Title: Creating Mobile Manipulation Capabilities: On Dynamic Modeling and Control of Euler-Lagrange passive nonholonomic systems

Date: Tuesday, June 27, 2023

Time: 12:00PM EST

Location: (Virtual) Microsoft Teams Meeting

Sergio Aguilera

Robotics Ph.D. Candidate

School of Electrical and Computer Engineering

Georgia Institute of Technology

Committee:

Dr. Seth Hutchinson (Advisor) – School of Interactive Computing, Georgia Institute of Technology

Dr. Ye Zhao – School of Mechanical Engineering, Georgia Institute of Technology

Dr. Jonathan Rogers – School of Aerospace Engineering, Georgia Institute of Technology

Dr. Charlie Kemp – Department of Biomedical Engineering, Georgia Institute of Technology

Dr. Frank Dellaert – School of Interactive Computing, Georgia Institute of Technology

Abstract:

Mobile manipulators (MMs) have been introduced into various fields, from agriculture and warehouse automation to hospitals and personal assistants. Commonly used for fetching tasks, the range of capabilities that MMs currently have are limited to traversing the environment and interacting with light objects. We want to enable MMs to interact and control heavy objects around the environment to expand their capabilities. Considering that large and heavy objects have nontrivial dynamics and momentum, we need to understand how they behave and react to the interactions with the MM. From pushing wagons and trolleys in a warehouse, wheeled beds and wheelchairs in a hospital, and shopping carts, luggage, and strollers as personal assistant robots, there is a wide range of tasks where we want MMs to push objects with changing inertial parameters.

This thesis proposes to develop a framework for interacting with and controlling wheeled objects with a wide range of inertial parameters. We propose to study both the MM and object as two individual systems interacting with each other. For the object, we propose a general dynamic model for various cart-like systems with unknown parameters, and the actuation is an external force applied by the MM. First, we present an adaptive control approach to tackle the system identification of the object and control for trajectory tracking. Then, we propose a hybrid control scheme for the MM manipulator to move the base along with the object while applying the required force at a given contact point on the object.