Rui Lou PhD Dissertation Defense

Announcing:
PhD Dissertation Defense

Name:
Rui Luo

Title:
Shared Assistance Methods for Human-in-the-loop Robot Systems

Date:
7/25/2024

Time:
2:00:00 PM

Location:
EXP 701A.

Committee Members:
Prof. Taskin Padir (Advisor)
Prof. John Peter Whitney
Prof. Yanzhi Wang
Dr. Mark Zolotas

Abstract:
Fully autonomous robot systems, though highly desired, face substantial theoretical and practical challenges when being deployed into a dynamic environment where human co-exists. To tackle this challenge, this thesis investigates the concept of human-in-the-loop (HITL) systems, which incorporate human input to enhance robot functionality. HITL systems offer a pragmatic alternative, combining human versatility with robotic precision.

This research aims to address critical questions in one specific HITL system which  prioritizes the dominant role of human within the system, positioning the robot primarily in an assistive capacity that adheres to human commands to facilitate the achievement of a shared goal. It explores two primary paradigms of shared assistance methods—Shared Control (SC) and Shared Autonomy (SA)—and discuss the system designs as well as specific algorithms to implement the three critical components in a HITL systems: human intention estimation, modulation of human inputs and robot autonomy, and the human-robot communication channel.

Due to the variety of use cases and their specific challenges, four distinct HITL systems are developed and analyzed to exemplify how shared assistance methods could be incorporated to assist human operators: an assistive wheelchair for indoor navigation, a human-centered robot system design for industrial tasks, a mobile bi-manual robot for tele-manipulation, and a VR-based customizable shared control system for fine teleopeartion.  Although each system represents a comprehensive robotic solution, the research contributions for each work vary.

In the assistive wheelchair navigation system, the focus was on human intent estimation via low-throughput interface utilizing a recursive Bayesian filter, with significant efforts dedicated to developing a real-time user interface serving as the communication channel. In the human-robot collaboration system for industrial setting, the emphasis was on human state estimation through camera-based posture tracking and exploring the interplay between robot behavior and human ergonomics. For the two teleoperation systems, the primary focus was on the real-time modulation of human inputs and robot autonomy to aid in achieving dexterous manipulation tasks. A novel VR-based user interface was developed to enable users to customize the level of robotic autonomous assistance. Each system was validated through a pilot study involving 10-20 human subjects, accompanied by extensive data analysis to provide insights into designing HITL systems for various applications.

In conclusion, this thesis contributes to a deeper understanding of HITL systems, highlighting their potential to enhance human productivity, ergonomics, and quality of life in various applications through concrete examples. The integration of human intent estimation and real-time shared control methods into robotic systems demonstrates the feasibility and benefits of HITL approaches. Our extensive experimental analysis underscores the critical role of human feedback in designing practical HITL systems that can be deployed in real-world scenarios.