The University of Southampton
University of Southampton Institutional Repository

Real-time opinion aggregation methods for crowd robotics

Real-time opinion aggregation methods for crowd robotics
Real-time opinion aggregation methods for crowd robotics
Unmanned Aerial Vehicles (UAVs) are increasingly becoming instrumental to many commercial applications, such as transportation and maintenance. However, these applications require flexibility, understanding of natural language, and comprehension of video streams that cannot currently be automated and instead require the intelligence of a skilled human pilot. While having one pilot individually supervising a UAV is not scalable, the machine intelligence, especially vision, required to operate a UAV is still inadequate. Hence, in this paper, we consider the use of crowd robotics to harness a real-time crowd to orientate a UAV in an unknown environment. In particular, we present two novel real-time crowd input aggregation methods. To evaluate these methods, we develop a new testbed for crowd robotics, called CrowdDrone, that allows us to evaluate crowd robotic systems in a variety of scenarios. Using this platform, we benchmark our real-time aggregation methods with crowds hired from Amazon Mechanical Turk and show that our techniques outperform the current state-of-the-art aggregation methods, enabling a robotic agent to travel faster across a fixed distance, and with more precision. Furthermore, our aggregation methods are shown to be significantly more effective in dynamic scenarios
841-849
Salisbury, Elliot
329cf646-21f4-477d-a143-32be37491cf7
Stein, Sebastian
cb2325e7-5e63-475e-8a69-9db2dfbdb00b
Ramchurn, Sarvapali
1d62ae2a-a498-444e-912d-a6082d3aaea3
Salisbury, Elliot
329cf646-21f4-477d-a143-32be37491cf7
Stein, Sebastian
cb2325e7-5e63-475e-8a69-9db2dfbdb00b
Ramchurn, Sarvapali
1d62ae2a-a498-444e-912d-a6082d3aaea3

Salisbury, Elliot, Stein, Sebastian and Ramchurn, Sarvapali (2015) Real-time opinion aggregation methods for crowd robotics. At 14th International Conference on Autonomous Agents and Multi-Agent Systems (AAMAS) 14th International Conference on Autonomous Agents and Multi-Agent Systems (AAMAS), Turkey. 04 - 08 May 2015. 8 pp, pp. 841-849.

Record type: Conference or Workshop Item (Paper)

Abstract

Unmanned Aerial Vehicles (UAVs) are increasingly becoming instrumental to many commercial applications, such as transportation and maintenance. However, these applications require flexibility, understanding of natural language, and comprehension of video streams that cannot currently be automated and instead require the intelligence of a skilled human pilot. While having one pilot individually supervising a UAV is not scalable, the machine intelligence, especially vision, required to operate a UAV is still inadequate. Hence, in this paper, we consider the use of crowd robotics to harness a real-time crowd to orientate a UAV in an unknown environment. In particular, we present two novel real-time crowd input aggregation methods. To evaluate these methods, we develop a new testbed for crowd robotics, called CrowdDrone, that allows us to evaluate crowd robotic systems in a variety of scenarios. Using this platform, we benchmark our real-time aggregation methods with crowds hired from Amazon Mechanical Turk and show that our techniques outperform the current state-of-the-art aggregation methods, enabling a robotic agent to travel faster across a fixed distance, and with more precision. Furthermore, our aggregation methods are shown to be significantly more effective in dynamic scenarios

PDF document.pdf - Other
Available under License Creative Commons Attribution.
Download (980kB)

More information

Accepted/In Press date: January 2015
Published date: May 2015
Venue - Dates: 14th International Conference on Autonomous Agents and Multi-Agent Systems (AAMAS), Turkey, 2015-05-04 - 2015-05-08
Organisations: Agents, Interactions & Complexity

Identifiers

Local EPrints ID: 375287
URI: https://eprints.soton.ac.uk/id/eprint/375287
PURE UUID: 44265690-6182-4850-a6d9-d1a2c6c9467a
ORCID for Sarvapali Ramchurn: ORCID iD orcid.org/0000-0001-9686-4302

Catalogue record

Date deposited: 20 Mar 2015 12:02
Last modified: 06 Jun 2018 12:42

Export record

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of https://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×