Position and orientation estimation of a front loader bucket using stereo vision

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School of Electrical Engineering | Master's thesis
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ix + 84
Stereopsis or Stereo vision is a technique that has been extensively used in computer vision these days helps to percept the 3D structure and distance of a scene from two images taken at different viewpoints; precisely the same way a human being visualizes anything using both eyes. The research involves object matching by extracting features from images and includes some preliminary tasks like camera calibration, correspondence and reconstruction of images taken by a stereo vision unit and 3D construction of an object:. The main goal of this research work is to estimate the position and the orientation of a front loader bucket of an autonomous mobile robot configured in a work machine name Avant which consists a stereo vision unit and several other sensors and is designed for outdoor operations like excavation. Several image features finding algorithms, including the most prominent two, S1FT and SURF has been considered for the image matching and object recognition. Both algorithms find interest points in an image in different ways which apparently accelerates the feature extraction procedure, but still the time requires for matching in both cases is left as an important issue to be resolved. As the machine requires to do some loading and unloading tasks, dust and other particles could be a major obstacle for recognizing the bucket s workspace, also it has been observed that the hydraulic arm and other equipment comes inside the FOV of the cameras which also makes the task much challenging. The concept of using markers has been considered as a solution to these problems. Moreover, the outdoor environment is very different from indoor environment and object matching is far more challenging due to some factors like light, shadows, environment etc. that change the features inside a scene very rapidly. Although the work focuses on position and orientation estimation, optimum utilization of stereo vision like environment perception or ground modelling can be an interesting avenue of future research.
Halme, Aarne|Hyyppä, Kalevi
Thesis advisor
Saarinen, Jari
Terho, Sami
stereo vision, SURF, SIFT, Haar, object detection, fiducial markers, camera calibration,