Logo image
From Autonomy to Cooperative Traded Control of Humanoid Manipulation Tasks with Unreliable Communication
Journal article   Peer reviewed

From Autonomy to Cooperative Traded Control of Humanoid Manipulation Tasks with Unreliable Communication

Calder Phillips-Grafflin, Halit Bener Suay, Jim Mainprice, Nicholas Alunni, Daniel Lofaro, Dmitry Berenson, Sonia Chernova, Robert W. Lindeman and Paul Oh
Journal of intelligent & robotic systems, v 82(3-4), pp 341-361
01 Jun 2016

Abstract

Computer Science Computer Science, Artificial Intelligence Robotics Science & Technology Technology
In this paper, we present our system design, operational procedure, testing process, field results, and lessons learned for the valve-turning task of the DARPA Robotics Challenge (DRC). We present a software framework for cooperative traded control that enables a team of operators to control a remote humanoid robot over an unreliable communication link. Our system, composed of software modules running on-board the robot and on a remote workstation, allows the operators to specify the manipulation task in a straightforward manner. In addition, we have defined an operational procedure for the operators to manage the teleoperation task, designed to improve situation awareness and expedite task completion. Our testing process, consisting of hands-on intensive testing, remote testing, and remote practice runs , demonstrates that our framework is able to perform reliably and is resilient to unreliable network conditions. We analyze our approach, field tests, and experience at the DRC Trials and discuss lessons learned which may be useful for others when designing similar systems.

Metrics

8 Record Views
14 citations in Scopus

Details

UN Sustainable Development Goals (SDGs)

This publication has contributed to the advancement of the following goals:

#3 Good Health and Well-Being

InCites Highlights

Data related to this publication, from InCites Benchmarking & Analytics tool:

Collaboration types
Domestic collaboration
Web of Science research areas
Computer Science, Artificial Intelligence
Robotics
Logo image