Visual servoing based path planning for wheeled mobile robot in obstacle environments

The presentation of the environment based on visual data is important for the mobile robot to do localization and orientation. Selection safe path for the path planning, it is necessary to locate the position of the mobile robot in surrounding environment. In this study, vision-based control system and fuzzy logic controller methods were used together to construct a collision free path environment. The experimental environment was monitored with an overhead camera and robot position information, obstacles and target positions were determined by visual processing techniques. A safe (non-collision) path plan between the robot and the target has been achieved using fuzzy decision sets. Six virtual sensor data were used to plan the robot orientation control. A graphical representation of the test results of applications made for different scenarios is demonstrated and commentated.

[1]  Muhammad Akmal Jeffril,et al.  Mobile robot obstacle avoidance by using Fuzzy Logic technique , 2013, 2013 IEEE 3rd International Conference on System Engineering and Technology.

[2]  Mohammad M. Ali,et al.  Path tracking control of a mobile robot using fuzzy logic , 2016, 2016 13th International Multi-Conference on Systems, Signals & Devices (SSD).

[3]  Ting Zhu,et al.  Background subtraction based on non-parametric model , 2015, 2015 4th International Conference on Computer Science and Network Technology (ICCSNT).

[4]  Hong Wang,et al.  Monocular Vision Navigation and Control of Mobile Robot , 2012 .

[5]  Yangmin Li,et al.  Mobile robot autonomous path planning based on fuzzy logic and filter smoothing in dynamic environment , 2016, 2016 12th World Congress on Intelligent Control and Automation (WCICA).

[6]  Y. Tipsuwan,et al.  Fuzzy logic microcontroller implementation for DC motor speed control , 1999, IECON'99. Conference Proceedings. 25th Annual Conference of the IEEE Industrial Electronics Society (Cat. No.99CH37029).

[7]  Anthony Stentz,et al.  Optimal and efficient path planning for partially-known environments , 1994, Proceedings of the 1994 IEEE International Conference on Robotics and Automation.

[8]  Kuo-Ho Su,et al.  Navigation design with SVM path planning and fuzzy-based path tracking for wheeled agent , 2012, 2012 International conference on Fuzzy Theory and Its Applications (iFUZZY2012).

[9]  Nils J. Nilsson,et al.  A Formal Basis for the Heuristic Determination of Minimum Cost Paths , 1968, IEEE Trans. Syst. Sci. Cybern..

[10]  Qing Liu,et al.  An Improvement of D* Algorithm for Mobile Robot Path Planning in Partial Unknown Environment , 2009, 2009 Second International Conference on Intelligent Computation Technology and Automation.

[11]  Kevin Warwick,et al.  Planning of multiple autonomous vehicles using RRT , 2011, 2011 IEEE 10th International Conference on Cybernetic Intelligent Systems (CIS).

[12]  Hiroshi Noborio,et al.  On the heuristics of A* or A algorithm in ITS and robot path-planning , 2003, Proceedings 2003 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2003) (Cat. No.03CH37453).

[13]  Kemao Peng,et al.  Robust Composite Nonlinear Feedback Control With Application to a Servo Positioning System , 2007, IEEE Transactions on Industrial Electronics.

[14]  Lotfi A. Zadeh,et al.  A fuzzy-algorithmic approach to the definition of complex or imprecise concepts , 1976 .

[15]  Sreekala P.,et al.  Speed control of brushless DC motor with PI and fuzzy logic controller using resonantpole inverter , 2011, ISGT2011-India.

[16]  K. H. Park,et al.  Collision-free path planning of stereo vision based mobile robots using power potential approach , 2002, 7th International Conference on Control, Automation, Robotics and Vision, 2002. ICARCV 2002..

[17]  P Sreekala,et al.  Speed control of brushless DC motor with PI and fuzzy logic controller using resonantpole inverter , 2011 .

[18]  Wei-Yen Wang,et al.  Image-based fuzzy control system , 2008 .

[19]  Xuebo Zhang,et al.  Visual Servoing of Nonholonomic Mobile Robots With Uncalibrated Camera-to-Robot Parameters , 2017, IEEE Transactions on Industrial Electronics.

[20]  M. A. Fkirin,et al.  Practical path planning and path following for a non-holonomic mobile robot based on visual servoing , 2016, 2016 IEEE Information Technology, Networking, Electronic and Automation Control Conference.

[21]  Lim Chot Hun,et al.  A star path following mobile robot , 2011, 2011 4th International Conference on Mechatronics (ICOM).

[22]  M. A. Fkirin,et al.  Dynamic path planning and decentralized FLC path following implementation for WMR based on visual servoing , 2016, 2016 3rd MEC International Conference on Big Data and Smart City (ICBDSC).

[23]  Yaonan Wang,et al.  Background subtraction based on adaptive non-parametric model , 2008, 2008 7th World Congress on Intelligent Control and Automation.

[24]  Wen Cao,et al.  Application of an Improved A* Algorithm in Route Planning , 2009, 2009 WRI Global Congress on Intelligent Systems.