Fuzzy-EKF Controller for Intelligent Wheelchair Navigation

Abstract The electric wheelchair gives more autonomy and facilitates movement for handicapped persons in the home or in a hospital. Among the problems faced by these persons are collision with obstacles, the doorway, the navigation in a hallway, and reaching the desired place. These problems are due to the difficult manipulation of an electric wheelchair, especially for persons with severe disabilities. Hence, we tried to add more functionality to the standard wheelchair in order to increase movement range, security, environment access, and comfort. In this context, we have developed an automatic control method for indoor navigation. The proposed control system is mounted on the electric wheelchair for the handicapped, developed in the research laboratory CEMLab (Control and Energy Management Laboratory-Tunisia). The proposed method is based on two fuzzy controllers that ensure target achievement and obstacle avoidance. Furthermore, an extended Kalman filter was used to provide precise measurements and more effective data fusion localization. In this paper, we present the simulation and experimental results of the wheelchair navigation system.

[1]  Mohamed Jallouli,et al.  Synthesis of a fuzzy controller for the navigation of an electricwheelchair for handicapped , 2009, 2009 6th International Multi-Conference on Systems, Signals and Devices.

[2]  Ahmad Nor Kasruddin Nasir,et al.  PD-fuzzy Control of a Stair Climbing Wheelchair , 2013 .

[3]  Kevin M. Passino,et al.  Stable adaptive control using fuzzy systems and neural networks , 1996, IEEE Trans. Fuzzy Syst..

[4]  Kiyoshi Irie,et al.  Outdoor Localization Using Stereo Vision Under Various Illumination Conditions , 2012, Adv. Robotics.

[5]  M. Jallouli,et al.  Wheelchair obstacle avoidance based on fuzzy controller and ultrasonic sensors , 2013, 2013 International Conference on Computer Applications Technology (ICCAT).

[6]  John R. Spletzer,et al.  ATRS - A Technology-Based Solution to Automobility for Wheelchair Users , 2007, FSR.

[7]  Yoshinori Kuno,et al.  SOCIALLY ACCEPTABLE SMART WHEELCHAIR NAVIGATION FROM HEAD ORIENTATION OBSERVATION , 2014 .

[8]  Rachid Belaroussi,et al.  How to Manage Conflict and Ambiguities in Localization and Map Matching , 2014, J. Intell. Syst..

[9]  Urbano Nunes,et al.  An outdoor guidepath navigation system for AMRs based on robust detection of magnetic markers , 2007, 2007 IEEE Conference on Emerging Technologies and Factory Automation (EFTA 2007).

[10]  Hugh F. Durrant-Whyte,et al.  Multisensor Data Fusion , 2016, Springer Handbook of Robotics, 2nd Ed..

[11]  Francesco Mondada,et al.  Fuzzy Control System for Autonomous Navigation of Thymio II Mobile Robots , 2014 .

[12]  Manuel Mazo,et al.  Fusing odometric and vision data with an EKF to estimate the absolute position of an autonomous mobile robot , 2003, EFTA 2003. 2003 IEEE Conference on Emerging Technologies and Factory Automation. Proceedings (Cat. No.03TH8696).

[13]  Kalevi Hyyppä,et al.  GIMnet on the MICA wheelchair , 2010 .

[14]  H Maaref,et al.  Sensor-based fuzzy navigation of an autonomous mobile robot in an indoor environment , 2000 .

[15]  Said Mammar,et al.  Numerical Intelligence for Mobility and Communication: Tendencies in Automatics and Control , 2014, J. Intell. Syst..

[16]  Urbano Nunes,et al.  Assisted navigation for a brain-actuated intelligent wheelchair , 2013, Robotics Auton. Syst..

[17]  N. G. Jabson,et al.  THE AUTONOMOUS GOLF PLAYING MICRO ROBOT: WITH GLOBAL VISION AND FUZZY LOGIC CONTROLLER , 2008 .

[18]  Mohamed Jallouli,et al.  EKF for electric wheelchair localization , 2014, 2014 World Symposium on Computer Applications & Research (WSCAR).

[19]  BingFei Wu,et al.  Simultaneous Localization and Human Following for a Wheelchair Robot using a Camera with Depth Information , 2013 .

[20]  Guy Bourhis,et al.  Smart wheelchair control through a deictic approach , 2010, Robotics Auton. Syst..

[21]  R. Simpson Smart wheelchairs: A literature review. , 2005, Journal of rehabilitation research and development.

[22]  Kosei Demura,et al.  A Navigation Method Using the Mutual Feedback of Waypoints and Self-Positions , 2012, Adv. Robotics.