Vision-based Control of Soft Continuum Robots
Abstract: Continuum robots mark a revolutionary shift in robotics, thanks to their flexible mechanics and hyper-redundant degrees of freedom. They present great potential for applications in medical and assistive robotics. Most existing control literature focuses on regulating the end effector pose of continuum robots. These approaches fail to exploit the redundancy of continuum manipulators. In contrast, my research develops novel control strategies that regulate the entire shape of the robot using visual cues from an external camera observing the robot. Utilizing vision to close the loop enables us to adapt to changes in the system behavior in real-time and allows for incorporating task-based constraints into the control loop. In the remainder of my PhD, I aim to extend the convergence of my proposed image-based controllers to the 3D workspace of the robot and investigate the application of the proposed control algorithms to practical assistive tasks such as opening drawers and retrieving objects. Such tasks require the robot to interact with its environment. This environmental interaction introduces additional uncertainty to the robot’s model, which is typically developed under no-load conditions, and requires additional constraints on the control formulation and task planning front.
Advisor: Professor Berk Calli
Committee: Professor Cagdas Onal, Professor Loris Fichera, Professor Zhu Mao
Zoom Link: https://wpi.zoom.us/j/93396037021