Research on motion trajectory planning of the robotic arm of a robot

被引:6
作者
Miao, Xinghua [1 ]
Fu, Huansen [1 ]
Song, Xiangqian [1 ]
机构
[1] Taizhou Univ, Sch Shipping & Mechatron Engn, 93 Jichuan East Rd, Taizhou 225300, Jiangsu, Peoples R China
关键词
Cross variation; Particle swarm optimization algorithm; Robotic arm; Trajectory planning; SPACE MANIPULATOR; OPTIMIZATION;
D O I
10.1007/s10015-022-00779-2
中图分类号
TP24 [机器人技术];
学科分类号
080202 ; 1405 ;
摘要
The emergence of robots has replaced repetitive manual labor, and good robotic arm route planning can effectively improve work efficiency. This paper briefly introduced the motion model and trajectory planning method of robotic arms. The motion trajectory of robot arms was optimized by the genetic algorithm-improved particle swarm optimization (PSO) algorithm, and simulation experiments were carried out. The results showed that the improved PSO algorithm converged faster and had the lowest fitness after stable convergence; the arm had continuous and smooth changes in angle, angular velocity and angular acceleration and consumed the shortest time while moving on the route planned by the improved particle swarm algorithm, and the improved PSO algorithm took the shortest time to compute the route.
引用
收藏
页码:561 / 567
页数:7
相关论文
共 14 条
[1]  
Ayten KK, 2017, INT J ADV APPL SCI, V4, P1, DOI 10.21833/ijaas.2017.012.001
[2]   Novel analytical and experimental trajectory optimization of a 7-DOF baxter robot: global design sensitivity and step size analyses [J].
Bagheri, Mostafa ;
Naseradinmousavi, Peiman .
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY, 2017, 93 (9-12) :4153-4167
[3]   Driver-behavior-based robust steering control of unmanned driving robotic vehicle with modeling uncertainties and external disturbance [J].
Chen, Gang ;
Su, ShuHua .
PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART D-JOURNAL OF AUTOMOBILE ENGINEERING, 2020, 234 (06) :1585-1596
[4]   Trajectory optimization for inhibiting the joint parameter jump of a space manipulator with a load-carrying task [J].
Chen, Gang ;
Yuan, Bonan ;
Jia, Qingxuan ;
Fu, Yingzhuo ;
Tan, Jiayi .
MECHANISM AND MACHINE THEORY, 2019, 140 :59-82
[5]   Extending the capabilities of robotic manipulators using trajectory optimization [J].
Gallant, Andre ;
Gosselin, Clement .
MECHANISM AND MACHINE THEORY, 2018, 121 :502-514
[6]  
Jia Qingxuan, 2016, Int J Aerosp Eng, V2016, P1
[7]   Trajectory Optimization With Particle Swarm Optimization for Manipulator Motion Planning [J].
Kim, Jeong-Jung ;
Lee, Ju-Jang .
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 2015, 11 (03) :620-631
[8]  
Marchese AD, 2015, IEEE INT CONF ROBOT, P2528, DOI 10.1109/ICRA.2015.7139538
[9]   Path Planning for Multi-Arm Manipulators Using Deep Reinforcement Learning: Soft Actor-Critic with Hindsight Experience Replay [J].
Prianto, Evan ;
Kim, MyeongSeop ;
Park, Jae-Han ;
Bae, Ji-Hun ;
Kim, Jung-Su .
SENSORS, 2020, 20 (20) :1-23
[10]   Minimum-acceleration Trajectory Optimization for Humanoid Manipulator Based on Differential Evolution [J].
Ren Ziwu ;
Li Chunguang ;
Sun Lining .
INTERNATIONAL JOURNAL OF ADVANCED ROBOTIC SYSTEMS, 2016, 13