Abstract: This paper studied the CSS-based indoor localization system which is easy to implement, inexpensive to compose the systems, additionally CSS-based indoor localization system covers larger area than other system. However, this system has problem which is affected by reflected distance data. This problem in localization is caused by the multi-path effect. Error caused by multi-path is difficult to be corrected because the indoor environment cannot be described. In this paper, in order to solve the problem by multi-path, we have supplemented the localization system by using pattern matching method based on extended database. Thereby, this method improves precision of estimated. Also this method is verified by experiments in gymnasium. Database was constructed by 1m intervals, and 16 sample data were collected from random position inside the region of DB points. As a result, this paper shows higher accuracy than existing method through graph and table.
Abstract: This paper presents a sensing system for 3D sensing
and mapping by a tracked mobile robot with an arm-type sensor
movable unit and a laser range finder (LRF). The arm-type sensor
movable unit is mounted on the robot and the LRF is installed at the
end of the unit. This system enables the sensor to change position and
orientation so that it avoids occlusions according to terrain by this
mechanism. This sensing system is also able to change the height of
the LRF by keeping its orientation flat for efficient sensing. In this kind
of mapping, it may be difficult for moving robot to apply mapping
algorithms such as the iterative closest point (ICP) because sets of the
2D data at each sensor height may be distant in a common surface. In
order for this kind of mapping, the authors therefore applied
interpolation to generate plausible model data for ICP. The results of
several experiments provided validity of these kinds of sensing and
mapping in this sensing system.
Abstract: In this paper, a new method of information fusion – DSmT (Dezert and Smarandache Theory) is introduced to apply to managing and dealing with the uncertain information from robot map building. Here we build grid map form sonar sensors and laser range finder (LRF). The uncertainty mainly comes from sonar sensors and LRF. Aiming to the uncertainty in static environment, we propose Classic DSm (DSmC) model for sonar sensors and laser range finder, and construct the general basic belief assignment function (gbbaf) respectively. Generally speaking, the evidence sources are unreliable in physical system, so we must consider the discounting theory before we apply DSmT. At last, Pioneer II mobile robot serves as a simulation experimental platform. We build 3D grid map of belief layout, then mainly compare the effect of building map using DSmT and DST. Through this simulation experiment, it proves that DSmT is very successful and valid, especially in dealing with highly conflicting information. In short, this study not only finds a new method for building map under static environment, but also supplies with a theory foundation for us to further apply Hybrid DSmT (DSmH) to dynamic unknown environment and multi-robots- building map together.