Integration of a visual perception pipeline for object manipulation

Detta är en Master-uppsats från KTH/Skolan för elektroteknik och datavetenskap (EECS)

Sammanfattning: The integration of robotic modules is common both in industry and in academia, especially when it comes to robotic grasping and object tracking. However, there are usually two challenges in the integration process. Firstly, the respective fields are extensive, making it challenging to select a method in each field for integration according to specific needs. Secondly, because the integrated system is rarely discussed in academia, there is no set of metrics to evaluate it. Aiming at the first challenge, this thesis reviews and categorizes popular methods in the fields of robotic grasping and object tracking, summarizing their advantages and disadvantages. This categorization provides the basis for selecting methods according to the specific needs of application scenarios. For evaluation, two well-established methods for grasp pose detection and object tracking are integrated for a common application scenario. Furthermore, the technical, as well as the task-related challenges of the integration process are discussed. Finally, in response to the second challenge, a set of metrics is proposed to evaluate the integrated system. 

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