Vision and motion planning for a mobile robot under uncertainty
International Journal of Robotics Research
OBPRM: an obstacle-based PRM for 3D workspaces
WAFR '98 Proceedings of the third workshop on the algorithmic foundations of robotics on Robotics : the algorithmic perspective: the algorithmic perspective
Moving Target Classification and Tracking from Real-time Video
WACV '98 Proceedings of the 4th IEEE Workshop on Applications of Computer Vision (WACV'98)
Object Recognition from Local Scale-Invariant Features
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
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It is very important for a robot to obverse its environment in real-time and walk without collision in a crowd. This paper presents a motion planning method, based on visual feedback, for safe Human-Robot Interaction (HRI) in dynamic environments. Firstly, in order to improve accuracy of features marching, Scale Invariant Feature Transform (SIFT) is merged into binocular stereo vision, which is used to detect motion of people. Secondly, by improving Lazy PRM, a robot can find the shortest safe path and move to predetermined destination along the path. Experimental results show that position of people can be detected in real-time in environments with several people walking inside, and the accuracy can reach 96%. Therefore, a robot can arrive at the goal configuration node without collision with people much faster than Lazy PRM.