Robust Image-Servo Control of Robotic Manipulators for Unstructured Environments

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Despite significant advances in robot control, robot positioning problem still requires significant effort in structuring the robotic cells and robot teaching for new tasks. The resulting high engineering costs prevent robots from being versatile reprogrammable machines, adapting quickly to new tasks. The "long-term" objective of this research program is on the development of high-performance control methods using image servoing ("IS"), to enable robot operations in unstructured environments. Despite enormous potential of IS, lack of robustness has hindered the integration of IS into many real-world applications. Also the previous work has mainly focused on visual servoing, leaving many issues related to the integration of other imaging sensors unsolved. The short-term objectives of this proposal focus on the unresolved issues for the development of "robust" control techniques using image feedback. In addition to vision sensor, the focus will be on the images from ultrasound/echo, computed tomography, and fluoroscopy. Key features of the proposed research include: i) development of a robust feature presentation scheme in the IS context; ii) development of the first comprehensive IS loop uncertainty model that will be used to design a novel hybrid framework for robust multi-regime motion planning and control techniques; and iii) extending the results to solve difficult positioning problems in new applications such as the control of continuum robots. The proposed research results could eliminate cell structuring and robot teaching efforts, and would provide the potential to relax the mechanical accuracy and stiffness requirements for robotic mechanisms, reducing their cost and extending their applications. The outcome of this research work is expected to entail unique and systematic procedures for the design of robust manipulation systems. The availability of such procedures could have a significant and immediate impact by improving the execution of current tasks and by facilitating applications previously taught to be almost impossible with classical techniques. Also, this research will yield to the foundation of new programming paradigm, in which the goals will be specified in integrated task and image spaces.