| There is little prior knowledge for mobile robots in unknown indoor environment.Therefore, map building can improve the adaptability of mobile robots to the indoorenvironment and is one of the key technologies for the application of mobile robots incomplex and unknown environments. The methods of map building based on gridenvironment are important means to improve real-time and flexibility of mobile robotsin unknown environment. Among most methods of map building, the methods of mapbuilding based on grid environment have been widely applied into map building formobile robots in unknown environment because of their low calculation complexity ofthe parameters and the characters for easy to be building and maintain in recent years.According to the problem of high complexity methods of map building nowadays,a new method of map building is presented for mobile robots in unknown indoorenvironments. It combined Internal Spiral Coverage (ISC) algorithm, A*algorithmand wildfire algorithm to detect and build the map in unknown indoor environments.The rasterization of indoor environment can reduce the calculation time and improvethe efficiency of the exploration of mobile robots on the environment.In an unknown indoor environment with complex obstacles, the mobile robot willimmediately go around the obstacle to quickly identify its location and size once anobstacle is explored. When the mobile robot enters into “trap”, in other words, thegrids map around the robot are known and have been coveraged, the grassfirealgorithm and A*algorithm are adopted to help the mobile robot get rid of the difficultposition to continue its map building.Finally, the proposed method of map building is verified in GA. The simulationresults show that the proposed method of map building based on different unknownindoor environments is very effective. In the process of map building, thenew-building map with good accuracy can improve the adaptability of mobile robot inunknown indoor environments. |
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