Mobile Robot Localization Method Research Articles

不正確さを許すマップにおける移動ロボットの自己位置推定

A major problem in mobile robot navigation using a map is that an accurate map needs a lot of building cost. A framework of navigation using a roughly measured map would be a solution of this problem. The paper proposes a Topological-Geometrical map, or TG map for short, which permits inaccurate description, and a method of mobile robot localization on a TG map. A TG map is built by defining the relative poses between geometrical entities in the environment. The models of the geometrical entities are supposed to be predefined, and the relative poses between them can be as inaccurate as those measured by eye. These features allow the map-building cost to be small. The robot pose is represented in a local frame attached on each entity since the robot pose based on a global reference frame might be inconsistent because of the inaccuracy of the map. Errors in relative poses between entities are represented by probability density functions, and the robot pose is estimated using a variant of Markov localization which is augmented so as to incorporate map errors into data fusion process. Simulation and experiments show that the robot pose is estimated correctly on a TG map by the proposed method.

A Fast Linear Method for Mobile Robot Localization from Landmark Bearings

The paper presents an algorithm which estimates the position and orientation of a mobile robot from three or more noisy landmark bearing measurements, The main question answered is how to deal correctly and efficiently with the case of when more than three measurements are provided. The method is based on linearc onstraints, one due to each bearing measurement. This linear system can be solved at low computational cost but yields not very accurate results. We therefore transform the system to an equivalent linear system which yields virtually optimal results at a small fraction of the cost of a non-linear optimization method which usually achieves the optimal result. Experimental results showing the quality of the results and the low computational cost are presented. The analysis that we performed can also be applied to other problems which result in fast accurate estimation algorithms.

A two-stage mobile robot localization method by overlapping segment-based maps

This paper presents a new method for accurately estimating the pose (position and orientation) of a mobile robot by registering a segment-based local map observed from the current robot pose and a global map. The method works in a two-stage procedure. First, the orientation is determined by aligning the local and global map through a voting process based on a generalized Hough transform. Second, it uses a coarse-to-fine approach for selecting candidate positions and a weighted voting scheme to determine the degree of overlap of the two maps at each of these poses. Unlike other methods previously proposed, this approach allows us to uncouple the problem of estimating the robot orientation and the robot position which may be useful for some applications. In addition it can manage environments described by many (possibly short) segments. This paper presents some experimental results based on our mobile robot RAM-2 that show the accuracy and the robustness of the proposed method even for poor quality maps and large dead-reckoning errors.

Mobile robot localization using color signboard

Accurate, flexible and low-cost localization is an important issue for achieving autonomous and cooperative motions of mobile robots. This paper proposes a localization method for indoor mobile robots by using vision and artificial signboard. The signboards are placed in an environment and attached to the robots to decide the absolute positions and relative positions, respectively, of the robots. The important contribution is using signboard for the relative localization. Use of forward-looking camera and eye-level signboard allows us to achieve both the absolute and relative localization in a multi-robot environment, however, it brings a potential problem that the signboard viewed with the camera tends to be occasionally occluded with mobile robots hovering in the environment. The signboard is therefore designed such that the forward-looking camera can reliably detect the signboard even though it is partially blocked with unforeseen obstructions. A color-coding pattern is printed on the signboard to identify a lot of signboards in the multi-robots environment. The Kalman filter and the Interacting Multiple Model method are applied to find accurate positions of the robots by using the identified signboards. Experimental results show the feasibility of the proposed localization method.

A Rapidly Converging Recursive Method for Mobile Robot Localization

This paper proposes a simple method for estimating the position of a robot from relatively few sensor readings. Our algorithms are intended for applications where sensor readings are expensive or otherwise limited, and the readings that are taken are subject to con siderable errors or noise. This method exhibits faster convergence with fewer measurements and greater accuracy than that exhibited by the discrete Kalman filter in this type of application. Our approach is validated with a mobile robot, on which a camera is used to obtain bearing information with respect to landmarks in the environment.

The Improvement of Sonar-Based Mobile Robot Localization Method by Multiple Beacons

This paper proposes a new method of estimating the position and heading angle of a mobile robot navigating in indoor environments. In this paper, typical positioning errors of a localization method of using two beacons are computed. The proposed localization method utilizes three passive beacons in order to reliably determine the mobile robot's current position and heading angle. Localization experiments using two beacons as well as three beacons are conducted in indoor environments. The performance and validity of the proposed method were evaluated through a series of the experiments and the experimental results of the navigation were presented.