Mobile robot navigation algorithm using a vector-based topological map and virtual Jacobian

Abstract

In this paper, a vector-based topological map is to be built consisting of available directions (moving directions) and the distances between nodes. This map represents the whole environment as a skeleton, using nodes similar to vectors independent of geometrical information of obstacles. To build a vector-based topological map, the following are developed: (a) acquisition of reliable range values using local minimum values, (b) fuzzy inference system (FIS) for extracting available directions, and (c) collision avoidance using virtual Jacobians. First, only local minimum values are used among the range of sensor values in order to decrease the effect of specular reflection and calculate available directions using the FIS. Specially, the number of consequent membership functions is determined as the number of obstacle orientations around a mobile robot, enabling the mobile robot to find available directions independently of the geometrical information of obstacles. Finally, to avoid collisions, a virtual Jacobian method is used because a vector-based topological map does not include the geometrical information about obstacles. The proposed algorithms have been verified in the simulation and implemented on a robot in the real environment.

Keywords

navigation vector-based topological map virtual Jacobian mobile robot

Get full access to this article

View all access options for this article.

References

Fukuda

Kubota

An intelligent robotic system based on a fuzzy approach

Proc. IEEE, September 1999, 87 (9), 1448–1470.

Tsourveloudis

N. C.

Valavanis

K. P.

Hebert

Autonomous vehicle navigation utilizing electrostatic potential fields and fuzzy logic

IEEE Trans. Robotics and Automn, August 2001, 17 (4), 490–497.

Choset

Nagatani

Topological simultaneous localization and mapping (SLAM): Toward exact localization without explicit localization

IEEE Trans. Robotics and Automn, April 2001, 17 (2), 125–137.

Van Zwynsvoorde

Simeon

Alami

Building topological models for navigation in large scale environments

In Proceedings of the 2001 IEEE International Conference on Robotics and automation, 21-26 May 2001, pp. 4256–4261.

Wong

S. C.

MacDonald

B. A.

A topological coverage algorithm for mobile robots

In Proceedings of the 2003 IEEE/RSJ International Conference on Intelligent robots and systems, October 2003, pp. 1685–1690.

Tomatis

Nourbakhsh

Siegwart

Simultaneous localization and map building: A global topological model with local metric maps

In Proceedings of the 2001 IEEE/RSJ International Conference on Intelligent robots and systems, 29 October-3 November 2001, pp. 421–426.

Chang-Hyuk Choi, Jae-Bok Song, Woojin Chung, and Musang Kim

Topological map building based on thinning and its application to localization

In Proceedings of the 2002 IEEE/RSJ International Conference on Intelligent robots and systems, October 2002, pp. 552–557.

Howie

Ilhan

Joel

Mobile robot navigation: Issue in implementating the generalized Vornoi graph in the plane

In Proceedings of the 1996 IEEE/SICE/RSJ International Conference on Multisensor fusion and integration for intelligent systems, December 1996, pp. 241–248.

Nagatani

Iwai

Tanaka

Sensor based navigation for car-like mobile robots using generalized Vornoi graph. In Proceedings of the 2001 IEEE/RSJ International Conference on Intelligent robots and systems, 29 October-3 November 2001, pp. 1017–1022.

10.

Zou Yi, Ho Yeong Khing, Chua Chin Seng, and Zhou Xiao Wei

Multi-ultrasonic sensor fusion for mobile robots. In Proceedings of the IEEE Intelligent Vehicles Symposium 2000, 3-5 October 2000, pp. 387–391.

11.

Peter

Herbert

Localization of 3D objects based on ultrasonic data, considering the influence of measurement uncertainty. In Proceedings of the IEEE, Sensors, 2003, Vol. 1, 22–24 October 2003, pp. 12–17.

12.

Fausett

L. V.

Applied numerical analysis using Matlab, 1999 (Prentice-Hall, Englewood Cliffs, New Jersey).

13.

Jang

J.-S. R.

Sun

C.-T.

Mizutani

Neurofuzzy and soft-computing, 1997 (Prentice-Hall, Englewood Cliffs, New Jersey).

14.

Horowitz

Sahni

Anderson-Freed

Fundamentals of data structures in C, 1992 (Computer Science Press).