Design and Implementation of Bézier Curve Trajectory Planning in DELTA Parallel Robots

2015 ◽  
pp. 420-430 ◽  
Author(s):  
Zhiwu Dai ◽  
Xingjun Sheng ◽  
Jian Hu ◽  
Hui Wang ◽  
Dingguo Zhang
Keyword(s):  
Trajectory Planning ◽  
Parallel Robots ◽  
Bézier Curve ◽  
Bezier Curve ◽  
Design And Implementation

Trajectory Planning for a Welding Robot Based on the Bezier Curve

2015 ◽  
Vol 8 (2) ◽  
pp. 351-362 ◽  
Author(s):  
Caidong Wang ◽  
Xinjie Wang ◽  
Hui Zheng
Keyword(s):  
Trajectory Planning ◽  
Bézier Curve ◽  
Bezier Curve ◽  
Welding Robot

Trajectory planning in 3D dynamic environment with non-cooperative agents via fast marching and Bézier curve

2019 ◽  
Vol 5 (2) ◽  
pp. 119-143 ◽  
Author(s):  
Xuepeng Zong ◽  
Qiyu Sun ◽  
Dachen Yao ◽  
Wei Du ◽  
Yang Tang
Keyword(s):  
Trajectory Planning ◽  
Dynamic Environment ◽  
Bézier Curve ◽  
Bezier Curve ◽  
Fast Marching ◽  
Cooperative Agents

Bézier curve‐based trajectory planning for autonomous vehicles with collision avoidance

2020 ◽  
Vol 14 (13) ◽  
pp. 1882-1891
Author(s):  
Ling Zheng ◽  
Pengyun Zeng ◽  
Wei Yang ◽  
Yinong Li ◽  
Zhenfei Zhan
Keyword(s):  
Collision Avoidance ◽  
Trajectory Planning ◽  
Autonomous Vehicles ◽  
Bézier Curve ◽  
Bezier Curve

scholarly journals CONTINUOUS TRAJECTORY PLANNING FOR WELDING OF COMPLEX JOINTS USING BEZIER CURVE

2019 ◽  
Vol 33 ◽  
pp. 685-692
Author(s):  
J. Ogbemhe ◽  
K. Mpofu ◽  
N.S Tlale
Keyword(s):  
Trajectory Planning ◽  
Bézier Curve ◽  
Bezier Curve

scholarly journals Using the Bezier Curve and Particle Swarm Optimization in Trajectory Planning for Overhead Cranes to Suppress the Payloads’ Residual Swing

2018 ◽  
Vol 2018 ◽  
pp. 1-13
Author(s):  
Huasen Liu ◽  
Wenming Cheng
Keyword(s):  
Trajectory Planning ◽  
Control Point ◽  
Particle Swarm ◽  
Bézier Curve ◽  
Bezier Curve ◽  
Underactuated System ◽  
Overhead Crane ◽  
Particle Swarm Optimizer ◽  
Swing Angle ◽  
Simulation Results

An overhead crane is an underactuated system, which leads to residual swing of the crane’s payload when the crane accelerates or decelerates. This paper proposes a trajectory planning approach which uses the Bezier curve and particle swarm optimizer (PSO-BC) to limit the residual swing of a payload. The dynamic equation for an overhead crane is discredited, and a five-order Bezier curve is generated as the trolley’s displacement. The trolley’s desired position is set as the last control point of the Bezier curve, which guarantees that the trolley reaches the desired position accurately. Various constraints, including restricting the swing angle, the allowable trolley velocity, and the allowable trolley acceleration, are then taken into consideration as the constraints. In order to make the trolley reach its desired position whilst suppressing the payload’s swing under the constraints, a particle swarm optimizer is used to determine the optimal control point positions of the Bezier curve. Finally, the PSO-BC simulation results are compared to some existing approaches and are presented to show the feasibility and robustness of the proposed PSO-BC method. The simulation results indicate that the trolley moved to the desired position accurately whilst the payload’s swing angle is kept to an allowable level.

scholarly journals An optimal trajectory planning algorithm for autonomous trucks: Architecture, algorithm, and experiment

2020 ◽  
Vol 17 (2) ◽  
pp. 172988142090960 ◽  
Author(s):  
Feng Zhang ◽  
Ranfei Xia ◽  
Xinxing Chen
Keyword(s):  
Cost Function ◽  
Trajectory Planning ◽  
Bézier Curve ◽  
Bezier Curve ◽  
Dijkstra Algorithm ◽  
Function Model ◽  
Lane Changing ◽  
Target Trajectory ◽  
Planning Algorithm ◽  
Optimal Target

Safe lane changing of the dynamic industrial park and port scenarios with autonomous trucks involves the problem of planning an effective and smooth trajectory. To solve this problem, we propose a new trajectory planning method based on the Dijkstra algorithm, which combines the Dijkstra algorithm with a cost function model and the Bezier curve. The cost function model is established to filter target trajectories to obtain the optimal target trajectory. The third-order Bezier curve is employed to smooth the optimal target trajectory. Road experiments are carried out with an autonomous truck to illustrate the effectiveness and smoothness of the proposed method. Compared with other conventional methods, the improved method can generate a more effective and smoother trajectory in the truck lane change.

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