Accessibility and Trajectory Planning of Cutter Changing Robot Arm for Large-Diameter Slurry Shield

Yang, Mei; Zeng, Guiying; Ren, Yongjie; Lin, Laikuang; Ke, Wei; Liu, Y.

doi:10.5755/j02.mech.30386

Cited by 6 publications

(3 citation statements)

References 28 publications

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“…The most widely modeled approach is the Euler-Lagrange equation, where the RA is represented as shown in Eq. (1).…”

Section: A Tdra's Dynamics Modeling and Its Tracking Controllermentioning

confidence: 99%

“…In Eq. ( 7), 1 z is the error, y and d y are the actual and desired angles, respectively, and  denotes the fuzzy system design. As for the two subsystems of the controller, its stability analysis is done by using Lyapunov function, as shown in Eq.…”

Section: B Tdra Sliding Membrane Control and Trajectory Trackingmentioning

confidence: 99%

“…Robot arm (RA) is a device that is programmed to move and manipulate a manipulator to perform a grasp-and-place operation [1]. With the development of computers, RAs are used in engineering fields such as ecosystem monitoring, aerospace and medical engineering [2][3][4].…”

Section: Introductionmentioning

confidence: 99%

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Tendon-Driven Robotic Arm Control Method Based on Radial Basis Function Adaptive Tracking Algorithm

Fang

2024

ijacsa

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With the rapid development of intelligent technology, robotic arms are widely used in different fields. The study combines the tendon drive theory and radial basis function neural network to construct the robotic arm model, and then combines the back-stepping method and non-singular fast terminal sliding mode to improve the controller and system optimization of the tendon drive robotic arm model. Simulation tests on commercial mathematical software platforms yielded that joint 2 achieves stable overlap of position trajectory and velocity trajectory after 0.2s and 0.5s with errors of 1° and 1°/s, respectively. Radial basis function neural network approximation of robotic arm error converged to the true value at 14s. The optimized joint achieved the accuracy of trajectory tracking after 0.2s. Also the control torque of joint 2 changes at 1.5s, 4.5s and 8s and its change is small. The tendon tension curve was smoother and more stable in the range of -0.05N~0.0.5N to show that the robotic arm model has superiority after the optimization of the controller, and the interference observer had accurate estimation of the tracking trajectory of the tendon-driven robotic arm. Therefore, the radial basis function-based adaptive tracking algorithm had higher accuracy for the tendon-driven robotic arm model and provided technical reference for the control system of the intelligent robotic arm.

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“…The most widely modeled approach is the Euler-Lagrange equation, where the RA is represented as shown in Eq. (1).…”

Section: A Tdra's Dynamics Modeling and Its Tracking Controllermentioning

confidence: 99%

Section: B Tdra Sliding Membrane Control and Trajectory Trackingmentioning

confidence: 99%

See 1 more Smart Citation

Tendon-Driven Robotic Arm Control Method Based on Radial Basis Function Adaptive Tracking Algorithm

Fang

2024

ijacsa

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Trajectory planning and automatic docking of LNG five-axis loading arm

Jiang,

Chen,

Chen

et al. 2024

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PurposeIn response to the challenges posed by the conventional manual flange docking method in the LNG (Liquefied Natural Gas) loading process, such as low positioning accuracy, constraints on production efficiency and safety hazards, this study analyzed the LNG five-axis loading arm’s main functions and structural characteristics.Design/methodology/approachAn automated solution for the joints of the LNG loading arm was designed. The forward kinematic model of the LNG loading arm was established using the Denavit–Hartenberg (D-H) parameter method, and its workspace was analyzed. The Newton–Raphson iteration method was employed to solve the inverse kinematics of the LNG loading arm, facilitating trajectory planning. The relationship between the target position and the joint variables was established to verify the stability of the arm’s motion. Flange center identification was achieved using the Hough transform function. Based on the ROS platform, combined with Gazebo and Rviz, an experimental simulation of automatic docking of the LNG loading arm was conducted.FindingsThe docking errors in the XYZ directions were all less than 0.8 mm, meeting the required docking accuracy. Moreover, the motion performance of the loading arm during docking was smooth and free of abrupt changes, validating its capability to accomplish the automatic docking task.Originality/valueThe proposed trajectory planning and automatic docking scheme can be used for the rapid filling of LNG filling arms and LNG tankers to improve the efficiency of LNG transportation. In guiding the docking, the proposed automatic docking scheme is an accurate and efficient way to improve safety.

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Design and Simulation of Electro-hydraulic Servo System of Shield Cutter-changing Robot for Shield Machine

Tian,

Chen,

Yang

et al. 2024

2024 9th Asia-Pacific Conference on Intelligent Robot Systems (ACIRS)

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Accessibility and Trajectory Planning of Cutter Changing Robot Arm for Large-Diameter Slurry Shield

Cited by 6 publications

References 28 publications

Tendon-Driven Robotic Arm Control Method Based on Radial Basis Function Adaptive Tracking Algorithm

Tendon-Driven Robotic Arm Control Method Based on Radial Basis Function Adaptive Tracking Algorithm

Trajectory planning and automatic docking of LNG five-axis loading arm

Design and Simulation of Electro-hydraulic Servo System of Shield Cutter-changing Robot for Shield Machine

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