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A hybrid lidar-based indoor navigation system enhanced by ceiling visual codes for mobile robots

Jiongtao Xiong, Yijun Liu, Xiangrong Ye, Long Han, Huihuan Qian, Yangsheng Xu

Year
2016
Citations
22

Abstract

Localization and navigation are fundamental issues to autonomous mobile robotics. In the case of the environmental map has been built, the traditional two-dimensional (2D) lidar localization and navigation system can't be matched to the initial position of the robot in dynamic environment and will be unreliable when kidnapping occurs. Moreover, it relies on high-cost lidar for high accuracy and long range. In view of this, the paper presents a low cost navigation system based on a low cost lidar and a cheap webcam. In this approach, 2D-codes are attached to the ceiling, to provide reference points to aid the indoor robot localization. The mobile robot is equipped with webcam pointing to the ceiling to identify 2D-codes. On the other hand, a low-cost 2D laser scanner is applied to build a map in unknown environment and detect obstacles. Adaptive Monte Carlo Localization (AMCL) is implements for lidar positioning, A* and Dynamic Window Approach (DWA) are applied in path planning based on a 2D grid map. The error analysis and experiments has validated the proposed method.

Keywords

LidarCeiling (cloud)Computer visionComputer scienceMobile robotArtificial intelligenceMotion planningRobotMobile robot navigationMonte Carlo localization

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