AI-driven rehabilitation and assistive robotic system with intelligent PID controller based on RBF neural networks

Xiao, Wei; Chen, Kai; Fan, Jiaming; Hou, Yifan; Kong, Weifei; Guo, Dan

doi:10.1007/s00521-021-06785-y

Cited by 11 publications

(8 citation statements)

References 42 publications

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“…1 ) has generic nature of the equipment, technology, and study targets. The ingenious and convenient modelling and calculation method is in line with the physiological characteristics of the upper limb, providing new ideas for upper-limb motion research and theoretical support for upper-limb mirroring rehabilitation 21 , 53 , 54 , motor function assessment 42 , 55 , 56 , upper-limb motion recognition 36 , 57 , etc. In conclusion, this study achieved ingenious and convenient kinematic analysis and description that better matched the physiological characteristics of the human upper limb by utilizing multi-spatial fusion, and provided theoretical support to advance the engineering application of upper limb modelling and motion extraction in various research fields.…”

Section: Introductionmentioning

confidence: 91%

Upper limb modeling and motion extraction based on multi-space-fusion

Wang,

Guo,

Pei

et al. 2023

Sci Rep

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Modeling and motion extraction of human upper limbs are essential for interpreting the natural behavior of upper limb. Owing to the high degrees of freedom (DOF) and highly dynamic nature, existing upper limb modeling methods have limited applications. This study proposes a generic modeling and motion extraction method, named Primitive-Based triangular body segment method (P-BTBS), which follows the physiology of upper limbs, allows high accuracy of motion angles, and describes upper-limb motions with high accuracy. For utilizing the upper-limb modular motion model, the motion angles and bones can be selected as per the research topics (The generic nature of the study targets). Additionally, P-BTBS is suitable in most scenarios for estimating spatial coordinates (The generic nature of equipment and technology). Experiments in continuous motions with seven DOFs and upper-limb motion description validated the excellent performance and robustness of P-BTBS in extracting motion information and describing upper-limb motions, respectively. P-BTBS provides a new perspective and mathematical tool for human understanding and exploration of upper-limb motions, which theoretically supports upper-limb research.

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Section: Introductionmentioning

confidence: 91%

Upper limb modeling and motion extraction based on multi-space-fusion

Wang,

Guo,

Pei

et al. 2023

Sci Rep

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“…Robots that can monitor rehabilitation play a pivotal role in assisting patients to recover from injuries and surgeries, which provides guidance for physical therapy exercises, ensuring that patients perform them correctly and consistently [202,203]. With camera-based intelligent sensing, robots can monitor a patient's movements, provide feedback, and adjust the intensity of exercises based on the patient's progress [204,205].…”

Section: Camera-based Health Monitoring Robotmentioning

confidence: 99%

Deformable Morphing and Multivariable Stiffness in the Evolutionary Robotics

Feng,

Xue,

et al. 2023

IJAMM

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Review Deformable Morphing and Multivariable Stiffness in the Evolutionary Robotics Huijuan Feng , Yahui Xue , Honggeng Li , Zhao Tang , Wenjin Wang , Zhenhua Wei , Guosong Zeng , Mingwu Li , and Jian S. Dai * Shenzhen Key Laboratory of Intelligent Robotics and Flexible Manufacturing Systems, Institute for Robotics, Southern University of Science and Technology, Shenzhen 518055, China * Correspondence: daijs@sustech.edu.cn Received: 8 October 2023 Accepted: 20 October 2023 Published: 24 October 2023 Abstract: This paper is to review and discuss the current state-of-the-art and future direction of the evolutionary robotics in its deformable morphing and multivariable stiffness. Structural morphing and shape morphing are the center piece of the deformable morphing and lead to the study of both reversible and irreversible deformabilities in morphing that form a basis for future evolutionary robotics. Having thoroughly reviewed the techniques, this paper reviews the science and technology in multivariable stiffness for evolutionary robotics particularly for reconfigurable evolutionary robots and their various applications. This leads to a review of dynamics with the model order reduction, and leads to a review of actuation strategy of metamorphic mechanisms that is a core of the structure of the evolutionary robotics. As such, the paper further reviews camera-based evolutionary robots with intelligent sensing, intelligent controlling and health monitoring, and then the real-time control of high-dimensional robots which cast light on tackling the evolutionary robot control, with the fault monitoring and maintenance. The paper in general presents the future prospects for the evolutionary robots in their deformable morphing and multivariable stiffness with the control of high-dimensional robots and their applications in intelligent infrastructure construction and maintenance.

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“…For example, Djaneye-Boundjou et al ( 2016) developed a stable adaptive particle swarm optimizer to automatically adjust the parameters of PID gain; Shamseldin and Mohamed A (Shamseldin, 2021) improved the optimization model by simulating how covid-19 spreads and infuses, and proposed an efficient covid-19 optimization algorithm to obtain the optimal value of the PD/PID cascade controller. Xiao et al (2023) also used RBF neural network to improve the tracking performance of the manipulator by updating PID parameters through errors between network output and system output.…”

Section: Introductionmentioning

confidence: 99%

Control and physical verification of 6-DOF manipulator for power inspection robots based on expert PID algorithm

Jiang,

Wang,

Liu

2024

Front. Energy Res.

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To enhance the performance of power inspection robots in intricate nuclear power stations, it is necessary to improve their response speed and accuracy. This paper uses the manipulator of the power inspection robot as the primary research object, and unlike previous control algorithm research, which only remained in the software simulation stage, we constructed a set of physical verification platforms based on CAN communication and physically verified the robotic arm’s control algorithm. First, the forward motion model is established based on the geometric structure of the manipulator and D-H parameter method, and the kinematic equation of the manipulator is solved by combining geometric method and algebraic method. Secondly, in order to conduct comparison tests, we designed PID controllers and expert PID controllers by utilising the expertise of experts. The results show that compared with the traditional PID algorithm, the expert PID algorithm has a faster response speed in the control process of the manipulator. It converges quickly in 0.75 s and has a smaller overshoot, with a maximum of only 6.9%. This confirms the expert PID algorithm’s good control effect on the robotic arm, allowing the six-degree-of-freedom robotic arm to travel more accurately and swiftly along the trajectory of the target point.

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AI-driven rehabilitation and assistive robotic system with intelligent PID controller based on RBF neural networks

Cited by 11 publications

References 42 publications

Upper limb modeling and motion extraction based on multi-space-fusion

Upper limb modeling and motion extraction based on multi-space-fusion

Deformable Morphing and Multivariable Stiffness in the Evolutionary Robotics

Control and physical verification of 6-DOF manipulator for power inspection robots based on expert PID algorithm

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