A comprehensive study for robot navigation techniques

被引:116
作者
Gul, Faiza [1 ]
Rahiman, Wan [1 ]
Alhady, Syed Sahal Nazi [1 ]
机构
[1] Univ Sains Malaysia, Sch Elect & Elect Engn, Engn Campus, Nibong Tebal 14300, Penang, Malaysia
来源
COGENT ENGINEERING | 2019年 / 6卷 / 01期
关键词
Artificial intelligence; neural network; fuzzy logic; AGV; NEURAL-NETWORK APPROACH; MOBILE-ROBOT; FUZZY CONTROL; OBSTACLE AVOIDANCE; UNDERWATER VEHICLES; GENETIC ALGORITHM; A-ASTERISK; CONTROLLER; OPTIMIZATION; LOGIC;
D O I
10.1080/23311916.2019.1632046
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
An intelligent autonomous robot is required in various applications such as space, transportation, industry, and defense. Mobile robots can also perform several tasks like material handling, disaster relief, patrolling, and rescue operation. Therefore, an autonomous robot is required that can travel freely in a static or a dynamic environment. Smooth and safe navigation of mobile robot through cluttered environment from start position to goal position with following safe path and producing optimal path length is the main aim of mobile robot navigation. Regarding this matter, several techniques have been explored by researchers for robot navigation path planning. An effort has been made in this article to study several navigation techniques, which are well suited for the static and dynamic environment and can be implemented for real-time navigation of mobile robot.
引用
收藏
页数:25
相关论文
共 125 条
  • [1] A fuzzy-based reactive controller for a non-holonomic mobile robot
    Abdessemed, F
    Benmahammed, K
    Monacelli, E
    [J]. ROBOTICS AND AUTONOMOUS SYSTEMS, 2004, 47 (01) : 31 - 46
  • [2] Abu Bakar B. B., 2016, Journal of Applied Sciences, V16, P570, DOI 10.3923/jas.2016.570.579
  • [3] 3D path planning for underwater vehicles using five evolutionary optimization algorithms avoiding static and energetic obstacles
    Aghababa, Mohammad Pourmahmood
    [J]. APPLIED OCEAN RESEARCH, 2012, 38 : 48 - 62
  • [4] Ahmadzadeh S., 2012, Journal of Academic and Applied Studies (JAAS), V2, P32
  • [5] Al Mutib K., 2011, 2011 UkSim 13th International Conference on Computer Modelling and Simulation (UKSim 2011), P1, DOI 10.1109/UKSIM.2011.11
  • [6] Al-Jarrah Rami, 2015, IFAC - Papers Online, V48, P46, DOI 10.1016/j.ifacol.2015.08.106
  • [7] Adaptive Neuro-Fuzzy Technique for Autonomous Ground Vehicle Navigation
    Al-Mayyahi, Auday
    Wang, William
    Birch, Phil
    [J]. ROBOTICS, 2014, 3 (04): : 349 - 370
  • [8] Al-Mutib K, 2016, 2016 2ND IEEE INTERNATIONAL SYMPOSIUM ON ROBOTICS AND MANUFACTURING AUTOMATION (ROMA)
  • [9] Algabri M., 2014, INT J COMPUTER APPL, V91, P14, DOI [10.5120/15952-5400, DOI 10.5120/15952-5400]
  • [10] Comparative study of soft computing techniques for mobile robot navigation in an unknown environment
    Algabri, Mohammed
    Mathkour, Hassan
    Ramdane, Hedjar
    Alsulaiman, Mansour
    [J]. COMPUTERS IN HUMAN BEHAVIOR, 2015, 50 : 42 - 56