Path Planning Algorithm for Smart Wheelchair Indoor Navigation
CSTR:
Author:
  • Article
  • | |
  • Metrics
  • |
  • Reference [11]
  • |
  • Related [20]
  • | | |
  • Comments
    Abstract:

    The smart wheelchair improve the quality of life and give more freedom for people who lose the ability to walk. Path planning for smart wheelchair technology is one of an important Technology. Research method The degree of difficulty walking in the actual environment is difference. A new path planning algorithm for a kind of navigation methods to find the optimal path has been proved. Firstly the grid modeling has been established for indoor environment, and the adjacent relation with the improved A* algorithm has been used to optimal planning of global path between the two positions, then the virtual force field algorithm can be implemented for the local path planning on the way. Results and Conclusions This algorithm just needs to gather the information where you want to reach, then the smart wheelchair can automatically navigate to the destination. The experiments show that the algorithm is applied to the smart wheelchair indoor navigation system to reach the expectations and has the advantages of quick response, stable performance, easy to use and strong extensibility.

    Reference
    1 贾文川.四足机器人脑机协作导航与规划[博士学位论文]. 武汉:华中科技大学,2011.
    2 Sina D, Syn S, Julianne U, Andreas H, Wolfgang S, et al. Navigation within buildings: Novel movement detection algorithms supporting people with visual impairments. Research in Developmental Disabilities, 2014, 9(35): 26-34.
    3 董晓倩.一种智能轮椅的静态路径规划方法.教育部中南地区高等学校电子电气基础课教学研究会第二十届学术年会会议论文集(下册),郑州: 2010: 642-645.
    4 Hector BM, Carlos S, Youcef M, Jean-Bernard H, et al. Visual navigation of wheeled mobile robots using direct feedback of a geometric constraint. Autonomous Robot, 2014, 2(37): 137-156.
    5 徐彪,朱健铭,蒋朝阳,等.通用型工业级数据采集和监控系统设计.计算机测量与控制,2014,22(10):3192-3195.
    6 Zou JM, Kusyk J, Uyar MU, Gundry S, Sahin CS. Bio-inspired and voronoi-based algorithms for self-positioning autonomous mobile nodes. IEEE Military Communications Conference. 2014. 6-12.
    7 杨剑峰.蚁群算法及其应用研究[博士学位论文].杭州:浙江大学,2007.
    8 鲁涛,原魁,朱海兵.智能轮椅研究现状及发展趋势.机器人技术与应用,2008,2:1523-1535.
    9 Ghazaleh P, Magnus J. Vision-aidedinertial navigation based on ground plane feature detection. IEEE-ASME Transactions Mechatronics, 2014, 4(19): 1206-1215.
    10 张鑫.基于嵌入式定位系统的研究[硕士学位论文].西安: 西安科技大学,2011.
    11 Kosei D, Yuichi K. A navigation method using the mutual feedback of waypoints and self-positions. Advanced Robotic, 2012, 14(26): 1677-1691.
    Cited by
    Comments
    Comments
    分享到微博
    Submit
Get Citation

徐彪,蒋朝阳,朱健铭,陈真诚.智能轮椅室内导航路径规划算法.计算机系统应用,2015,24(8):171-175

Copy
Share
Article Metrics
  • Abstract:1362
  • PDF: 3137
  • HTML: 0
  • Cited by: 0
History
  • Received:December 10,2014
  • Revised:January 29,2015
  • Online: September 03,2015
Article QR Code
You are the first990605Visitors
Copyright: Institute of Software, Chinese Academy of Sciences Beijing ICP No. 05046678-3
Address:4# South Fourth Street, Zhongguancun,Haidian, Beijing,Postal Code:100190
Phone:010-62661041 Fax: Email:csa (a) iscas.ac.cn
Technical Support:Beijing Qinyun Technology Development Co., Ltd.

Beijing Public Network Security No. 11040202500063