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A 2.5D Map-Based Mobile Robot Localization via Cooperation of Aerial and Ground Robots

Tae Hyeon Nam, Jae Woong Shim, Young Cho

发表年份
2017
引用次数
31
访问权限
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摘要

Recently, there has been increasing interest in studying the task coordination of aerial and ground robots. When a robot begins navigation in an unknown area, it has no information about the surrounding environment. Accordingly, for robots to perform tasks based on location information, they need a simultaneous localization and mapping (SLAM) process that uses sensor information to draw a map of the environment, while simultaneously estimating the current location of the robot on the map. This paper aims to present a localization method based in cooperation between aerial and ground robots in an indoor environment. The proposed method allows a ground robot to reach accurate destination by using a 2.5D elevation map built by a low-cost RGB-D (Red Green and Blue-Depth) sensor and 2D Laser sensor attached onto an aerial robot. A 2.5D elevation map is formed by projecting height information of an obstacle using depth information obtained by the RGB-D sensor onto a grid map, which is generated by using the 2D Laser sensor and scan matching. Experimental results demonstrate the effectiveness of the proposed method for its accuracy in location recognition and computing speed.

关键词

RobotComputer visionArtificial intelligenceMobile robotRGB color modelComputer scienceSimultaneous localization and mappingElevation (ballistics)Matching (statistics)Remote sensing

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