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Image-based visual servoing with hybrid camera configuration for robust robotic grasping

University of British Columbia

A challenging anthropomorphic characteristic which a robotic manipulator should acquire is vision. When first introduced to manufacturing and material-handling industries, robots were taught to move “blindly” in a structured environment where the position and the orientation of the manipulated object were assumed to be known. Since then, a spectrum of visual servoing techniques has been developed to increase the versatility and accuracy of the robotic manipulators for carrying out tasks in less structured environments. In particular, the concept of continuous motion control of robotic systems using a visual feedback loop has been applied recently to unstructured environments. In the work presented in this thesis, a functioning mobile manipulator platform, named Autonomous Intelligent Mobile Manipulator (AIMM) with a hybrid camera configuration has been developed. This platform is a member of the cooperative heterogeneous mobile robotic team at the Industrial Automation Laboratory (IAL) of the University of British Columbia (UBC). Given the increasing threat of terrorism and natural disasters around the world, the encompassing research explores new robotic solutions for search and rescue applications. Specifically, the LkL robotics subgroup develops robotic capabilities that can assist or even replace human rescuers in situations that involve life threatening risks. The main contribution of the work in this thesis can be summarized by its two aspects: hardware and control scheme. The developed mobile manipulator consists of a light-weight yet capable manipulator, a mobile robotic base, and a hybrid camera configuration using both a monocular camera and a stereo camera. The classical image-based visual servoing scheme has been improved by techniques of depth estimation and neural network-based grasping. In the present work, both the platform and the control scheme have been tested in real-life scenarios where multiple robots complete a complex task of object handling in an unstructured environment. Future directions in platform upgrade and visual servoing research are proposed as well.

Text

2010-03-24

Attribution-NonCommercial-NoDerivatives 4.0 International

http://hdl.handle.net/2429/22478

Mechanical Engineering

University of British Columbia

UBCV

http://creativecommons.org/licenses/by-nc-nd/4.0/