【摘 要】
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With the rapid development in the service,medical,logistics and other industries,and the in-creasing demand for unmanned mobile devices,mobile robots with the ability of independent map-ping,localization and navigation capabilities have become one of the
【机 构】
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School of Mechanical Engineering and Automation,Beihang University,Beijing 100191,P.R.China;Research
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With the rapid development in the service,medical,logistics and other industries,and the in-creasing demand for unmanned mobile devices,mobile robots with the ability of independent map-ping,localization and navigation capabilities have become one of the research hotspots.An accurate map construction is a prerequisite for a mobile robot to achieve autonomous localization and naviga-tion.However,the problems of blurring and missing the borders of obstacles and map boundaries are often faced in the Gmapping algorithm when constructing maps in complex indoor environments.In this pursuit,the present work proposes the development of an improved Gmapping algorithm based on the sparse pose adjustment (SPA) optimizations.The improved Gmapping algorithm is then applied to construct the map of a mobile robot based on single-line Lidar.Experiments show that the improved algorithm could build a more accurate and complete map,reduce the number of particles required for Gmapping,and lower the hardware requirements of the platform,thereby sav-ing and minimizing the computing resources.
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