Title: Investigating maneuverability and adaptability of a non-biomorphic swimming robot in the cluttered aquatic environment
Date: Friday, June 30, 2023
Time: 2:00 - 3:30 PM EST
Location: (Virtual) Zoom meeting link:
https://us04web.zoom.us/j/6501592154?pwd=K09LeDVXTVhnMy9mTVZLdi9XN0dxUT09
Meeting ID: 650 159 2154
Passcode: 0DsGZr
Bangyuan Liu
Robotics Ph.D. Student
School of Mechanical Engineering
Georgia Institute of Technology
Committee:
Dr. Frank L. Hammond III (Advisor) - School of Mechanical Engineering, Georgia Institute of Technology
Dr. Daniel Goldman - School of Physics, Georgia Institute of Technology
Dr. Alper Erturk - School of Mechanical Engineering, Georgia Institute of Technology
Dr. Layne Churchill - Georgia Tech Research Institute, Georgia Institute of Technology
Dr. Howie Choset - Robotics Institute, Carnegie Mellon University
Abstract
Aquatic swimmers, whether natural or artificial, leverage their maneuverability and morphological adaptability to operate successfully in diverse, complex underwater environments. Maneuverability allows swimmers the agility to change speed and direction within a constrained operating space, while morphological adaptability allows their bodies to deform as they avoid obstacles and pass through narrow gaps.
In this work, we design a soft, modular, non-biomorphic swimming robot that emulates the maneuverability and adaptability of biological swimmers. This tethered swimming robot is actuated by a two-degree-of-freedom (2-DOF) cable-driven mechanism that enables not only common maneuvers, such as undulatory surging and pitch/yaw rotation, but also, a novel roll rotation maneuver, which is theoretically studied and experimentally verified. This simple 2-DOF system demonstrates full 3D swimming abilities in a space-constrained underwater testbed. The soft compliant body and passive foldable fins of the swimming robot lend to its morphological adaptability, allowing it to move through narrow gaps, channels, and tunnels and to avoid obstacles without the need for a low-level feedback control strategy. Moreover, a larger scale version robot with a controllable folding fin will be designed and studied, which is expected to explore the robot's swimming capability, sense obstacle contacts, and improve swimming robot body adaptability to the underwater cluttered environment. The adaptability and maneuvering capabilities of our swimming robot offer a new approach to achieving underwater navigation in complex real-world settings.