Controlling the Motion of an Autonomous Mobile Robot Using Various Techniques: a Review

Autonomous navigation of mobile robots in an uncertain and complex environment is a broad and complicated issue due to a variety of obstacles that mobile robots have to detect and represent in their maps to navigate safely. The objective of the navigation-mobile robot is to obtain an optimum path, meaning that the robot should plan a reliable path between the source point and the target point without colliding with the static and dynamic obstacles found in an uncertain and complex environment. Several efficient techniques have been developed by researchers in the motion planning of mobile robots. This paper presents detailed analysis of various techniques used in the autonomous navigation of mobile robot.

[1]  R. Sreerama Kumar,et al.  Intelligent task planning and action selection of a mobile robot in a multi-agent system through a fuzzy neural network approach , 2007, Eng. Appl. Artif. Intell..

[2]  Ujjwal Maulik,et al.  A framework for an artificial immunity and speech based navigation for mobile robots , 2008, 2008 IEEE Congress on Evolutionary Computation (IEEE World Congress on Computational Intelligence).

[3]  Dayal R. Parhi,et al.  ANFIS Approach for Navigation of Mobile Robots , 2009, 2009 International Conference on Advances in Recent Technologies in Communication and Computing.

[4]  Sunan Wang,et al.  A Novel Immune Network Strategy for Robot Path Planning in Complicated Environments , 2010, J. Intell. Robotic Syst..

[5]  Soh Chin Yun,et al.  Improved genetic algorithms based optimum path planning for mobile robot , 2010, 2010 11th International Conference on Control Automation Robotics & Vision.

[6]  Xuanzi Hu,et al.  Robot path planning based on artificial immune network , 2007, 2007 IEEE International Conference on Robotics and Biomimetics (ROBIO).

[7]  Howie Choset,et al.  Limited communication, multi-robot team based coverage , 2004, IEEE International Conference on Robotics and Automation, 2004. Proceedings. ICRA '04. 2004.

[8]  Chi Yen Kim,et al.  A study of cluster robots line formatted navigation using potential field method , 2011, 2011 IEEE International Conference on Mechatronics and Automation.

[9]  Fengyu Zhou,et al.  Mobile Robot Path Planning Based on Q-ANN , 2007, 2007 IEEE International Conference on Automation and Logistics.

[10]  Dayal R. Parhi,et al.  Intelligent neuro-controller for navigation of mobile robot , 2009, ICAC3 '09.

[11]  De-Bao Sun,et al.  Path planning for mobile robot using the particle swarm optimization with mutation operator , 2004, Proceedings of 2004 International Conference on Machine Learning and Cybernetics (IEEE Cat. No.04EX826).

[12]  François Chaumette,et al.  Image-based robot navigation from an image memory , 2007, Robotics Auton. Syst..

[13]  Guan-Chun Luh,et al.  Behavior-based intelligent mobile robot using an immunized reinforcement adaptive learning mechanism , 2002, Adv. Eng. Informatics.

[14]  Dayal R. Parhi Navigation of Mobile Robots Using a Fuzzy Logic Controller , 2005, J. Intell. Robotic Syst..

[15]  Anup Kumar Panda,et al.  Fuzzy logic techniques for navigation of several mobile robots , 2009, Appl. Soft Comput..

[16]  Sallehuddin Mohamed Haris,et al.  Motion planning for mobile robot navigation using combine Quad-Tree Decomposition and Voronoi Diagrams , 2010, 2010 The 2nd International Conference on Computer and Automation Engineering (ICCAE).

[17]  Meng Wang,et al.  Fuzzy logic-based real-time robot navigation in unknown environment with dead ends , 2008, Robotics Auton. Syst..

[18]  Xiaochuan Wang,et al.  Intelligent obstacle avoidance for an autonomous mobile robot , 2004, Fifth World Congress on Intelligent Control and Automation (IEEE Cat. No.04EX788).

[19]  W. Gharieb,et al.  Path planning for a mobile robot using genetic algorithms , 2004, International Conference on Electrical, Electronic and Computer Engineering, 2004. ICEEC '04..

[20]  Xin Chen,et al.  Mobile Robot Navigation Using Particle Swarm Optimization and Adaptive NN , 2005, ICNC.

[21]  Qidi Wu,et al.  A fast two-stage ACO algorithm for robotic path planning , 2011, Neural Computing and Applications.

[22]  Hideki Hashimoto,et al.  Path generation for mobile robot navigation using genetic algorithm , 1995, Proceedings of IECON '95 - 21st Annual Conference on IEEE Industrial Electronics.

[23]  Alan S. Perelson,et al.  The immune system, adaptation, and machine learning , 1986 .

[24]  Anup Kumar Panda,et al.  Potential field method to navigate several mobile robots , 2006, Applied Intelligence.

[25]  Anup Kumar Panda,et al.  Neuro-fuzzy technique for navigation of multiple mobile robots , 2006, Fuzzy Optim. Decis. Mak..

[26]  Hyungsuck Cho,et al.  An active trinocular vision system of sensing indoor navigation environment for mobile robots , 2006 .

[27]  Lixin Gao,et al.  An Improved Ant Colony System Algorithm for Optimal Path Planning Problem of Mobile Robots , 2010, 2010 Second International Conference on Computer Modeling and Simulation.

[28]  Jin Xu,et al.  Path Planning for Mobile Robot Based on Chaos Genetic Algorithm , 2008, 2008 Fourth International Conference on Natural Computation.

[29]  Kuo-Lan Su,et al.  Ant Colony System Based Mobile Robot Path Planning , 2010, 2010 Fourth International Conference on Genetic and Evolutionary Computing.

[30]  R. Carelli,et al.  Neural network-based optimal control for autonomous mobile vehicle navigation , 2004, Proceedings of the 2004 IEEE International Symposium on Intelligent Control, 2004..

[31]  Lu Wang,et al.  Path planning method for mobile robot based on ant colony optimization algorithm , 2008, 2008 3rd IEEE Conference on Industrial Electronics and Applications.

[32]  Maarouf Saad,et al.  An improved Artificial Potential Field approach to real-time mobile robot path planning in an unknown environment , 2011, 2011 IEEE International Symposium on Robotic and Sensors Environments (ROSE).

[33]  Hongpeng Liu,et al.  Optimal Path Planning in Complex Indoor Environment Based on Improved PSO , 2011 .

[34]  Yangmin Li,et al.  Smooth Path Planning of a Mobile Robot Using Stochastic Particle Swarm Optimization , 2006, 2006 International Conference on Mechatronics and Automation.

[35]  Gabor Horvath,et al.  Artificial neural network based mobile robot navigation , 2009, 2009 IEEE International Symposium on Intelligent Signal Processing.

[36]  Vincenzo Caglioti,et al.  An information-based exploration strategy for environment mapping with mobile robots , 2010, Robotics Auton. Syst..

[37]  O. Khatib,et al.  Real-Time Obstacle Avoidance for Manipulators and Mobile Robots , 1985, Proceedings. 1985 IEEE International Conference on Robotics and Automation.

[38]  Nouri Masmoudi,et al.  A Fuzzy Logic Based Navigation of a Mobile Robot , 2008 .

[39]  Yang Yimin,et al.  Mobile Robot Navigation in Unknown Dynamic Environment Based on Ant Colony Algorithm , 2009, 2009 WRI Global Congress on Intelligent Systems.

[40]  Dogan Ibrahim,et al.  Navigation of mobile robots in the presence of obstacles , 2010, Adv. Eng. Softw..

[41]  Joaquim Salvi,et al.  Appearance-based mapping and localization for mobile robots using a feature stability histogram , 2011, Robotics Auton. Syst..

[42]  Oscar Castillo,et al.  Multiple Objective Genetic Algorithms for Path-planning Optimization in Autonomous Mobile Robots , 2006, Soft Comput..

[43]  Peter Eberhard,et al.  Cooperative Motion of Swarm Mobile Robots Based on Particle Swarm Optimization and Multibody System Dynamics , 2011 .