Smooth Trajectory Planning for a Cable-Driven Waist Rehabilitation Robot Using Quintic NURBS

Jiang, Meng; Yang, Zhengmeng; Li, Yuan; Sun, Zhi; Zi, Bin

doi:10.1007/978-3-030-89095-7_53

Cited by 2 publications

(2 citation statements)

References 12 publications

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“…Using quintic B-spline curves with higher degrees of freedom can better satisfy these constraints and limitations. The shape of the fifth-degree B-spline curve can be flexibly controlled by adjusting the positions and weights of the control points [ 34 ]. This enables the robotic arm to move smoothly and precisely without collisions, reaching the desired positions.…”

Section: Rrt*smart-ad Algorithmmentioning

confidence: 99%

Cooperative Dynamic Motion Planning for Dual Manipulator Arms Based on RRT*Smart-AD Algorithm

Long,

Li,

Zhou

et al. 2023

Sensors

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Intelligent manufacturing requires robots to adapt to increasingly complex tasks, and dual-arm cooperative operation can provide a more flexible and effective solution. Motion planning serves as a crucial foundation for dual-arm cooperative operation. The rapidly exploring random tree (RRT) algorithm based on random sampling has been widely used in high-dimensional manipulator path planning due to its probability completeness, handling of high-dimensional problems, scalability, and faster exploration speed compared with other planning methods. As a variant of RRT, the RRT*Smart algorithm introduces asymptotic optimality, improved sampling techniques, and better path optimization. However, existing research does not adequately address the cooperative motion planning requirements for dual manipulator arms in terms of sampling methods, path optimization, and dynamic adaptability. It also cannot handle dual-manipulator collaborative motion planning in dynamic scenarios. Therefore, in this paper, a novel motion planner named RRT*Smart-AD is proposed to ensure that the dual-arm robot satisfies obstacle avoidance constraints and dynamic characteristics in dynamic environments. This planner is capable of generating smooth motion trajectories that comply with differential constraints and physical collision constraints for a dual-arm robot. The proposed method includes several key components. First, a dynamic A* cost function sampling method, combined with an intelligent beacon sampling method, is introduced for sampling. A path-pruning strategy is employed to improve the computational efficiency. Strategies for dynamic region path repair and regrowth are also proposed to enhance adaptability in dynamic scenarios. Additionally, practical constraints such as maximum velocity, maximum acceleration, and collision constraints in robotic arm applications are analyzed. Particle swarm optimization (PSO) is utilized to optimize the motion trajectories by optimizing the parameters of quintic non-uniform rational B-splines (NURBSs). Static and dynamic simulation experiments verified that the RRT*Smart-AD algorithm for cooperative dynamic path planning of dual robotic arms outperformed biased RRT* and RRT*Smart. This method not only holds significant practical engineering significance for obstacle avoidance in dual-arm manipulators in intelligent factories but also provides a theoretical reference value for the path planning of other types of robots.

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Section: Rrt*smart-ad Algorithmmentioning

confidence: 99%

Cooperative Dynamic Motion Planning for Dual Manipulator Arms Based on RRT*Smart-AD Algorithm

Long,

Li,

Zhou

et al. 2023

Sensors

View full text Add to dashboard Cite

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“…Hwang et al [26] presented a scheme to suppress unwanted oscillatory motions of the payload of a four-cable-driven CDPR based on a zero-vibration input-shaping scheme, and the advantage of the proposed scheme is that it is possible to generate an oscillation-free trajectory based on a ZV inputshaping scheme, and moreover, a series of computer simulations and experiments to verify the effectiveness of the proposed method were conducted for three-dimensional motions of a CBPR with four cables. A smooth trajectory planning algorithm to enhance the smoothness of the trajectory when used in rehabilitation training was proposed for a cabledriven waist rehabilitation robot by employing an improved quintic non-uniform rational B-splines [27]. As demonstrated in [28], a novel methodology for the identification of the inertial parameters of the end-effector, based on the use of internal-dynamics equations and free-motion excitations, was proposed for the underactuated cable-driven parallel robots, where the optimal free-motion trajectories were investigated to obtain optimal identification results.…”

Section: Pick-and-place Trajectory Planningmentioning

confidence: 99%

Pick–and–Place Trajectory Planning and Robust Adaptive Fuzzy Tracking Control for Cable–Based Gangue–Sorting Robots with Model Uncertainties and External Disturbances

et al. 2022

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A suspended cable−based parallel robot (CBPR) composed of four cables and an end−grab is employed in a pick−and−place operation of moving target gangues (MTGs) with different shapes, sizes, and masses. This paper focuses on two special problems of pick−and−place trajectory planning and trajectory tracking control of the cable−based gangue−sorting robot in the operation space. First, the kinematic and dynamic models for the cable−based gangue−sorting robots are presented in the presence of model uncertainties and unknown external disturbances. Second, to improve the sorting accuracy and efficiency of sorting system with cable−based gangue−sorting robot, a four-phase pick−and−place trajectory planning scheme based on S-shaped acceleration/deceleration algorithm and quintic polynomial trajectory planning method is proposed, and moreover, a robust adaptive fuzzy tracking control strategy is presented against inevitable uncertainties and unknown external disturbances for trajectory tracking control of the cable−based gangue−sorting robot, where the stability of a closed-loop control scheme is proved with Lyapunov stability theory. Finally, the performances of pick−and−place trajectory planning scheme and robust adaptive tracking control strategy are evaluated through different numerical simulations within Matlab software. The simulation results show smoothness and continuity of pick−and−place trajectory for the end−grab as well as the effectiveness and efficiency to guarantee a stable and accurate pick−and−place trajectory tracking process even in the presence of various uncertainties and external disturbances. The pick−and−place trajectory generation scheme and robust adaptive tracking control strategy proposed in this paper lay the foundation for accurate sorting of MTGs with the robot.

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Smooth Trajectory Planning for a Cable-Driven Waist Rehabilitation Robot Using Quintic NURBS

Cited by 2 publications

References 12 publications

Cooperative Dynamic Motion Planning for Dual Manipulator Arms Based on RRT*Smart-AD Algorithm

Cooperative Dynamic Motion Planning for Dual Manipulator Arms Based on RRT*Smart-AD Algorithm

Pick–and–Place Trajectory Planning and Robust Adaptive Fuzzy Tracking Control for Cable–Based Gangue–Sorting Robots with Model Uncertainties and External Disturbances

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