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Conference

Field and Service Robotics 

About: Field and Service Robotics is an academic conference. The conference publishes majorly in the area(s): Mobile robot & Robot. Over the lifetime, 574 publication(s) have been published by the conference receiving 9494 citation(s).
Papers
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Book ChapterDOI
15 May 2017
Abstract: Developing and testing algorithms for autonomous vehicles in real world is an expensive and time consuming process Also, in order to utilize recent advances in machine intelligence and deep learning we need to collect a large amount of annotated training data in a variety of conditions and environments We present a new simulator built on Unreal Engine that offers physically and visually realistic simulations for both of these goals Our simulator includes a physics engine that can operate at a high frequency for real-time hardware-in-the-loop (HITL) simulations with support for popular protocols (eg MavLink) The simulator is designed from the ground up to be extensible to accommodate new types of vehicles, hardware platforms and software protocols In addition, the modular design enables various components to be easily usable independently in other projects We demonstrate the simulator by first implementing a quadrotor as an autonomous vehicle and then experimentally comparing the software components with real-world flights

694 citations


Book ChapterDOI
24 Jun 2015
TL;DR: How the SPENCER project advances the fields of detection and tracking of individuals and groups, recognition of human social relations and activities, normative human behavior learning, socially-aware task and motion planning, learning socially annotated maps, and conducting empirical experiments to assess socio-psychological effects of normative robot behaviors is described.
Abstract: We present an ample description of a socially compliant mobile robotic platform, which is developed in the EU-funded project SPENCER. The purpose of this robot is to assist, inform and guide passengers in large and busy airports. One particular aim is to bring travellers of connecting flights conveniently and efficiently from their arrival gate to the passport control. The uniqueness of the project stems from the strong demand of service robots for this application with a large potential impact for the aviation industry on one side, and on the other side from the scientific advancements in social robotics, brought forward and achieved in SPENCER. The main contributions of SPENCER are novel methods to perceive, learn, and model human social behavior and to use this knowledge to plan appropriate actions in real-time for mobile platforms. In this paper, we describe how the project advances the fields of detection and tracking of individuals and groups, recognition of human social relations and activities, normative human behavior learning, socially-aware task and motion planning, learning socially annotated maps, and conducting empirical experiments to assess socio-psychological effects of normative robot behaviors.

192 citations


Proceedings Article
01 Jan 1998
Abstract: Recent studies of insect visual behaviour and navigation reveal a number of elegant strategies that can be profitably applied to the design of autonomous robots. The “peering” behaviour of grasshoppers, for example, has inspired the design of new rangefinding systems. The “centring” response of bees flying through a tunnel has led to simple methods for navigating through corridors. These and other visually-mediated insect behaviours are described along with a number of applications to robot navigation.

191 citations


Book ChapterDOI
01 Jan 2003
TL;DR: A network of distributed mobile sensor systems as a solution to the emergency response problem and how such networks can assist human users to find an exit is developed.
Abstract: We develop a network of distributed mobile sensor systems as a solution to the emergency response problem. The mobile sensors are inside a building and they form a connected ad-hoc network. We discuss cooperative localization algorithms for these nodes. The sensors collect temperature data and run a distributed algorithm to assemble a temperature gradient. The mobile nodes are controlled to navigate using this temperature gradient. We also discuss how such networks can assist human users to find an exit. We have conducted an experiment to at a facility used to train firefighters to understand the environment and to test component technology. Results from experiments at this facility as well as simulations are presented here.

189 citations


Proceedings Article
01 Jan 2003
TL;DR: A Bayesian approach to the problem of searching for a single lost target by a single autonomous sensor platform, implemented for an airborne vehicle looking for both a stationary and a drifting target at sea.
Abstract: This paper presents a Bayesian approach to the problem of searching for a single lost target by a single autonomous sensor platform. The target may be static or mobile but not evading. Two candidate utility functions for the control solution are highlighted, namely the Mean Time to Detection, and the Cumulative Probability of Detection. The framework is implemented for an airborne vehicle looking for both a stationary and a drifting target at sea. Simulation results for different control solutions are investigated and compared to demonstrate the effectiveness of the method.

177 citations


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Performance
Metrics
No. of papers from the Conference in previous years
YearPapers
20214
20192
201860
20172
201656
201555