This paper suggests a new exploration strategy of an autonomous mobile robot in an unknown environment. Determination of a temporary goal based on a representation of work area named exploration quadtree is proposed. The exploration quadtree provides the information on quality of the regions concerned in a robot’s workspace. Using this quadtree the robot easily finds the next temporary goal that makes exploration more efficient. The quadtree is made up from a sonar probability map that is constructed by sonar range sensing and Bayesian probability theory. We then propose a method that plans a path between the determined temporary goals based on a probability map. The developed methods were implemented on a real mobile robot, AMROYS-II, which was built in our laboratory, and shown to be useful enough in a real environment that can be projected onto a two-dimensional space.

1.
Borenstein
J.
, and
Koren
Y.
,
1991
a, “
The Vector Field Histogram—Fast Obstacle Avoidance for Mobile Robots
,”
IEEE Trans. on Robotics and Automation
, Vol.
7
, No.
3
, pp.
278
288
.
2.
Borenstein
J.
, and
Koren
Y.
,
1991
b, “
Histogramic In-Motion Mapping for Mobile Robot Obstacle Avoidance
,”
IEEE Trans. on Robotics and Automation
, Vol.
7
, No.
4
, pp.
535
539
.
3.
Cho
D. W.
,
1990
, “
Certainty Grid Representation for Robot Navigation by a Bayesian Method
,”
Robotica
, Vol. (
8)
, pp.
159
165
.
4.
Lim, J. H., and Cho, D. W., 1992, “Physically Based Sensor Modeling for a Sonar Map in a Specular Environment,” Proc. of the 1992 IEEE Int. Conf. of Robotics and Automation, Nice, France, pp. 1714–1719.
5.
Lim, J. H., and Cho, D. W., 1993, “Consideration of Multipath Effect in Sonar Map Construction for an Autonomous Mobile Robot,” Proc. of The 1993 Korea Automatic Control Conference, Seoul, Korea, pp. 106–112.
6.
Lim, J. H., and Cho, D. W., 1994a, “Specular Reflection Probability in the Certainty Grid Representation,” ASME JOURNAL OF DYNAMIC SYSTEM, MEASUREMENT, AND CONTROL, Vol. 116, No. 3.
7.
Lim, J. H., and Cho, D. W., 1994b, “Real Time Map Construction and Position Estimation for an Autonomous Mobile Robot using Sonar Sensors,” To appear in Int. J. of Computers and Their Applications.
8.
Lozano-Perez
T.
,
1983
, “
Spatial Planning: A Configuration Space Approach
,”
IEEE Trans. on Computers
,
C-32
,
2
, pp.
108
120
.
9.
Lumelsky, V. J., and Stepanov, A. A., 1987, “Path-Planning Strategies for a Point Mobile Automaton Moving Amidst Unknown Obstacle of Arbitrary Shape,” Algorithmica, Springer-Verlag, New York, pp. 403–430.
10.
Moravec, H. P., and Elfes, A., 1985, “High Resolution Maps from Wide Angle Sonar,” Proc. of IEEE Int. Conf. on Robotics and Automation, St. Louis, MO, pp. 116–121.
11.
Moravec, H. P., and Cho, D. W., 1989, “A Bayesian Method for Certainty Grids,” AAAI Spring Symposium on Robot Navigation, Stanford, CA, March 1989, pp. 57–60.
12.
Noborio, H., Naniwa, T., and Arimoto, S., 1991, “A Feasible Motion-Planning Algorithm for a Mobile Robot on a Quadtree Representation,” Proc. of IEEE Int. Conf. on Robotics and Automation, Sacramento, CA, pp. 327–332.
13.
Samet, H., 1990, The Design and Analysis of Spatial Data Structures, Addison-Wesley, Reading, MA.
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