For the development of an automatic floor cleaning robot system, an accurate positioning method in unstructured and dynamically changing environments is indispensable. Dead reckoning is a popular method, but is not reliable for measurement over long distances especially on uneven and slippery floors due to the accumulation error of wheel diameter and slippage. The landmark method, which estimates current position relative to landmarks, cannot be used in an uncharted and an unfamiliar environment. We have proposed a new method called "Cooperative Positioning System (CPS)." The main concept of CPS is to divide the robots into two groups, A and B where group A remains stationary and acts as a landmark while group B moves, then group B stops and acts as a landmark for group A. This process is repeated until the target position is reached. CPS has a far lower accumulation of positioning error than dead reckoning, and can work in three-dimensions. Also, CPS has inherent landmarks and therefore works in uncharted environments. In previous papers, we have introduced the prototype CPS machine models, CPS-I and CPS-II and demonstrated high performance as a positioning system in an unknown and uneven environment. In this paper, we report on the third prototype CPS model, CPS-III, that is designed specifically as an automatic floor-cleaning robot system, and the results of a floor cleaning experiment. In this system, we categorize these robots for two tasks, that is, an accurate positioning task achieved with 3 robots using the CPS strategy, and a floor-cleaning task executed by an omni-directional vehicle, so as to improve the efficiency of the floor-cleaning system. Experiments show that these robots can perform a floor-cleaning task in a corridor within a positioning error of 140.8 mm even after robots move over a distance of 101.7 m.
All Science Journal Classification (ASJC) codes
- Artificial Intelligence