On passing a doorway with an autonomous Internet connected wheelchair using MATLAB

If a wheelchair for disabled is used for semi-autonomous navigation indoors it must be able to navigate through doors. A door and doorway can be parameterized with five parameters. A divide and conquer implementation of the Hough transform is used to segment outlines from range scans. The client software remote controls the wheelchair from the MATLAB environment. The software consists of several Java threads that run concurrently. Sensor data are polled by threads and put into databases to reduce the network lag. The databases are used by a controller and a Kalman filter. Since most of the implementation is coded in Java it is possible to run it as a stand alone program on a computer that has Java installed. From 10 runs the trajectory offset was calculated to 0.9 cm with a standard deviation of 1.4 cm. The standard deviation of the heading was 2.2 degrees. This performance is essentially independent of the initial starting pose.

[1]  L.C. Bento,et al.  Multi-target detection and tracking with a laser scanner , 2004, IEEE Intelligent Vehicles Symposium, 2004.

[2]  H. Koshimizu,et al.  An algorithm to extract convex hull on theta - rho Hough transform space , 1988, [1988 Proceedings] 9th International Conference on Pattern Recognition.

[3]  Kalevi Hyyppä,et al.  A MATLAB/Java Interface to the MICA Wheelchair , 2004 .

[4]  Ingemar J. Cox,et al.  Blanche-an experiment in guidance and navigation of an autonomous robot vehicle , 1991, IEEE Trans. Robotics Autom..

[5]  Sada Wane,et al.  Dynamic control of the execution of trajectories by a mobile robot , 1991, Proceedings IROS '91:IEEE/RSJ International Workshop on Intelligent Robots and Systems '91.

[6]  S P Levine,et al.  The NavChair Assistive Wheelchair Navigation System. , 1999, IEEE transactions on rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society.

[7]  Johan Forsberg,et al.  Mobile robot navigation using the range-weighted Hough transform , 1995, IEEE Robotics Autom. Mag..

[8]  Stergios I. Roumeliotis,et al.  Weighted line fitting algorithms for mobile robot map building and efficient data representation , 2003, 2003 IEEE International Conference on Robotics and Automation (Cat. No.03CH37422).

[9]  Åke Wernersson,et al.  On covariances for fusing laser rangers and vision with sensors onboard a moving robot , 1998, Proceedings. 1998 IEEE/RSJ International Conference on Intelligent Robots and Systems. Innovations in Theory, Practice and Applications (Cat. No.98CH36190).

[10]  Sooyong Lee,et al.  Consecutive scanning based obstacle detection and probabilistic navigation of a mobile robot , 2003, Proceedings 2003 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2003) (Cat. No.03CH37453).

[11]  Johan Forsberg.  Mobile robot navigation using non-contact sensors , 1998 .

[12]  Sebastian Thrun,et al.  Detecting and modeling doors with mobile robots , 2004, IEEE International Conference on Robotics and Automation, 2004. Proceedings. ICRA '04. 2004.