Trajectory planning of robot manipulators by using spline function approach

Xu, Xiangrong; Wang, Xiaogang; Feng, Qin

doi:10.1109/wcica.2000.863436

Cited by 3 publications

(2 citation statements)

References 4 publications

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“…If we use only cubic polynomials for trajectory planning, the angular acceleration is discontinuous, and using only VOLUME 11, 2023 five-degree polynomials for trajectory planning will result in more computation. Xu et al [33] proposed a 3-5-3 spline splicing method, which can specify the angular velocity at the intermediate target point arbitrarily, and the angular acceleration is continuous. This paper uses a 3-5-3 polynomial curve to fit the starting, intermediate, and ending points.…”

Section: B Trajectory Constructionmentioning

confidence: 99%

Robot Time Optimal Trajectory Planning Based on Improved Simplified Particle Swarm Optimization Algorithm

Sun

et al. 2023

IEEE Access

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In order to tackle the robot trajectory planning problem with the short running time as the optimization goal, a time-optimal trajectory planning algorithm was presented based on improved simplified particle swarm optimization (ISPSO). The robot's trajectory was constructed by 3-5-3 polynomial interpolation in the joint space of the robot. Under the condition of satisfying the velocity constraint, the objective function was constructed by the sum of the time intervals between each node. ISPSO was used to optimize the objective function. The algorithm was improved by optimizing the inertia weight updating method and introducing a golden sine segmentation algorithm as an optimization operator. Compared with other particle swarm optimization algorithms, ISPSO had higher search velocity and accuracy. The effectiveness of the proposed algorithm was demonstrated through simulations using the PUMA 560 industrial robot, which resulted in a 19% reduction in time compared to the simplified particle swarm algorithm. The simulation results show that ISPSO achieved time optimization under the condition of velocity constraint, which proved its superiority in trajectory planning.

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Section: B Trajectory Constructionmentioning

confidence: 99%

Robot Time Optimal Trajectory Planning Based on Improved Simplified Particle Swarm Optimization Algorithm

Sun

et al. 2023

IEEE Access

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“…Improving the interpolation order of the polynomial and deploying piecewise interpolation methods smooth the trajectory. Xu et al [1] proposed the 3-5-3 spline function method for smoothed robot trajectory planning; this was a valuable contribution to the literature, The associate editor coordinating the review of this manuscript and approving it for publication was Luigi Biagiotti . but the scholars did not consider interpolation time.…”

Section: Introductionmentioning

confidence: 99%

Robot Time-Optimal Trajectory Planning Based on Improved Cuckoo Search Algorithm

et al. 2020

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The trajectory planning time is uncertain when there is no velocity constraint in the joint space of an operating robot. This paper proposes a 3-5-3 polynomial interpolation trajectory planning algorithm based on improved cuckoo search algorithm (ICS) which functions under a velocity constraint. Kinematics analysis of the robot is conducted and the 3-5-3 polynomial interpolation function is established as the foundation for trajectory planning. The size of the step size control factor is set as a variant which varies with the number of iterations, which accelerates the algorithm's convergence and prevents premature falling into the local optimal solution, both problems in the traditional cuckoo search algorithm where the step size control factor is fixed. The proposed algorithm was used to optimize the trajectory of a test robot with interpolation time as the search space for optimization. Any interpolation time that did not meet the speed constraint was eliminated to secure the shortest possible robot running time. The UR robot was taken as a research object to simulate the joint motion trajectory planning in MATLAB. The proposed algorithm performed well and better realized the time-optimal trajectory under the constraint of speed compared to the traditional cuckoo search algorithm, particle swarm optimization algorithm, and genetic algorithm.INDEX TERMS Improved cuckoo search algorithm, time-optimal, robot, trajectory planning, polynomial interpolation.

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