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Relevant bibliographies by topics / Quintic polynomial trajectory

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Academic literature on the topic 'Quintic polynomial trajectory'

Author: Grafiati

Published: 3 June 2025

Last updated: 23 June 2025

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Journal articles on the topic "Quintic polynomial trajectory"

1

Du, Qin Jun, Xue Yi Zhang, and Shi Long Zhai. "Humanoid Robot Arm Kinematics Modeling and Motion Planning." Applied Mechanics and Materials 644-650 (September 2014): 247–50. http://dx.doi.org/10.4028/www.scientific.net/amm.644-650.247.

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This paper establishes the kinematics model of humanoid robot arm, the arm forward kinematics equations were built and solved, based on the advantages of CCD (Cyclic Coordinate Descent) and BFS (Broyden-Fletcher-Shanno) algorithm to solve the inverse kinematics of humanoid robot arm. In the joint space, using cubic polynomial and quintic polynomial interpolation method respectively for each joint angle interpolation. Cubic polynomial trajectory planning can meet the point-to-point movement in general, but can not guarantee the continuity of acceleration of each point; Quintic polynomial trajectory planning can ensure that each point is continuous of the joint angle, angular velocity, and angular acceleration, so this polynomial method can meet the movement of the humanoid robot arm.

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Sun, Jun, Ling Lu, Jun Qing Chen, and Jiu Fu Jin. "Analysis of Gait Planning Method for Biped Robots." Advanced Materials Research 753-755 (August 2013): 1995–2000. http://dx.doi.org/10.4028/www.scientific.net/amr.753-755.1995.

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Biped robots research is mainly concentrated on the control system development and doing simulation, cubic spline interpolation method is widely applied to pre-gait planning work. This paper analyzed the robots walking process and calculated the joint trajectory curves of a walk cycle by using spline interpolation and the quintic polynomial fitting means, verifies that the result obtained by quintic polynomial algorithm tends to be more ideal, it is conducive to maintain walking stability and find the optimal joint angles. The paper provides a theoretical basis for optimizing robots trajectory planning.

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Shijie, Li. "Research Progress on Trajectory Planning of Industrial Robots." Current Journal of Applied Science and Technology 42, no. 2 (2023): 25–36. http://dx.doi.org/10.9734/cjast/2023/v42i24052.

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The research status of industrial robot trajectory planning is discussed in detail, and the applicable occasions of cubic polynomial interpolation, quintic polynomial interpolation, B-spline curve, mixed polynomial interpolation and other methods commonly used in basic trajectory planning are comprehensively analyzed. At the same time, various methods of optimal trajectory planning for industrial robots are comprehensively reviewed. The advantages and disadvantages of various methods are compared and the important research direction of optimal trajectory planning is prospected.

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Zhang, Yuelou, Lingshan Chen, and Ning Li. "Improved Quintic Polynomial Autonomous Vehicle Lane-Change Trajectory Planning Based on Hybrid Algorithm Optimization." World Electric Vehicle Journal 16, no. 5 (2025): 244. https://doi.org/10.3390/wevj16050244.

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A trajectory planning method is proposed to address the lane-changing problem in intelligent vehicles. The method is based on quintic polynomial improvement. The transit position is determined according to the position and state of motion of the vehicle and the obstacle vehicle; the lane-changing process is divided into two segments. The quintic polynomials are commonly applied in trajectory planning, respectively, in the two segments. According to the different characteristics of the lane-changing paths in the front and rear segments, a multi-objective optimization function with different weight coefficients is established. A safe and comfortable lane-changing trajectory is achieved through the improved particle swarm optimization algorithm. Real-time simulation tests of lane-changing method are conducted on the hardware-in-the-loop platform. The method can be used in different scenarios to plan safe and comfortable trajectories.

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Yang, Can, and Jie Liu. "Trajectory Tracking Control of Intelligent Driving Vehicles Based on MPC and Fuzzy PID." Mathematical Problems in Engineering 2023 (February 3, 2023): 1–24. http://dx.doi.org/10.1155/2023/2464254.

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To improve the stability and accuracy of quintic polynomial trajectory tracking, an MPC (model predictive control) and fuzzy PID (proportional-integral-difference)- based control method are proposed. A lateral tracking controller is designed by using MPC with rule-based horizon parameters. The lateral tracking controller controls the steering angle to reduce the lateral tracking errors. A longitudinal tracking controller is designed by using a fuzzy PID. The longitudinal controller controls the motor torque and brake pressure referring to a throttle/brake calibration table to reduce the longitudinal tracking errors. By combining the two controllers, we achieve satisfactory trajectory tracking control. Relative vehicle trajectory tracking simulation is carried out under common scenarios of quintic polynomial trajectory in the Simulink/Carsim platform. The result shows that the strategy can avoid excessive trajectory tracking errors which ensures a better performance for trajectory tracking with high safety, stability, and adaptability.

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Zhang, Wenjia, Weiwei Shang, Bin Zhang, Fei Zhang, and Shuang Cong. "Stiffness-based trajectory planning of a 6-DOF cable-driven parallel manipulator." Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science 231, no. 21 (2016): 3999–4011. http://dx.doi.org/10.1177/0954406216659893.

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The stiffness of the cable-driven parallel manipulator is usually poor because of the cable flexibility, and the existing methods on trajectory planning mainly take the minimum time and the optimal energy into account, not the stiffness. To solve it, the effects of different trajectories on stiffness are studied for a six degree-of-freedom cable-driven parallel manipulator, according to the kinematic model and the dynamic model. The condition number and the minimum eigenvalue of the dimensionally homogeneous stiffness matrix are selected as performance indices to analyze the stiffness changes during the motion. The simulation experiments are implemented on a six degree-of-freedom cable-driven parallel manipulator, to study the stiffness of three different trajectory planning approaches such as S-type velocity profile, quintic polynomial, and trigonometric function. The accelerations of different methods are analyzed, and the stiffness performances for the methods are compared after planning the point-to-point straight and the curved trajectories. The simulation results indicate that the quintic polynomial and S-type velocity profile have the optimal performance to keep the stiffness stable during the motion control and the travel time of the quintic polynomial can be optimized sufficiently while keeping stable.

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Li, Yang, Linbo Li, and Daiheng Ni. "Dynamic Trajectory Planning for Automated Lane Changing Using the Quintic Polynomial Curve." Journal of Advanced Transportation 2023 (September 15, 2023): 1–14. http://dx.doi.org/10.1155/2023/6926304.

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As one of the key algorithms in supporting AV (autonomous vehicle) to complete the LC (lane changing) maneuver, the LTP (LC trajectory planning) algorithm generates safe and efficient LC trajectory for the AV. This paper proposes a novel dynamic LTP algorithm based on the quintic polynomial curve. This algorithm is capable of adjusting LC trajectory according to the state changes of the surrounding driving environment. The formulation of our proposed algorithm mainly consists the underlying form of trajectory equation, the optimization objective function, the corresponding constrains, and the SQP (sequential quadratic programming) algorithm. For each planning step, the time-based quintic polynomial function is introduced to model the trajectory equation. The problem of solving the parameters of the corresponding equation is then transformed into an optimization problem, which takes driver’s safety, comfort, and efficiency into account. After that, the SQP algorithm is employed to solve this optimization problem. Finally, both numerical simulation and field-data validation are used to verify the effectiveness of our proposed algorithm. We anticipate that the research could provide certain valuable insights for developing more reliable LC algorithms for AVs.

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Reddy, A. Sridhar, V. V. M. J. Satish Chembuly, and V. V. S. Kesava Rao. "Modelling and Simulation of a Redundant Agricultural Manipulator with Virtual Prototyping." Journal of Robotics and Control (JRC) 4, no. 1 (2023): 83–94. http://dx.doi.org/10.18196/jrc.v4i1.17121.

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The development of autonomous robots for agricultural applications includes motion planning, fruit picking, and collision avoidance with surrounding environments, and these become challenging tasks. For harvesting applications, robust control of the manipulator is needed for the effective motion of the robot. Several combinations of Proportional(P)- Integrative(I)- Derivative(D) controllers are modelled and a simulation study was performed for trajectory tracking of a redundant manipulator in virtual agricultural environments. The article presents a comprehensive study on kinematic modelling and dynamic control of redundant manipulator for fruit-picking applications in virtual environments. The collisions with surrounding environment were eliminated using ‘bounding box technique’. The joint variables are obtained by constructing Inverse Kinematics (IK) problem and are determined using a classical optimization technique. Different controllers are modelled in the ‘Simulink’ environment and are tuned to generate error-free trajectory tracking during harvesting. The task space locations (TSLs) are considered as via-points, and joint variables at each TSLs are obtained by Sequential Quadratic Programming (SQP) technique. Joint-level trajectories are generated using Quintic and B-spline polynomials. For effective trajectory tracking, torque variations are controlled using the PID and Feedforward (FF) controller. The dynamic simulations of the robot manipulator are performed in Simscape Multibody software. Results show that the during the trajectory tracking of the manipulator, the Feed-forward controller performs best with Quintic polynomial trajectory.

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Zeng, Xinhong, and Yongxiang Wang. "Analysis and Simulation of Polishing Robot Operation Trajectory Planning." Algorithms 18, no. 1 (2025): 53. https://doi.org/10.3390/a18010053.

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Trajectory planning is essential for robotic polishing tasks, as the effectiveness of this planning directly influences the quality of the work and the energy efficiency of the operation. This study introduces an innovative trajectory planning method for robotic polishing tasks, focusing on the development and application of quintic B-spline interpolation. Recognizing the critical impact of trajectory planning on the quality and energy efficiency of robotic operations, we analyze the structure and parameters of the ABB-IRB120 robot within a laboratory setting. Using the Denavit–Hartenberg parameter method, a kinematic model is established, and the robot’s motion equations are derived through matrix transformation. We then propose a novel approach by implementing both fifth-degree polynomial and quintic B-spline interpolation algorithms for planning the robot’s spatial spiral arc trajectory, which is a key contribution of this work. The effectiveness of these methodologies is validated through simulation in MATLAB’s robotics toolbox. Our findings demonstrate that the quintic B-spline interpolation not only significantly improves task precision but also optimizes energy consumption, making it a superior method for trajectory planning in robotic grinding applications. By integrating advanced interpolation techniques, this study provides substantial technological and environmental benefits, offering a groundbreaking reference for enhancing the precision and efficiency of robotic control systems.

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Ma, Jun, Jian Ping Hu, Xiao Yue Yan, Chun Hui Qi, and Jing Guan. "Transplanting Path Planning and Motion Functions Research of the High-Speed Tray Seedling Transplanting Robot." Advanced Materials Research 694-697 (May 2013): 1747–52. http://dx.doi.org/10.4028/www.scientific.net/amr.694-697.1747.

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High-speed tray seedling transplanting robot was developed which used two-DOF parallel mechanism as transplanting mechanism, and pneumatic manipulator as the end-effector, so it can achieve high speed of transplanting. According to transplanting seedlings from high-density plug to the low-density plug, a type of transplanting path was put forward which consists of rise, translation and decline, in this paper, it was called three-stage trajectory. Analysis the movement characteristic of each stage, make sure the stability of transplanting, then the sine motion law, quintic polynomial motion law and septic polynomial motion law were put forward as the Transplanting movement function according the analysis of movement characteristic. Compared the transplanting efficiency and stability of the three motion law through their velocity, acceleration and saltus, finally, quintic polynomial motion law was preferred as transplanting robot motion law. Transplanting experiment was taken on the developed prototype, the transplanting frequency was more than 60 per minute and the qualified rate can reach 92.71%.

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Conference papers on the topic "Quintic polynomial trajectory"

1

Li, Yanghua, and Bo Mo. "The trajectory planning of spacecraft based on optimal quintic polynomial." In 2013 2nd International Conference on Measurement, Information and Control (ICMIC). IEEE, 2013. http://dx.doi.org/10.1109/mic.2013.6758098.

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Rai, Jaynendra Kumar, and Ravi Tewari. "Quintic polynomial trajectory of biped robot for human-like walking." In 2014 6th International Symposium on Communications, Control and Signal Processing (ISCCSP). IEEE, 2014. http://dx.doi.org/10.1109/isccsp.2014.6877888.

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Xin, Shi, Liao Liang, Song Wei, and Xu Shuyuan. "A trajectory planning method based on feedforward compensation and quintic polynomial interpolation." In 2019 14th IEEE International Conference on Electronic Measurement & Instruments (ICEMI). IEEE, 2019. http://dx.doi.org/10.1109/icemi46757.2019.9101620.

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Tan, Zefu, Jian Wei, and Nina Dai. "Real-time Dynamic Trajectory Planning for Intelligent Vehicles Based on Quintic Polynomial." In 2022 IEEE 21st International Conference on Ubiquitous Computing and Communications (IUCC/CIT/DSCI/SmartCNS). IEEE, 2022. http://dx.doi.org/10.1109/iucc-cit-dsci-smartcns57392.2022.00022.

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Liu, Yunxiang, Yao Wang, Xige Wang, and Chenghao Tao. "A model for safe lane changing of connected vehicles based on quintic polynomial Trajectory planning." In 2022 7th International Conference on Intelligent Informatics and Biomedical Sciences (ICIIBMS). IEEE, 2022. http://dx.doi.org/10.1109/iciibms55689.2022.9971621.

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Tan, Ao, Xiwen Guo, Qunjing Wang, Yuming Sun, Qiyong Yang, and Ronglin Zhang. "Point to Point Trajectory Planning of Permanent Magnet Spherical Motor Based on Quintic Polynomial Interpolation." In 2023 26th International Conference on Electrical Machines and Systems (ICEMS). IEEE, 2023. http://dx.doi.org/10.1109/icems59686.2023.10344867.

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Li, Yunfu, and Yifeng Qi. "Double quintic polynomial ecological lane change trajectory optimization for intelligent vehicles based on multi-objective genetic algorithm." In 2022 IEEE 2nd International Conference on Data Science and Computer Application (ICDSCA). IEEE, 2022. http://dx.doi.org/10.1109/icdsca56264.2022.9988522.

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Huang, Yi, Mi Zhao, and Jian Zhang. "The Position Control Method of two Joint Manipulator Based on Sliding Mode and Trajectory Setting Algorithm of Quintic Polynomial Interpolation." In 2021 IEEE International Conference on Networking, Sensing and Control (ICNSC). IEEE, 2021. http://dx.doi.org/10.1109/icnsc52481.2021.9702202.

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Liu, Longxi, Zihao Wang, Yunqing Zhang, and Jinglai Wu. "Trajectory Planning of Autonomous Vehicles Based on Parameterized Control Optimization for Three-Degree-of-Freedom Vehicle Dynamics Model." In WCX SAE World Congress Experience. SAE International, 2024. http://dx.doi.org/10.4271/2024-01-2332.

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<div class="section abstract"><div class="htmlview paragraph">In contemporary trajectory planning research, it is common to rely on point-mass model for trajectory planning. However, this often leads to the generation of trajectories that do not adhere to the vehicle dynamics, thereby increasing the complexity of trajectory tracking control. This paper proposes a local trajectory planning algorithm that combines sampling and sequential quadratic optimization, considering the vehicle dynamics model. Initially, the vehicle trajectory is characterized by utilizing vehicle dynamic control variables, including the front wheel angle and the longitudinal speed. Next, a cluster of sampling points for the anticipated point corresponding to the current vehicle position is obtained through a sampling algorithm based on the vehicle's current state. Then, the trajectory planning problem between these two points is modeled as a sequential quadratic optimization problem. By employing an offline method, the optimal trajectory set between the present position and the anticipated point cluster is computed. After acquiring clusters of candidate trajectories, each candidate trajectory is evaluated to determine its feasibility and cost, considering factors such as efficiency and comfort. The best trajectory is then chosen as the local trajectory of vehicle. The trajectories generated using the proposed method and the quintic polynomial method are both tracked and controlled using a 3-DOF vehicle dynamic model. The results clearly demonstrate that the trajectories generated by the proposed method exhibit superior tracking performance.</div></div>

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Gabriel, David, Daniel Görges, and Daniel Baumgärtner. "On the Development of a Path Tracking Controller by combining Optimal Preview Control and Pursuit Control Methods." In The Evolving Scholar - BMD 2023, 5th Edition. The Evolving Scholar - BMD 2023, 5th Edition, 2023. http://dx.doi.org/10.59490/65bbc2e6315708a53e169769.

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Path tracking controllers are an important part when developing self-driving vehicles. When designing such a controller for a single-track vehicle, a major challenge is that the vehicle not only has to follow a predefined path but has to be stabilized at the same time. Especially if the vehicle has slow steering dynamics (e.g. τ > 1.5s) and the path contains tight corners which should not be cut (e.g. directional change of more than 90° in less than 2s), the design of a suitable path tracking controller can be difficult. In this work an optimal preview controller that stabilizes a bicycle and that can track a given yaw rate trajectory is combined with a quintic polynomial pursuit controller. With this approach, we can achieve good tracking performance for the predefined paths, which can be seen in the simulation and experimental results.

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