计算机科学 ›› 2020, Vol. 47 ›› Issue (11A): 111-115.doi: 10.11896/jsjkx.200800068

• 人工智能 • 上一篇    下一篇

基于动态系统的多障碍实时规避算法

王伟光1, 尹健2, 钱祥利1, 周子航3   

  1. 1 山东管理学院智能工程学院 济南 250357
    2 河南理工大学土木工程学院 河南 焦作 454003
    3 湖北工业大学电气与电子工程学院 武汉 430068
  • 出版日期:2020-11-15 发布日期:2020-11-17
  • 通讯作者: 王伟光(wwgxl@163.com)
  • 基金资助:
    国家自然科学基金青年科学基金(11705103);山东省重点研发计划项目(2019GGX105013);山东管理学院科研启航计划(QH2020Z08)

Realtime Multi-obstacle Avoidance Algorithm Based on Dynamic System

WANG Wei-guang1, YIN Jian2, QIAN Xiang-li1, ZHOU Zi-hang3   

  1. 1 School of Intelligent Engineering,Shandong Management University,Jinan 250357,China
    2 School of Civil Engineering,Henan Polytechnic University,Jiaozuo,Henan 454003,China
    3 School of Electrical and Electronic Engineering,Hubei University of Technology,Wuhan 430068,China
  • Online:2020-11-15 Published:2020-11-17
  • About author:WANG Wei-guang,born in 1980,postgraduate,lecture,is a member of China Computer Federation.His main research interests include information secu-rity and intelligent algorithm.
  • Supported by:
    This work was supported by the Young Scientists Fund of the National Natural Science Foundation of China(11705103),Key R&D Project of Shandong Province(2019GGX105013) and “Sailing” Program of Shandong Management University Scientific Research (QH2020Z08).

摘要: 机器人自主操控的应用日益广泛,工作区域动态干扰的风险也随之增加。针对机器人在工作空间中存在的障碍实时规避问题,提出了一种基于动态系统的多目标实时规避算法。首先构造动力系统调制模型,其次设置调制矩阵,然后构建障碍规避路径,最后提出多障碍动态规避模型。该算法不再以障碍物的事前分析作为先决条件,而是根据当前场景中的障碍物直接计算出调制矩阵,采用动态系统调制方法实现了障碍物的不可穿透性表述,且不改变动力系统的平衡点。在仿真实验中,针对空间依附障碍规避问题,用连续调制算法(CM)与所提算法进行比对仿真,验证了所提算法的有效性。最后进行多类障碍环境仿真,结果表明该算法能够有效解决静态多障碍以及动态多障碍的实时规避路径规划问题。

关键词: 动力系统, 多障碍, 空间机器人, 路径规划, 实时规避

Abstract: With the increasing application of autonomous robot control,the risk of dynamic interference in the working area also increases.Aiming at the problem of real-time obstacle avoidance of robots in the workspace,this paper proposes a realtime multi-target avoidance algorithm based on dynamic system.Firstly,the modulation model of the dynamic system is constructed,then the modulation matrix is set up,then the obstacle avoidance path is constructed,and finally the multi-obstacle dynamic avoidance model is proposed.This algorithm no longer takes the prior analysis of obstacles as a prerequisite,but directly calculates the mo-dulation matrix according to the obstacles in the current scene,and uses the dynamic system modulation method to realize the impenetrability representation of obstacles without changing the equilibrium point of the dynamic system.In the simulation experiment,aiming at the problem of avoiding spatial attachment obstacles,the continuous modulation algorithm(CM) is used to compare and simulate with the proposed algorithm,and the effectiveness of the algorithm is verified.Finally,the simulation results show that the algorithm can effectively solve the problem of static multi-obstacle and dynamic multi-obstacle avoidance path planning.

Key words: Dynamical system, Multi-obstacles, Path planning, Realtime obstacle avoidance, Space robot

中图分类号: 

  • TP391
[1] CHEN J L,QIN X L,LI X L,et al.Multi-robot collaborative obstacle avoidance based on artificial potential field method [J/OL].Computer Science,1-10.[2020-08-09].http://kns.cnki.net/kcms/detail/50.1075.TP.20200721.1702.098.html.
[2] CHAI H M,FANG M,LV S N.Local path planning of mobile robot based on situation assessment technology [J].Computer Science,2019,46(4):210-215.
[3] XI F F,ZENG X,JI S M,et al.Path planning of mobile robot based on PG-RRT algorithm [J].Computer Science,2019,46(4):247-253.
[4] LIU J,ZHAO H F,ZHOU D L.Improved quantum behavedparticle swarm optimization algorithm for mobile robot path planning [J].Computer Science,2017,44(S2):123-128.
[5] ZADEH S M K,BILLARD A.Learning stable nonlinear dynamical systems with gaussian mixture models[J].IEEE Trans. on Robotics,2011,27(5):943-957.
[6] JSPEERT A J,NAKANISHI J,HOFFMANN H,et al.Dynamical Movement Primitives:learning attractor models for motor behaviors[J].Neural Computation,2013,25(2):328-373.
[7] VAZQUEZ-OTERO A,FAIGL J,MUNUZURI A P.Path planning based on reaction-diffusion process[C]//IEEE/RSJ International Conference on Intelligent Robots and Systems.2012:896-901.
[8] LUO Q,WANG H B,CUI X J,et al.Research on autonomous navigation system of warehousing mobile robot based on improved artificial potential field method in dynamic environment [J].Application Research of Computers,2020,37(3):745-749,762.
[9] PENG Y,GUO W Q,LIU M,et al.Obstacle Avoidance Planning Based on Artificial Potential Field Optimized by Point of Tangency in Three-dimensional Space[J].Journal of System Simulation,2014,26(8):1758-1762,1768.
[10] WANG W,WANG H.Real-time obstacle avoidance trajectory planning for missile borne air vehicle based on constrained artificial potential field method [J].Journal of Aerospace Power,2014,29(7):1738-1743.
[11] CHEN T D,HUANG Y Y,WANG Z H.Collision-free pathplanning based on collision prediction[J].Systems Engineering-Theory & Practice,2020,40(4):1057-1068.
[12] LI J,YANG F,HAN Y F,et al.Research on robotic path planning based on dynamic gravitational field[J].Modern Electronics Technique,2020,43(11):41-46.
[13] GUAN X M,LYU R L.Conflict Resolution Method for Multiple Aircraft Based on Hybrid Artificial Potential Field and Ant Colony Algorithm [J].Journal of Wuhan University of Technology (Transportation Science & Engineering,2020,44(1):28-33.
[14] SHI Y F,ZHANG L,LIU Z X,et al.Research of Dynamic Obstacle Avoidance of Manipulator based on Artificial Potential Field Method of Velocity Field[J].Journal of Mechanical Transmission,2020,44(4):38-44.
[15] BROCK O,KHATIB O.Elastic strips:A framework for motion generation in human environments[J].The International Journal of Robotics Research,2002,21(12):1031-1052.
[16] YOSHIDA E,KANEHIRO F.Reactive robot motion using path replanning and deformation [C]//IEEE International Conference on Robotics and Automation.2011:5456-5462.
[17] PARK D H,HOFFMANN H,PASTOR P,et al.Movement reproduction and obstacle avoidance with dynamic movement primitives and potential fields [C]//The 8th IEEE-RAS International Conference on Humanoid Robots.2008:91-98.
[18] HOFFMANN H,PASTOR P,PARK D H,et al.Biologically-inspired dynamical systems for movement generation:automatic realtime goal adaptation and obstacle avoidance [C]//IEEE International Conference on Robotics and Automation.2009:2587-2592.
[19] KHANSARI-ZADEH S M,BILLARD A.A dynamical system approach to realtime obstacle avoidance[J].Autonomous Robots,2012,32(4):433-454.
[20] BLOOMENTHAL J,WYVILL B.Introduction to Implicit Surfaces[M].San Francisco:Morgan Kaufmann,1997.
[21] CIMURS R,LEE J H,SUH I H.Goal-oriented obstacle avoidance with deep reinforcement learning in continuous action space[J].Electronics,2020,9(3):411-421.
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