Shigenori Ito

Navigation system based on ceiling landmark recognition for autonomous mobile robot

In this paper, we propose a vision based navigation system for autonomous mobile robots which recognizes air-conditioning device (anemo) as landmarks located on ceiling. Because landmarks on ceiling are not obstructed by any objects, robots can find them easier than landmarks on the floor. In the recognition process, gathering quadrangles in the image are regarded as anemo, the gravity center and the slope of these quadrangles are calculated. Then the navigation system can calculate the distance and the angle of the anemo from map information. As a result, the navigation system can identify the present robots position and orientation. By the proposed algorithm, if the landmark is not being taken completely, the landmark is inferred by partial information. In the experiments, we compared the error made by the robot which are navigated by our system with the error made by the robot which moves based on deadreckoning.<<ETX>>

Navigation system based on ceiling landmark recognition for autonomous mobile robot-landmark detection based on fuzzy template matching (FTM)

We propose a vision based navigation system for autonomous mobile robots that recognizes outlets of air conditioning system (anemo) located on the ceiling as landmarks. Because landmarks on the ceiling are not obstructed by other objects, robots can find them easier than landmarks on the floor. To detect the landmark, we applied the fuzzy template matching (FTM) method. Based on FTM, a fuzzy template (FT) is modeled based on the edge information of landmarks in the image. In addition, we use neural network (NN) to detect landmarks quickly. Inputs of NN are the grades of fuzzy memberships and the learned NN directs FT to the landmark in the image. Because FTM does not use image processing, except edge extraction, it does not make processing error and the landmark can be detected precisely. The navigation system can calculate the distance and the angle of the anemo from the map information. As a result, the navigation system can identify the present robots position and orientation. By the proposed algorithm, precise and fast landmark detection become possible even if the landmark follows the shadow.

Navigation system based on ceiling landmark recognition for autonomous mobile robot -position/orientation control by landmark recognition with plus and minus primitives

A template matching is a popular method for visual recognition. It costs much time to detect the target object. We have applied fuzzy and neural network algorithm to solve this problem. However, the problem to mistake recognizing the target object is not solved. Hence, in this paper, we propose robust visual recognition algorithm for the autonomous robot navigation. The proposing algorithm employs a fuzzy template matching with the target object as well as the similar objects in the environment. As a result, the robot verifies the tentative recognition by comparing the likelihood of plus elements (target objects) with that of minus elements (similar objects). To integrate this algorithm into the robot navigation system, we propose a hierarchical control architecture. The validity of the proposing navigation system is shown with experimental results.

Development of air conditioning equipment inspection robot with vision based navigation system

665 In order to maintain a comfortable office environment periodical inspection of the air conditioning equipment is very important. It is necessary to measure the air temperature and the volume of the controlled outlet air correctly from the ceiling air diffuser. The periodical inspection of a large number of ceiling air diffusers must be done efficiently and in a short time. Up to now this hard work has been done by humans. However, we have developed a robot which will take the place of the human and perform these inspections automatically. This autonomous mobile robot recognises the position of ceiling air diffusers from map information supplied to it. The robot measures the air temperature and air volume, and moves on to the next diffuser and so on. In this paper we present an outline of this autonomous mobile robot.