Abstract
This paper presents a framework of local path-planning technique for stereo camera-equipped mobile robot with real-time local free road detection in unknown indoor environments. The aim of the proposed framework is to produce an optimized local path using 3D point cloud data, from which a global optimized trajectory can be generated in unknown indoor scene by finding series of sub-goal-points to start point. The framework is constructed with free road detection, variant rapidly-exploring random tree for a path planning and reactive obstacle avoidance behaviors. The information of free road and obstacles computed by 3D point cloud is prepared for path-planning and quick obstacle avoidance. We can make use of the precise relative position obtained by the sensor to efficiently solve the navigation problem, without building a global map. The result of the whole experiments shows that the framework proposed in the paper has a satisfactory performance of local navigation and path-planning.
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Yang, H., Zhang, J., Chen, S. (2014). Stereo Camera Based Real-Time Local Path-Planning for Mobile Robots. In: Li, S., Liu, C., Wang, Y. (eds) Pattern Recognition. CCPR 2014. Communications in Computer and Information Science, vol 483. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-45646-0_35
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DOI: https://doi.org/10.1007/978-3-662-45646-0_35
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