Robust variable admittance control for human–robot co-manipulation of objects with unknown load

Mujica, Martín; Crespo, Martín; Benoussaad, Mourad; Junco, Sergio; Fourquet, Jean-Yves

doi:10.1016/j.rcim.2022.102408

Cited by 28 publications

(14 citation statements)

References 18 publications

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“…Re s a sa (11) Using the Mittag-Leffler function to describe the above fractional order differential equation, and then according to the Laplace transform of the Mittag-Leffler function the following inverse transformation can be obtained:…”

Section: Fractional Order Variable Damping Admittance Controlmentioning

confidence: 99%

Research on human-robot collaboration method for parallel robots oriented to segment docking

Sun,

Wang,

et al. 2024

Preprint

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In the field of aerospace, large and heavy cabin segments present a significant challenge in assembling space engines. The considerable inertial force of cabin segments’ mass causes unexpected motion during docking, leading to segment collisions and difficulty in ensuring precise engine segment docking. Traditional manual docking utilizes workers' expertise, yet the labor-intensive nature and low productivity are unsuitable for practical applications. Human-robot collaboration can effectively integrate the advantages of humans and robots. Additionally, parallel robots, known for their precision and load-bearing ability, are widely employed in precise assembly tasks under heavy loads. Thus, human-parallel-robot collaboration serves as an excellent solution for these challenges. This paper proposes an easily implementable framework, employing human-parallel-robot collaboration technology for cabin segment docking in production. A fractional-order variable damping admittance control and an inverse dynamics robust controller are suggested to improve the robot's compliance, responsiveness, and trajectory tracking accuracy in collaboration. This allows operators to dynamically adjust the robot's motion in real-time, counterbalancing inertial forces and preventing collisions. Segment docking assembly experiments are conducted utilizing the Stewart platform in this study. The results show that the proposed method enables the robot to quickly respond to interaction forces, ensuring compliance and stable motion accuracy, even under unknown interaction forces.

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Section: Fractional Order Variable Damping Admittance Controlmentioning

confidence: 99%

Research on human-robot collaboration method for parallel robots oriented to segment docking

Sun,

Wang,

et al. 2024

Preprint

View full text Add to dashboard Cite

show abstract

“…In the context of path and motion planning for robotics systems, model-based control systems are still widely used despite being challenged by data-driven approaches. Model-based control theory can offer advantages such as explainability and performance and safety guarantees [48], which are still lacking in AI-based methods. Developing trust in autonomous systems is an active research area that will be central to achieving symbiotic human-robot collaboration.…”

Section: Computational Intelligencementioning

confidence: 99%

Human-Centric Digital Twins in Industry: A Comprehensive Review of Enabling Technologies and Implementation Strategies

Asad

Khan

Khalid

et al. 2023

Sensors

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The last decade saw the emergence of highly autonomous, flexible, re-configurable Cyber-Physical Systems. Research in this domain has been enhanced by the use of high-fidelity simulations, including Digital Twins, which are virtual representations connected to real assets. Digital Twins have been used for process supervision, prediction, or interaction with physical assets. Interaction with Digital Twins is enhanced by Virtual Reality and Augmented Reality, and Industry 5.0-focused research is evolving with the involvement of the human aspect in Digital Twins. This paper aims to review recent research on Human-Centric Digital Twins (HCDTs) and their enabling technologies. A systematic literature review is performed using the VOSviewer keyword mapping technique. Current technologies such as motion sensors, biological sensors, computational intelligence, simulation, and visualization tools are studied for the development of HCDTs in promising application areas. Domain-specific frameworks and guidelines are formed for different HCDT applications that highlight the workflow and desired outcomes, such as the training of AI models, the optimization of ergonomics, the security policy, task allocation, etc. A guideline and comparative analysis for the effective development of HCDTs are created based on the criteria of Machine Learning requirements, sensors, interfaces, and Human Digital Twin inputs.

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“…On the one hand, force control methods used in robotic systems primarily fall into the categories of impedance/admittance control [11] and position/force hybrid control [12]. This includes variable impedance control [13], adaptive admittance control [14], and robust impedance control [15,16]. In general, impedance control is superior to position/force hybrid control when dealing with dynamic contact control between robotic manipulators and environment.…”

Section: Introductionmentioning

confidence: 99%

Robust Adaptive Nonlinear Admittance Control of Robotic Manipulators with Extra-Intra Uncertainties and Disturbances

Zhang,

Chen,

Zhang

2024

Preprint

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This paper focuses on achieving rapid convergence in finite time for robust trajectory tracking of robotic manipulators, which upper-bound uncertainties are unknown. To address the issues of excessive control torque and control reversal at the initial stage, a novel Robust Adaptive Fast Terminal Sliding Mode Control (RAF-TSMC) method is developed. The proposed method provides faster transient response, higher steady-state tracking accuracy, and can eliminate singularities and mitigate chattering effects. To enhance the physical collaboration in human-robot interactions, a novel Nonlinear Admittance Control method with RAF-TSMC is proposed, which benefits from adaptive compliance characteristics of Nonlinear Admittance Control with RAF-TSMC. This improves suppleness and flexibility of human-robot interaction in uncertain environments. Finally, the proposed controller is validated using a two-link robotic manipulator subjected to uncertainty and external forces. The results demonstrate that the proposed RAF-TSMC controller can effectively minimize tracking errors and convergence time, and the proposed Nonlinear Admittance Control with RAF-TSMC can enhances the flexibility and adaptability of the robot system.

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Robust variable admittance control for human–robot co-manipulation of objects with unknown load

Cited by 28 publications

References 18 publications

Research on human-robot collaboration method for parallel robots oriented to segment docking

Research on human-robot collaboration method for parallel robots oriented to segment docking

Human-Centric Digital Twins in Industry: A Comprehensive Review of Enabling Technologies and Implementation Strategies

Robust Adaptive Nonlinear Admittance Control of Robotic Manipulators with Extra-Intra Uncertainties and Disturbances

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