A Motion Planning Algorithm Based on Trajectory Optimization with Workspace Goal Region

被引:0
|
作者
Mi, Kai [1 ,2 ]
Hao, Peng [1 ,2 ]
Zheng, Jun [2 ]
Wang, Yunkuan [2 ]
Hu, Jianhua [2 ]
机构
[1] Univ Chinese Acad Sci, Yuquan Rd 19, Beijing, Peoples R China
[2] Chinese Acad Sci, Inst Automat, Intelligent Mfg Technol & Syst Res Ctr, Zhongguancun East Rd 95, Beijing, Peoples R China
来源
2019 IEEE INTERNATIONAL CONFERENCE ON MECHATRONICS AND AUTOMATION (ICMA) | 2019年
关键词
Workspace goal region; Distance field; Goal-region-constrained likelihood; Trajectory optimization; Obstacle avoidance;
D O I
10.1109/icma.2019.8816541
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
We consider a motion planning problem with workspace goal region in obstacle environments and the task is to move the end-effector into a specific goal region without posture constraints. In order to improve the quality of the planning trajectory, we present a goal region constraint algorithm based on Gaussian process motion planning. We construct a distance field for the irregular goal region in advance. The closest distance and direction from any location of the workspace to the specific goal region can be easily computed. Combined with the original method, we define a goal-region-constrained likelihood which specifies the probability that the position of end-effector is within the specific goal region and move the end-effector to a better position by numerical optimization. Finally, multiple simulation experiments are carried out and the results show that the proposed algorithm can quickly plan an obstacle avoidance trajectory in joint space and the quality of the trajectory is improved effectively compared to randomly specifying a goal configuration.
引用
收藏
页码:763 / 768
页数:6
相关论文
共 50 条
  • [1] Autonomous Vehicle Motion Planning Based on Improved RRT* Algorithm and Trajectory Optimization
    Yuan J.-N.
    Yang L.
    Tang X.-F.
    Chen A.-W.
    Zidonghua Xuebao/Acta Automatica Sinica, 2022, 48 (12): : 2941 - 2950
  • [2] Trajectory Optimization With Particle Swarm Optimization for Manipulator Motion Planning
    Kim, Jeong-Jung
    Lee, Ju-Jang
    IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 2015, 11 (03) : 620 - 631
  • [3] Optimization of trajectory planning based on loading robot
    Zhu, Houyao
    Deng, Qingwen
    Wu, Wenqiang
    Lin, Hui
    Li, Shuai
    Zhang, Chunliang
    PROCEEDINGS OF 2021 7TH INTERNATIONAL CONFERENCE ON CONDITION MONITORING OF MACHINERY IN NON-STATIONARY OPERATIONS (CMMNO), 2021, : 52 - 57
  • [4] Goal state driven trajectory optimization
    Sintov, Avishai
    AUTONOMOUS ROBOTS, 2019, 43 (03) : 631 - 648
  • [5] Goal state driven trajectory optimization
    Avishai Sintov
    Autonomous Robots, 2019, 43 : 631 - 648
  • [6] Trajectory planning for penetration of multi-aircraft for mation based on improved convex optimization algorithm
    Liu Y.
    Li Y.
    Han W.
    Cui K.
    Xi Tong Gong Cheng Yu Dian Zi Ji Shu/Systems Engineering and Electronics, 2023, 45 (09): : 2819 - 2830
  • [7] An Improved Snake Optimization Algorithm and Its Application in Manipulator Trajectory Planning
    Li, Wei
    Zhao, Jiangbo
    Wang, JunZhen
    2023 35TH CHINESE CONTROL AND DECISION CONFERENCE, CCDC, 2023, : 4306 - 4313
  • [8] A TE-E Optimal Planning Technique Based on Screw Theory for Robot Trajectory in Workspace
    Zhifeng Liu
    Jingjing Xu
    Congbin Yang
    Yongsheng Zhao
    Tao Zhang
    Journal of Intelligent & Robotic Systems, 2018, 91 : 363 - 375
  • [9] A TE-E Optimal Planning Technique Based on Screw Theory for Robot Trajectory in Workspace
    Liu, Zhifeng
    Xu, Jingjing
    Yang, Congbin
    Zhao, Yongsheng
    Zhang, Tao
    JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS, 2018, 91 (3-4) : 363 - 375
  • [10] Mixtures of Gaussian Processes for Robot Motion Planning Using Stochastic Trajectory Optimization
    Petrovic, Luka
    Markovic, Ivan
    Petrovic, Ivan
    IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS, 2022, 52 (12): : 7378 - 7390