This paper proposes a novel hybrid-structured model for the adaptive localization of robots combining a stochastic localization model and a rhythmic action model, for avoiding vacant spaces of landmarks efficiently. In regularly arranged landmark environments, robots may not be able to detect any landmarks for a long time during a straight-like movement. Consequently, locally diverse and smooth movement patterns need to be generated to keep the position estimation stable. Conventional approaches aiming at the probabilistic optimization cannot rapidly generate the detailed movement pattern due to a huge computational cost; therefore a simple but diverse movement structure needs to be introduced as an alternative option. We solve this problem by combining a particle filter as the stochastic localization module and the dynamical action model generating a zig-zagging motion. The validation experiments, where virtual-line-tracing tasks are exhibited on a floor-installed RFID environment, show that introducing the proposed rhythm pattern can improve a minimum error boundary and a velocity performance for arbitrary tolerance errors can be improved by the rhythm amplitude adaptation fed back by the localization deviation.

Reader antennas' configuration for two wheeled robots were evaluated to estimate their posture from floor-installed RFID tags. RFID systems where IC tags are installed under/on floors have widely been utilized in recent years as the next positioning infrastructure. The reader antennas should be properly placed on a robot so that such an environment can give full play to its potential capabilities of positioning the robot. This problem calls for guidelines in designing the configuration of reader antennas. Experiments using actual robots cannot offer sufficient data because of time and physical limitations, which prevent helpful and reproducible evaluations. We overcame this problem by constructing a simulation environment using a localization model and by evaluating the effects of configurations on positioning accuracy using computations. Of particular note, we found a “forward-backward configuration effect” from the results and had a detailed a discussion on how it occurred. Finally, a simple experiment using an actual robot validated the effect.

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 robot's RFID readers are near the center of the robot's rotation because the reader could not detect enough tags by rotating movements when the robot's 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.

Wabot-House Research Laboratory is working on a project that will enable integrating robots into our everyday life. We believe that a “structured environment” (SE) will be one of most important concepts for this project. An SE generally means that objects near people that have some database or intelligence provide certain information to those people. An SE will also assist robot recognition or movement planning. Now, we focus on a global positioning system (GPS), which is a global SE that gives users or robots their positions whenever and wherever they are outdoors all over the world. GPS will strongly support robot self-positioning. However, GPS has the problem that it cannot be used when the robots are indoors. To solve this problem, we experimentally mounted four pseudolites (‘pseudo’ means imitated and ‘lite’ means satellite) in our laboratory and developed indoor GPS. The system worked well unless the robot was near the wall, where cycle slip often occurred. To examine the characteristics and reason for cycle slip, we measured the radio-wave environment in the laboratory. The first half of this paper introduces this system. The last reports results and findings about this experiment.

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.

This paper presents a novel construction of a locomotion system that compensates for walking-sense with simple interfaces using hands or fingers. The realization of moving with body-sense in virtual space has required high-quality system designs including walking cancellations, haptic feedback, and high-resolution displays. However, such approaches result in increasing costs of calculation and space, which obstruct the spread of VR technology. We therefore propose a new framework of locomotion systems with simple interfaces that give users "passivity and restraint", which are essential components of walking-sense. They are realized with mutual entrainment between a nonlinear oscillator and users' input. Two experiments were conducted for evaluation. The first one showed that our system gives users sense of distance based on a body standard and sense of rhythm with stable input. The second one demonstrated that the users of our system can experience a subjective body-sense and a sense of velocity.