Optical Flow Based Navigation
نویسندگان
چکیده
As new technologies continue to develop, more and more robots are replacing humans in situations deemed too dangerous. However, current solutions are not fully automated, requiring offsite human operators for executing basic actions. The ideal solution would be a fully autonomous vehicle that could complete its objectives without any human intervention. In this project, the viability of optical flow based navigation was investigated. Optical flow, or optic flow, is the perception of object motion due to the object’s pixel shifts as the viewer moves relative to the environment. First, motion detection filters were developed and applied to image sequences in MATLAB. Then, they were implemented in optic flow based navigation MATLAB programs for an iRobot Create with a camera to provide video input. The robot successfully traversed through a textured environment but encountered difficulties when attempting to avoid textured obstacles and corners. Experiments were developed to compare the effectiveness of the Correlation and Gabor filters and to find the relationship between increased motion detection ability and processing time per frames. Possible future directions for this project include implementing GPU (Graphics Processing Unit), FPGA (Field-Programmable Gate Array), or even ASIC (Application-Specific Integrated Circuit) chips to speed up computation time, utilizing a wide-angle camera or an array of cameras to get a wider field of view, and integrating a q learning system.
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