Title: Characterization of Soft Structures for Synergy-Based Performance Optimization in Robotic Grasping and Other Manipulation Tasks
 

Date: Wednesday, May 11, 2022

Time: 1:00 PM - 3:00 PM EST

Location: Whitaker 3115 (McIntire Conference Room) https://bluejeans.com/465504245/9726
 

Elizabeth Fox

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. Jaydev Desai- School of Biomedical Engineering, Georgia Institute of Technology
 

Dr. Jun Ueda- School of Mechanical Engineering, Georgia Institute of Technology
 

Dr. Gregory Sawicki- School of Mechanical Engineering, Georgia Institute of Technology
 

Dr. Yue Chen- School of Biomedical Engineering, Georgia Institute of Technology
 

Abstract 

Robotic grasping is a significant area of study, and reduction in its mechanical and control complexity is of great interest for use in wearable devices, teleoperated devices, as well as fully autonomous devices. This work aims to demonstrate efficient and reliable methods for mechanical complexity reduction using fully characterized soft robotics and advanced modeling techniques, and to combine that reduction with a methodology for reducing the dimensionality of the control problem using techniques based on synergy control and a novel method for generating an optimal synergy matrix for an arbitrary gripper.  

The major goals of this work are to: 

1. Study muscle-like soft actuators and characterize properties to provide a foundation for using compliant muscle-like actuators.  

2. Develop a soft secondary mechanism to enable synergy control in underactuated gripper by changing the joint interaction properties, then fully characterizing and modeling this system to simulate it and create a synergy control scheme.  

3. Optimize synergy matrix without mapping, and study the interactions between it, gripper design parameters, and actuation type, using soft actuators from the first goal and the soft mechanisms and the modeling method from the second goal, along with a modeled fully-actuated gripper.