation capabilities or by tapping into increased redundancy. Numerous techniques have been devised for the control and dynamical modeling of CRMs. Nevertheless, the field continues to present technical challenges and scientific inquiries. To inspire and facilitate further research and development in this realm, this review aims to consolidate the current body of knowledge pertaining to CRMs kinematics, dynamics modeling, and various control methodologies used for payload manipulation via CRMs.

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