Merging of Depth Image Between Stereo Camera and Structure Sensor on Robot “FloW†Vision

Dadet Pramadihanto, Ardiansyah Alfarouq, Suryo Aji Waskitho, Sritrusta Sukaridhoto


Human can recognize an object just by looking at the environment, this capability is very useful for designing the reference of humanoid robot with the ability of adapting it on its environment. By knowing the field conditions that exist in such environments, robot can understand the obstacles or anything that can be passed. To do that, robot vision needs to have a knowledge to understanding an obstacles that exist around it. Because of these problems, this paper shows a method for reducing error rate of vacant space in the data depth by combining a stereo camera and structure sensor. Merging the stereo camera and structure sensor can extract depth information becomes dense. The proposed method has been successfully running the whole algorithm built and has a density of depth with an average error rate of vacant space is 18.10%.


humanoid robot; robot vision; RGB-D sensor; depth calibration; computer vision.

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Published by INSIGHT - Indonesian Society for Knowledge and Human Development