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Journal ArticleDOI

Development of Method Using a Combination of DGPS and Scan Matching for the Making of Occupancy Grid Maps for Localization

20 Jun 2013-Journal of robotics and mechatronics (Fuji Technology Press Ltd.)-Vol. 25, Iss: 3, pp 506-514
About: This article is published in Journal of robotics and mechatronics.The article was published on 2013-06-20. It has received 8 citations till now. The article focuses on the topics: Occupancy grid mapping & Matching (statistics).
Citations
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Journal ArticleDOI
TL;DR: This article focuses on the SLAM technology, including a brief overview of its history, insights from the author, and, finally, introduction of a specific example that the author was involved.
Abstract: Simultaneous localization and mapping (SLAM) forms the core of the technology that supports mobile robots. With SLAM, when a robot is moving in an actual environment, real world information is imported to a computer on the robot via a sensor, and robot’s physical location and a map of its surrounding environment of the robot are created. SLAM is a major topic in mobile robot research. Although the information, supported by a mathematical description, is derived from a space in reality, it is formulated based on a probability theory when being handled. Therefore, this concept contributes not only to the research and development concerning mobile robots, but also to the training of mathematics and computer implementation, aimed mainly at position estimation and map creation for the mobile robots. This article focuses on the SLAM technology, including a brief overview of its history, insights from the author, and, finally, introduction of a specific example that the author was involved.

9 citations

References
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Journal ArticleDOI
TL;DR: Outdoor navigation for a mobile robot by using differential GPS (DGPS) and odometry in a campus walkway environment is described and a novel position correction method by fusing GPS and Odometry is proposed.
Abstract: This paper describes outdoor navigation for a mobile robot by using differential GPS (DGPS) and odometry in a campus walkway environment. The robot position is estimated by fusion of DGPS and odometry. The GPS receiver measures its position by radio waves from GPS satellites. The error of GPS measurement data increases near high buildings and trees because of multi-path and forward diffractions. Thus, it is necessary to pick up only accurate DGPS measurement data when the robot position is modified by fusing DGPS and odometry. In this paper, typical DGPS measurement data observed near high buildings and trees are reported. Then, the authors propose a novel position correction method by fusing GPS and odometry. Fusion of DGPS and odometry is realized using an extended Kalman filter framework. Moreover, outdoor navigation for a mobile robot is accomplished by using the proposed correction method.

89 citations

Proceedings ArticleDOI
19 May 2008
TL;DR: Experimental results show the performance of the localization system compared to a previously measured ground truth in a differential drive mobile vehicle on real forested paths.
Abstract: This paper describes a 2D localization method for a differential drive mobile vehicle on real forested paths. The mobile vehicle is equipped with two rotary encoders, Crossbow's NAV420CA inertial measurement unit (IMU) and a NAVCOM SF-2050M GPS receiver (used in StarFire-DGPS dual mode). Loosely-coupled multisensor fusion and sensor fault detection issues are discussed as well. An extended Kalman filter (EKF) is used for sensor fusion estimation where a GPS noise pre-filter is used to avoid introducing biased GPS data (affected by multi-path). Normalized innovation squared (NIS) tests are performed when a GPS measurement is incorporated to reject GPS data outliers and keep the consistency of the filter. Finally, experimental results show the performance of the localization system compared to a previously measured ground truth.

54 citations

Journal ArticleDOI
TL;DR: This research developed an intelligent robotic cart (senior car) that moves autonomously along a given course to help people transfer luggage or themselves and proposed simple and novel algorithms for localization using a grid map and navigation for four-wheeled robots.
Abstract: This research aims at development of a stable mobile robot (personal mobility robot) that can navigate automatically on sidewalks where ordinary citizens are coming and going. Many studies have investigated automated vehicles that move on public roads. In the case of a road environment, many infrastructures and traffic regulations exist. In contrast, in a sidewalk environment, human and robots cross the same area without clear rules. For these reasons, some paths or landmarks are often blocked by unknown obstacles such as bicycles and passing pedestrians. Therefore, the most important requirements for a mobile robot are robust localization and safe navigation without collisions. We proposed simple and novel algorithms for localization using a grid map and navigation for four-wheeled robots. We also developed an intelligent robotic cart (senior car) that moves autonomously along a given course to help people transfer luggage or themselves. The sensors used in this system are three small laser scan...

15 citations

Proceedings ArticleDOI
01 Dec 2011
TL;DR: Experiences of the Tsukuba Challenge 2009 and 2010, or the Real World Robot Challenge, which aims at promoting practical technologies for autonomous mobile robot working in pedestrian environment, are reported.
Abstract: This paper reports experiences of the Tsukuba Challenge 2009 and 2010, or the Real World Robot Challenge. The challenge aims at promoting practical technologies for autonomous mobile robot working in pedestrian environment. The robot has to travel 1 km along a specified route without human aid, modifying the environments, or causing any dangers to human safety. This paper discusses failure due to unexpected behavior of pedestrians in the 2009 challenge and solutions for success in the challenge 2010.

10 citations