Velocity planning method for position–velocity–time control based on a modified S-shaped acceleration/deceleration algorithm

Ni, Hepeng; Ji, Shuai; Liu, Yanan; Ye, Yingxin; Zhang, Chengrui; Chen, Jiwen

doi:10.1177/17298814211072418

Cited by 3 publications

(2 citation statements)

References 22 publications

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“…The S-shaped acceleration/deceleration algorithm is optimized on the basis of T-shaped velocity programming. The planned trajectory, velocity, and acceleration are continuous, which can ensure smooth acceleration and deceleration of the end-effector without impact [55,56]. There are four types of S-shaped velocity curve planning: seven-stage, six-stage, five−stage, and four-stage, respectively.…”

Section: Implementation Methods Of Each Trajectory For the Four Perio...mentioning

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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Section: Implementation Methods Of Each Trajectory For the Four Perio...mentioning

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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“…Optimization algorithms have been widely used in velocity planning due to their high realtime performance. Most papers that employed optimization algorithms set hard constraints, such as acceleration and Jerk, which often caused planner solution failures in unknown and complex scenarios (Guarino Lo Bianco, 2013;Ni et al, 2022). Setting the constraint value too low reduced the algorithm solution space and limited the exploitation of vehicle dynamic performance.…”

Section: Introductionmentioning

confidence: 99%

An Optimization-based Time-optimal Velocity Planning for Autonomous Driving

HU,

PAN,

GAO

et al. 2023

SIC

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Velocity planning plays an important role in motion planning of automated driving as it must meet safety, comfort, and traffic regulation requirements. Therefore, it is necessary to consider Jerk constraint and dynamic obstacle constraint. However, the introduction of these constraints makes velocity planning a non-convex optimization problem, significantly increasing computational complexity. To address these challenges, this paper investigates an optimization-based timeoptimal velocity planning method. The non-convex and non-linear problems caused by Jerk constraint and dynamic obstacle constraint are addressed by realizing constraint linearization through velocity filtering with acceleration as the threshold. The linear programming (LP) method is then used twice to calculate a time-optimal velocity profile that satisfies the given constraints. Furthermore, when hard constraints are unable to satisfy obstacle avoidance planning, a dynamic constraint frame strategy is proposed to relax the hard constraints and fully utilize the dynamic performance of the ego-vehicle to avoid obstacles. Finally, simulations are conducted in various driving scenarios to validate the effectiveness of the proposed approach. The simulation results demonstrate that the approach proposed in this paper can quickly generate velocity profiles that meet safety and comfort constraints, within a short planning period. Additionally, the dynamic constraint frame strategy can improve the dynamic adaptability of the algorithm.

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Through hole-cutting conic posture optimization for a redundant 3D laser cutting machine

Ding,

Soccio,

Indri

et al. 2024

Int J Adv Manuf Technol

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Productively reducing the time required to cut numerous through holes in automotive workpieces is crucial for enhancing parts manufacturing in the 3D laser cutting process. However, the conventional cutting strategy, in which the laser beam maintains a stationary posture along the hole path, lacks flexibility and fails to effectively leverage processing tolerances. In this study, we conduct a thorough analysis of the kinematics of a six-axis redundant laser cutting machine and resolve through a decoupling method with singularity management. We propose an innovative conic posture cutting strategy for 3D laser hole-cutting with thin materials. This approach adopts the geometry of a cone as the posture while cutting the hole path. In order to obtain the optimal vertex of the cone while minimizing the taper error generated by the conic posture and kinetic energy consumption of the actuators during motion, we formulate a multi-objective optimization problem and solve it using a genetic algorithm. Furthermore, we enhance the optimization by adopting a time minimization approach. Through the implementation of a B-pillar workpiece cutting experiment, we have successfully validated the credibility of our proposed cutting strategy, thereby demonstrating an enhancement of time on 26 hole-cutting paths.

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Velocity planning method for position–velocity–time control based on a modified S-shaped acceleration/deceleration algorithm

Cited by 3 publications

References 22 publications

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

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

An Optimization-based Time-optimal Velocity Planning for Autonomous Driving

Through hole-cutting conic posture optimization for a redundant 3D laser cutting machine

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