Affiliation:
1. Chienkuo Technology University
2. Chung-shan institute of Science and Technology
Abstract
The image-guided system is the important issue for the automatic navigation. In this paper, a novel visually-guided disaster detection Robot (DD robot) is designed to carry out the automatic navigation function. Moreover, the DD robot is meticulously designed to detect gases or suspicious persons in the surrounding environment of the plant. Besides, we have successfully made our robots equipped with the devices by ourselves. These devices contain the disaster-detected sensors, the navigation module and the image module. In addition, we designed three operation modes: Automatic navigation mode (AN), Manual Remote Control mode (MRC) and the Visually-Guided mode (VG). Furthermore, the human-machine interface offers the users the view of information and also the details of the functions of the DD robot. The experimental results validate the practicality of the proposed visually-guided based automatic navigation system applied to disaster detection robots.
Publisher
Trans Tech Publications, Ltd.
Reference5 articles.
1. ACGIH, TLVs and BEIs : Based on the Threshold Limit Values for Chemical Substances and Physical Agents and Biological Exposure Indices, American Conference of Governmental Industrial Hygienists (ACGIH), Inc. Cincinnati, Ohio. (2009).
2. T. Pieter, in: Trends in Carbon Dioxide, NOAA / ESRL (2009).
3. I. Q. Whishaw, D. J. Hines, and D. G. Wallace, in: Dead reckoning (path integration) requires the hippocampal formation: evidence from spontaneous exploration and spatial learning tasks in light (allothetic) and dark (idiothetic) tests, Behavioural Brain Research, Vol. 127 (2001).
4. S. Ablameyko, V. Beveisbik, , M. Homenko, N. Paramonova and O. Patsko, in: Interpretation of colour maps. A combination of automatic and interactive techniques, Computing & Control Engineering Journal, Vol. 12, Issue 4 (2001), pp.188-196.
5. X. Xu, M. Ester, H.P. Kriegel and J. Sander, in: A Distribution-Based Clustering Algorithm for Mining in Large Spatial Databases, Proceedings of 14th International Conference on Data Engineering (1998), pp.324-331.