Cooperative Manipulation for a Mobile Dual-Arm Robot Using Sequences of Dynamic Movement Primitives

Zhao, Ting; Deng, Mingdi; Li, Zhijun; Hu, Yingbai

doi:10.1109/tcds.2018.2868921

Cited by 27 publications

(16 citation statements)

References 34 publications

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“…Two simulation examples, including the compared tracking of the planar three-link robot with the previous studies [35], the cooperative comparison of three-link dual-arms with the previous studies [2]- [5], [10], [29] validate the computational effectiveness and superior performance. In the future, the implementation of smart chef is considered [37], [38], or the applications of mobile dual arm for the payload carrying using visual navigation [39].…”

Section: Discussionmentioning

confidence: 99%

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Tracking and Cooperative Designs of Robot Manipulators Using Adaptive Fixed-Time Fault-Tolerant Constraint Control

Hwang

2020

IEEE Access

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At the outset, a nonlinear dynamic system for the generalized robots with input constraint is given to design an adaptive fixed-time fault-tolerant constraint control (AFTFTCC) for trajectory tracking. The proposed AFTFTCC includes a nonlinear filtering tracking error, which can shape the system response. As the operating point is in the neighborhood of the zero nonlinear filtering tracking error, nonlinear filtering gains are increasing to accelerate its tracking ability. The skew-symmetric matrix's condition for the timederivative of the inertia matrix and Coriolis and centrifugal force matrix is not required. The upper bound of uncertainties is learned to improve system performance. The stabilities of the closed-loop system are verified by the Lyapunov stability theory. Without true force feedback, the cooperative task of multiple robots with multiple arms is also addressed by the proposed AFTFTCC. Finally, two examples, including the trajectory tracking control of planar three-link robot arm and the cooperative control of dual planar three-link robot arms, are employed to validate the effectiveness and robustness of the proposed control. INDEX TERMS Adaptive fixed-time fault-tolerant constraint control, nonlinear filtering tracking error and gain, trajectory tracking of robot, cooperative control of multiple robots, Lyapunov stability theory.

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Section: Discussionmentioning

confidence: 99%

“…From (12) and (37), the following result is obtained. (38) Taking its time-derivative of V ei (t) = e T q i (t)e q i (t)/2 and substituting (38) (39) where α ei , β ei and γ ei are expressed in (28). According to Lemma 1, the fixed-time zero filtering tracking error in (27)-(28) is achieved.…”

Section: Tracking Design Via Aftftccmentioning

confidence: 99%

Tracking and Cooperative Designs of Robot Manipulators Using Adaptive Fixed-Time Fault-Tolerant Constraint Control

Hwang

2020

IEEE Access

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“…In addition, hybrid collaborative arm systems exist, having one end fixed to a mobile base, which is free to perform tasks in an environment dexterously (these are often called mobile manipulators). Mobile manipulators allow for a theoretically infinite workspace for the manipulator (see the following citations for more information about the modern application of this technology: Zhao et al (2018) ; Wu et al (2019) ; Balatti et al (2020) ). Such hybrid robotic systems can be used in healthcare centers for manipulating and moving materials, and even can assist with delivering physical assistance for patients, reducing physical interaction between personnel and between patients and caregivers.…”

Section: Categories Of Robotic Systems For Boosting Care Deliverymentioning

confidence: 99%

Review: How Can Intelligent Robots and Smart Mechatronic Modules Facilitate Remote Assessment, Assistance, and Rehabilitation for Isolated Adults With Neuro-Musculoskeletal Conditions?

2021

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Worldwide, at the time this article was written, there are over 127 million cases of patients with a confirmed link to COVID-19 and about 2.78 million deaths reported. With limited access to vaccine or strong antiviral treatment for the novel coronavirus, actions in terms of prevention and containment of the virus transmission rely mostly on social distancing among susceptible and high-risk populations. Aside from the direct challenges posed by the novel coronavirus pandemic, there are serious and growing secondary consequences caused by the physical distancing and isolation guidelines, among vulnerable populations. Moreover, the healthcare system’s resources and capacity have been focused on addressing the COVID-19 pandemic, causing less urgent care, such as physical neurorehabilitation and assessment, to be paused, canceled, or delayed. Overall, this has left elderly adults, in particular those with neuromusculoskeletal (NMSK) conditions, without the required service support. However, in many cases, such as stroke, the available time window of recovery through rehabilitation is limited since neural plasticity decays quickly with time. Given that future waves of the outbreak are expected in the coming months worldwide, it is important to discuss the possibility of using available technologies to address this issue, as societies have a duty to protect the most vulnerable populations. In this perspective review article, we argue that intelligent robotics and wearable technologies can help with remote delivery of assessment, assistance, and rehabilitation services while physical distancing and isolation measures are in place to curtail the spread of the virus. By supporting patients and medical professionals during this pandemic, robots, and smart digital mechatronic systems can reduce the non-COVID-19 burden on healthcare systems. Digital health and cloud telehealth solutions that can complement remote delivery of assessment and physical rehabilitation services will be the subject of discussion in this article due to their potential in enabling more effective and safer NMSDK rehabilitation, assistance, and assessment service delivery. This article will hopefully lead to an interdisciplinary dialogue between the medical and engineering sectors, stake holders, and policy makers for a better delivery of care for those with NMSK conditions during a global health crisis including future pandemics.

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“…So they proposed the coupling of originally independent robotic trajectories by expanding framework of DMPs, which enables the bimanual execution tightly coupled for cooperative tasks [17]. Zhao et al presented a reinforcement learning (RL) algorithm called the policy improvement with path integrals for sequences of DMPs (SDMPs) to learn and adjust recorded trajectories of dual-arm robot cooperative manipulation [18]. Colome et al studied simultaneously learning a DMPcharacterized robot motion and the joint couplings through linear dimensionality reduction (DR), which provides valuable qualitative information leading to a reduced and intuitive algebraic description of such motion [19].…”

Section: Introductionmentioning

confidence: 99%

DMPs-based skill learning for redundant dual-arm robotic synchronized cooperative manipulation

Wang

Shi

2021

Complex Intell. Syst.

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Dual-arm robot manipulation is applicable to many domains, such as industrial, medical, and home service scenes. Learning from demonstrations is a highly effective paradigm for robotic learning, where a robot learns from human actions directly and can be used autonomously for new tasks, avoiding the complicated analytical calculation for motion programming. However, the learned skills are not easy to generalize to new cases where special constraints such as varying relative distance limitation of robotic end effectors for human-like cooperative manipulations exist. In this paper, we propose a dynamic movement primitives (DMPs) based skills learning framework for redundant dual-arm robots. The method, with a coupling acceleration term to the DMPs function, is inspired by the transient performance control of Barrier Lyapunov Functions. The additional coupling acceleration term is calculated based on the constant joint distance and varying relative distance limitations of end effectors for object-approaching actions. In addition, we integrate the generated actions in joint space and the solution for a redundant dual-arm robot to complete a human-like manipulation. Simulations undertaken in Matlab and Gazebo environments certify the effectiveness of the proposed method.

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Cooperative Manipulation for a Mobile Dual-Arm Robot Using Sequences of Dynamic Movement Primitives

Cited by 27 publications

References 34 publications

Tracking and Cooperative Designs of Robot Manipulators Using Adaptive Fixed-Time Fault-Tolerant Constraint Control

Tracking and Cooperative Designs of Robot Manipulators Using Adaptive Fixed-Time Fault-Tolerant Constraint Control

Review: How Can Intelligent Robots and Smart Mechatronic Modules Facilitate Remote Assessment, Assistance, and Rehabilitation for Isolated Adults With Neuro-Musculoskeletal Conditions?

DMPs-based skill learning for redundant dual-arm robotic synchronized cooperative manipulation

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