Haruhiko Niwa

Pose estimation of a mobile robot on a lattice of RFID tags

A method of estimating pose of a robot on a lattice of RFID tags is described. In recent years, radio frequency identification (RFID) technology has become a very popular method for localizing robots because it is robust to disturbances such as lighting and obstacles, which adversely affect the conventional methods that use cameras, supersonic waves and so on. Despite the advantage that RFID tags, especially passive tags, can be inexpensively mass-produced, previous studies using RFID have not targeted the detailed work of robots because they have made use of RFID tags dotted over a wide area as landmarks. Therefore, it is still difficult to use the technology at home. There is a model room in WABOT-HOUSE Laboratory of Waseda University where the floor is equipped with a lattice of RFID tags at 300 mm intervals, simulating a future home environment where robots interact symbiotically with humans. We speculate that such an environment, where the tags are distributed at regular intervals, is one of the most probable infrastructures of the near future and propose a method that use Monte Carlo localization to estimate the pose of robot on the lattice. Our experiments show that robots can localize their position more precisely than the interval of tags and also estimate their orientation successfully by using the proposed method when two readers are placed in appropriate positions.

Active localization of a robot on a lattice of RFID tags by using an entropy map

We have developed a novel way for robots to estimate their pose dynamically in an environment in which RFID tags have been arranged. We previously developed a method for localizing robots using a particle filter. Testing in a room equipped with a lattice of RFID tags at 300-mm intervals revealed that the estimation fails when the robots RFID readers are near the center of the robots rotation because the reader could not detect enough tags by rotating movements when the robots positions are not suitable. We have overcome this problem by developing an active localization algorithm that generates an entropy map from the RFID arrangement information, predicts the pose using a particle filter, and attracts the robot to the target using a dynamic model, the fundamental unit of which is rotation-based angular velocity. Testing demonstrated that a robot using this algorithm and an entropy map can estimate its pose robustly without falling into a dead zone by moving only about 20 cm at most.

Transport services on indoor map generating system using spatially distributed RFID tags for home environment

This paper proposes a methodology for generating an indoor map of the home environment using widely installed RFID tags, which is being experimentally developed in the model room in the WABOT-HOUSE Laboratory[1]. Our laboratory is studying a system that generates and renews an environmental map of a room in real time in cooperation with three subsystems: a tag infrastructure where many RFID (Radio Frequency Identification) tags are widely installed over the environment, indoor RT(Robot Technology) modules, such as robots and furniture with embedded computing technology, and a home server module that monitors their spatial information. In this paper, we describe the basic concept and contents of the system, then we propose a method of localizing the robot and of moving to a destination while avoiding obstacles. Finally we report an experiment on which the robot succeed in advancing to a resident in the room, as an example of transport services making use of our system.