<html><head><meta http-equiv="Content-Type" content="text/html charset=utf-8"></head><body style="word-wrap: break-word; -webkit-nbsp-mode: space; -webkit-line-break: after-white-space;" class=""><p class="MsoNormal">Apologies for cross posting!</p><p class="MsoSubtitle" style="margin-bottom: 0.0001pt;"><b class=""><span class="" style="font-family: Cambria; letter-spacing: 0pt;">IEEE RAS International Conference on Humanoid Robots 2017 workshop on Creating Meaning With Robot Assistants: The Gap Left by Smart Devices<o:p class=""></o:p></span></b></p><p class="MsoNormal"><a href="https://sites.google.com/site/humanoinds2017workshop/home" class="">https://sites.google.com/site/humanoinds2017workshop/home</a></p><p class="MsoNormal">November 15, 2017<o:p class=""></o:p></p><p class="MsoNormal">Birmingham, UK</p><h1 class="" style="margin-top: 0in;"><span class="" style="line-height: 27.600000381469727px;"><span class="" style="font-size: 12px;">Objectives:</span></span></h1><p class="MsoNormal" style="text-align: justify;">An Intelligent Personal Assistant (IPA) such as a smartphone or that tiny smart device that sits on the table reacting to voice command is a basic form of a shared activity between human and an agent. The very warm reception of IPAs into the household is a clear manifestation of human’s interest in collaborating with a digital companion on a shared activity, even with such limited functionality.</p><p class="MsoNormal" style="text-align: justify;">The phenomenal success of IPAs shows potential for robot assistants. After all, people have long desired for robot assistants even when the technology was not ready yet. Robots, with their ability to interact with the physical world, have more capabilities than IPAs, thus they can push further the value of a shared activity. However, when it comes to robot assistants, human expectation sets the bar high. Designing them merely as extension to IPAs requires a well-considered adaptation of their physical appearance, e.g., human-like form factor and their cognitive capabilities not to raise expectations from the user which cannot be met. On the other hand, treating the role of the robot assistant like any specialized service robot with interaction-limited personality (e.g. Roomba) puts it in the same category as our appliances. Robot assistants copying the mobility-limited focus of IPAs would be a waste of the emotional potential provided by their agility. Of equal importance as the objective completion of shared activity, robot assistants should enhance meaningful cooperation. For humans to embrace robot assistants, in a household crowded by smart devices and service robots, robot assistants need to at least meet human expectations.</p><p class="MsoNormal" style="text-align: justify;">This multidisciplinary workshop will gather researchers, engineers and designers on the crossroad of finding a niche for robot assistants to be relevant. In particular, we want to discuss the design of robot assistants that deliver more added values or features in its assistive task, cultivating trust and comfort that ultimately increases human appreciation of the robot assistant as both engage in a shared activity. Paper contributions with either experimental or theoretical focus are welcome. Moreover, preliminary results and experiments or applications with compelling use cases in the realm of robot assistants are encouraged.</p><p class="MsoNormal" style="text-align: justify;">Papers addressing topics related to the workshop should be submitted electronically with two-column format in the IEEE style via EasyChair: <a href="https://easychair.org/conferences/?conf=camera2017" class=""><span class="" style="color: windowtext; text-decoration: none;">https://easychair.org/conferences/?conf=camera2017</span></a>.</p><p class="MsoNormal" style="text-align: justify;"><o:p class=""></o:p></p><p class="MsoNormal" style="text-align: justify;">Paper length should be up to 6 pages. The templates can be found on the Humanoids conference via the link: <a href="http://humanoids2017.loria.fr/submissions/paper-submission/" class=""><span class="" style="color: windowtext; text-decoration: none;">http://humanoids2017.loria.fr/submissions/paper-submission/</span></a>. </p><div class="" style="text-align: justify;"> <br class="webkit-block-placeholder"></div><p class="MsoNormal" style="text-align: justify;"><b class="">Important dates:<o:p class=""></o:p></b></p><p class="MsoNormal" style="text-align: justify;">Submission deadline: October 31st, 2017<o:p class=""></o:p></p><p class="MsoNormal" style="text-align: justify;">Notification of Acceptance: November 7th, 2017<o:p class=""></o:p></p><h3 class=""><span class="" style="line-height: 15.724800109863281px;"><span class="" style="font-size: 12px;">Topics of interest:</span><font face="Cambria" class="" style="font-size: 12pt;"><o:p class=""></o:p></font></span></h3><p class="MsoListParagraphCxSpFirst" style="text-indent: -0.25in;"><span class="" style="font-size: 12pt; line-height: 18.399999618530273px; font-family: Symbol;"> <span class="" style="font-size: 7pt; line-height: normal; font-family: 'Times New Roman';"> </span></span><span class="" style="line-height: 13.800000190734863px;">·</span> <span class="" style="text-indent: -0.25in; font-size: 12pt; line-height: 18.399999618530273px; font-family: Symbol;"><span class="" style="font-size: 7pt; line-height: normal; font-family: 'Times New Roman';"> </span></span><span class="" style="text-indent: -0.25in; line-height: 13.800000190734863px;">Multimodal and Spoken Language Understanding</span></p><p class="MsoListParagraphCxSpMiddle" style="text-indent: -0.25in;"><span class="" style="line-height: 13.800000190734863px;"> ·<span class="" style="line-height: normal;"> </span></span><span class="" style="line-height: 13.800000190734863px;">Social Cognitive Systems<o:p class=""></o:p></span></p><p class="MsoListParagraphCxSpMiddle" style="text-indent: -0.25in;"><span class="" style="line-height: 13.800000190734863px;"> ·<span class="" style="line-height: normal;"> </span></span><span class="" style="line-height: 13.800000190734863px;">Socially Intelligent Robots<o:p class=""></o:p></span></p><p class="MsoListParagraphCxSpMiddle" style="text-indent: -0.25in;"><span class="" style="line-height: 13.800000190734863px;"> ·<span class="" style="line-height: normal;"> </span></span><span class="" style="line-height: 13.800000190734863px;">Collaborative Robotics<o:p class=""></o:p></span></p><p class="MsoListParagraphCxSpMiddle" style="text-indent: -0.25in;"><span class="" style="line-height: 13.800000190734863px;"> ·<span class="" style="line-height: normal;"> </span></span><span class="" style="line-height: 13.800000190734863px;">Active Perception (Acoustics, Vision, etc.)<o:p class=""></o:p></span></p><p class="MsoListParagraphCxSpMiddle" style="text-indent: -0.25in;"><span class="" style="line-height: 13.800000190734863px;"> ·<span class="" style="line-height: normal;"> </span></span><span class="" style="line-height: 13.800000190734863px;">Human Robot Interaction<o:p class=""></o:p></span></p><p class="MsoListParagraphCxSpMiddle" style="text-indent: -0.25in;"><span class="" style="line-height: 13.800000190734863px;"> ·<span class="" style="line-height: normal;"> </span></span><span class="" style="line-height: 13.800000190734863px;">Human Behavior Modeling<o:p class=""></o:p></span></p><p class="MsoListParagraphCxSpMiddle" style="text-indent: -0.25in;"><span class="" style="line-height: 13.800000190734863px;"> ·<span class="" style="line-height: normal;"> </span></span><span class="" style="line-height: 13.800000190734863px;">Affective Computing<o:p class=""></o:p></span></p><p class="MsoListParagraphCxSpMiddle" style="text-indent: -0.25in;"><span class="" style="line-height: 13.800000190734863px;"> ·<span class="" style="line-height: normal;"> </span></span><span class="" style="line-height: 13.800000190734863px;">Human Intention Recognition<o:p class=""></o:p></span></p><p class="MsoListParagraphCxSpMiddle" style="text-indent: -0.25in;"><span class="" style="line-height: 13.800000190734863px;"> ·<span class="" style="line-height: normal;"> </span></span><span class="" style="line-height: 13.800000190734863px;">Interactive Machine learning <o:p class=""></o:p></span></p><p class="MsoListParagraphCxSpMiddle" style="text-indent: -0.25in;"><span class="" style="line-height: 13.800000190734863px;"> ·<span class="" style="line-height: normal;"> </span></span><span class="" style="line-height: 13.800000190734863px;">Human-centered reinforcement learning<o:p class=""></o:p></span></p><p class="MsoListParagraphCxSpMiddle" style="text-indent: -0.25in;"><span class="" style="line-height: 13.800000190734863px;"> ·<span class="" style="line-height: normal;"> </span></span><span class="" style="line-height: 13.800000190734863px;">Learning from demonstration<o:p class=""></o:p></span></p><p class="MsoListParagraphCxSpMiddle" style="margin-bottom: 0.0001pt; text-align: justify; text-indent: -0.25in;"> · Imitation learning<o:p class=""></o:p></p><p class="MsoListParagraphCxSpMiddle" style="margin-bottom: 0.0001pt; text-align: justify; text-indent: -0.25in;"> · Active learning in robotics<o:p class=""></o:p></p><p class="MsoListParagraphCxSpMiddle" style="margin-bottom: 0.0001pt; text-align: justify; text-indent: -0.25in;"> · Mutual shaping of robots and human<o:p class=""></o:p></p><p class="MsoListParagraphCxSpMiddle" style="margin-bottom: 0.0001pt; text-align: justify; text-indent: -0.25in;"> · Performance metrics and benchmarking<o:p class=""></o:p></p><p class="MsoListParagraphCxSpLast" style="text-indent: -0.25in;"><span class="" style="line-height: 13.800000190734863px;"> ·<span class="" style="line-height: normal;"> </span></span><span class="" style="line-height: 13.800000190734863px;">Applications and challenges in human-centered robot assistant systems<font size="3" class=""><o:p class=""></o:p></font></span></p><h3 class=""><span class="" style="line-height: 15.724800109863281px;"><span class="" style="font-size: 12px;">Invited Speakers: </span><font face="Cambria" class="" style="font-size: 12pt;"><o:p class=""></o:p></font></span></h3><p class="MsoListParagraphCxSpFirst" style="text-indent: -0.25in;"><span class="" style="line-height: 13.800000190734863px;"> ·<span class="" style="line-height: normal;"> </span></span><span class="" style="line-height: 13.800000190734863px;">Maja Pantic, Imperial College London, UK<o:p class=""></o:p></span></p><p class="MsoListParagraphCxSpMiddle" style="text-indent: -0.25in;"><span class="" style="line-height: 13.800000190734863px;"> ·<span class="" style="line-height: normal;"> </span></span><span class="" style="line-height: 13.800000190734863px;">Paulo Alvito, IDMind Living Robotcs, Portugal<o:p class=""></o:p></span></p><p class="MsoListParagraphCxSpLast" style="text-indent: -0.25in;"><span class="" style="line-height: 13.800000190734863px;"> ·<span class="" style="line-height: normal;"> </span></span><span class="" style="line-height: 13.800000190734863px;">Nick Hawes, University of Birmingham, UK</span></p><div class=""><h1 class="" style="margin-top: 0in;"><span class="" style="line-height: 27.600000381469727px;"><span class="" style="font-size: 12px;">Organizing Committee:</span><font face="Cambria" class="" style="font-size: 12pt;"><o:p class=""></o:p></font></span></h1><p class="MsoNormal">Randy Gomez, Honda Research Institute Japan</p><p class="MsoNormal">Guangliang Li, Ocean University of China</p><p class="MsoNormal">Keisuke Nakamura, Honda Research Institute Japan</p><p class="MsoNormal"><o:p class=""></o:p></p><p class="MsoNormal">Manuel Muehlig, Honda Research Institute Europe<o:p class=""></o:p></p><p class="MsoNormal">Martin Heckmann, Honda Research Institute Europe<o:p class=""></o:p></p>Samer Moubayed, Furhat Robotics & KTH, Sweden </div></body></html>