HRI 2017 has seen the largest participation of any HRI conference to date and an exciting programme has been enjoyed by all. The organisation and steering committees want to thank the community for their continued engagement with HRI and the great time that was had in Vienna. And now, without further ado, this year’s AWARDS:

1 BEST VIDEO AWARD

As, due to technical problems during the award ceremony, this video has not been shown to all participants yet, the list of awards shall feature it first.

Robot’s Delight – A Lyrical Exposition on Learning by Imitation from Human-human Interaction (Page 408)

Dylan F. Glas (ATR)
Malcolm Doering (ATR)
Phoebe Liu (ATR)
Takayuki Kanda (ATR)
Hiroshi Ishiguro (Osaka University)

2 Best regular Paper Awards

2.1. BEST PAPER AWARD DESIGN

Cellulo: Versatile Handheld Robots for Education (Page 119)

Ayberk Özgür (École Polytechnique Fédérale de Lausanne)
Séverin Lemaignan (EPFL & Plymouth University)
Wafa Johal (École Polytechnique Fédérale de Lausanne)
Maria Beltran (École Polytechnique Fédérale de Lausanne)
Manon Briod (École Polytechnique Fédérale de Lausanne)
Léa Pereyre (École Polytechnique Fédérale de Lausanne)
Francesco Mondada (École Polytechnique Fédérale de Lausanne)
Pierre Dillenbourg (École Polytechnique Fédérale de Lausanne)

2.2. BEST PAPER AWARD HUMAN-ROBOT INTERACTION USER STUDIES

Two papers were awarded this year in this category.

Why Do They Refuse to Use My Robot?: Reasons for Non-Use Derived from a Long-Term Home Study (Page 224)

Maartje de Graaf (Brown University)
Somaya Ben Allouch (Saxion University of Applied Sciences)
Jan van Dijk (University of Twente)

Growing Growth Mindset with a Social Robot Peer (Page 137)

Hae Won Park (Massachusetts Institute of Technology)
Rinat Rosenberg-Kima (Tel Aviv University)
Maor Rosenberg (Tel Aviv University)
Goren Gordon (Tel Aviv University)
Cynthia Breazeal (Massachusetts Institute of Technology)

2.3. BEST PAPER AWARD TECHNICAL ADVANCES IN HUMAN-ROBOT INTERACTION

Creating Prosodic Synchrony for a Robot Co-player in a Speech-controlled Game for Children (Page 91)

Najmeh Sadoughi (University of Texas at Dallas & Disney Research Pittsburgh)
André Pereira (Disney Research Pittsburgh)
Rishub Jain (Disney Research Pittsburgh & Carnegie Mellon University)
Iolanda Leite (Disney Research Pittsburgh)
Jill Fain Lehman (Disney Research Pittsburgh)

2.4. BEST PAPER AWARD THEORY AND METHODS IN HUMAN-ROBOT INTERACTION

The Robotic Social Attributes Scale (RoSAS): Development and Validation (Page 254)

Colleen M. Carpinella (Disney Research)
Alisa B. Wyman (Disney Research)
Michael A. Perez (Disney Research)
Steven J. Stroessner (Disney Research)

3 Student Design Competition

3.1. 1ST PRIZE STUDENT DESIGN COMPETITION

Raven: A Street Robot to Address Homelessness (Page 397)

Haodan Tan (Indiana University)
Fuchang Yang (Indiana University)
Nava Teja Tummalapalli (Indiana University)
Chetan Bhatia (Indiana University)
Kaustubh Barde (Indiana University)

3.2. 2ND PRIZE STUDENT DESIGN COMPETITION

The Interactive Drawing Book (Page 395)

Ji Young Min (Ewha Womans University)
Gyeong Sun Kim (Ewha Womans University)

3.3. DELEGATES’ CHOICE STUDENT DESIGN COMPETITION

Snoozle – A Robotic Pillow that Helps You Go to Sleep: HRI 2017 Student Design Competition (Page 399)

Jered Vroon (University of Twente)
Cristina Zaga (University of Twente)
Daniel Davison (University of Twente)
Jan Kolkmeier (University of Twente)
Jeroen Linssen (University of Twente)

4 Service Awards

4.1. STUDENT COMMUNITY SERVICE AWARD

PRESENTED TO MARKUS BAJONES FOR EXCEPTIONAL SERVICE CONTRIBUTION TO HRI 2017

4.2. COMMUNITY SERVICE AWARD

PRESENTED TO ASTRID WEISS FOR EXCEPTIONAL SERVICE CONTRIBUTION TO HRI 2017

5 BEST DEMONSTRATION AWARD

MiRo: An Animal-like Companion Robot with a Biomimetic Brain-based Control System (Page 50)

Tony J. Prescott (University of Sheffield)
Ben Mitchinson (Consequential Robotics)
Sebastian Conran (Consequential Robotics)

6 BEST LATE BREAKING REPORT AWARD

Playing the Mirror Game with a Robot: Who Takes the Lead, and What Movements are Most Liked? (Page 159)

Shir Kashi (Ben Gurion University)
Amit Loutati (Ben Gurion University)
Shelly Levy-Tzedek (Ben Gurion University)

Telepresence

Did you have to stay at home and we miss you here in Vienna?

We are excited to announce that the HRI 2017 conference will have telepresence available for you to log in during the sessions and watch remotely.  For those of you who are unable to attend HRI this year in person, please express your interest in attending specific sessions via telepresence (provided by our supporters Revolve Robotics and Suitable Technologies) using this link. You will be asked to indicate which sessions you are interested in attending.  Prior to that session, you will receive an invitation email with a link to download the software and join the meeting for a specified timeframe.

Please keep in mind that the availability and quality of your telepresence experience is dependent on internet connection.  Therefore, please understand that at times connection may be slow or unavailable.  We will do our best to provide you with the best experience possible.  If you experience issues, please email jbeer@cse.sc.edu or mcakmak@cs.washington.edu.

1. If you registered for the conference on or before February 14 (registration numbers 995xxxxx or below), please go to the first venue “Zwölf Apostelkeller“, which is very close to the conference venue.
2. If you registered on or after February 15 (registration numbers 996xxxxx or higher), please go to the second venue “Gösser Bierklinik“.

May we ask you to please fill in the survey (please fill it multiple times, if you have purchased additional dinner tickets) to let us know whether or not you will actually attend dinner and to choose your food. Also please remember to have your badge with you.

Location

Justin Huang, Maya Cakmak

This paper introduces Code3, a system for user-friendly and rapid programming of mobile manipulator robots. The system enables general programmers with little to no robotics experience to program robots. Code3 consists of three integrated components: perception, manipulation, and high-level programming. The perception component helps users define a library of object and scene parts that the robot can later detect. The manipulation component lets users define actions for manipulating objects or scene parts through programming by demonstration techniques. Finally, the high-level programming component offers a drag-and-drop interface with which users can define logic and control flow to accomplish a task using their previously specified perception and manipulation capabilities. We present findings from a two-session user study with non-roboticist programmers (N=10) that demonstrate their ability to quickly learn Code3 and program a PR2 robot to do useful tasks. We also demonstrate how an expert can use the system to program complex tasks in orders of magnitude less time than it would take to code by hand in traditional robot programming frameworks such as ROS.

Kinesthetic Teaching of Re-usable Skills – Rapid and Simple Programming of a Safe Industrial Robot

Maj Stenmark, Elin Anna Topp, Mathias Haage

The development of robust non-expert programming systems is a long-standing challenge in robotics. Now emphasized with recently emerged collaborative industrial robots with a new feature set, such as built-in force controlled motion, vision, 7 degrees of freedom arms and dual arms. These features and the fact that the operator is being able to stay in close proximity during both programming and execution phases calls for a re-visit to shop-floor programming tools. This paper presents a tool prototype for iconic robot programming with a hybrid programming and execution mode. The tool was evaluated with 21 non-expert users with varying programming and robotics experience, including one nine year old. We also present a comparison of the programming times for an expert robot programmer using traditional tools versus this new method. The expert could program the same tasks in 1/5 of the time compared to traditional tools and the non-experts were able to program and debug a LEGO building task using the robot within 30 minutes.

Situated Tangible Robot Programming

Yasaman Sefidgar, Prerna Agarwal, Maya Cakmak

This paper introduces situated tangible robot programming in which a robot is programmed by placing specially designed tangible “blocks” in its workspace. These blocks are used for annotating objects, locations, or regions, and specifying actions and their ordering. The robot compiles a program by detecting blocks and objects in its workspace and grouping them into instructions by solving constraints. We present a proof-of-concept implementation using blocks with unique visual markers in a pick-and-place task domain. Three user studies evaluate the intuitiveness and learnability of situated tangible programming and iterate the block design. We characterize common challenges and gather feedback on how to further improve the design of blocks. Our studies demonstrate that people can interpret, generalize, and create many different situated tangible programs with minimal instruction or even with no instruction.

Not your cup of tea? How teaching a robot can increase perceived self-efficacy in HRI and technology acceptance

Astrid Rosenthal von der Pütten, Nikolai Bock, Katharina Brockmann

The goal of this work is to explore the influence of do-it-yourself customization of a robot on technologically experienced students and unexperienced elderly users’ perceived self-efficacy in HRI, uncertainty, and technology acceptance. We introduce the Self-Efficacy in HRI Scale and present two experimental studies. In study 1 (students, n=40) we found that actively teaching a robot objects relevant for a subsequent social interaction significantly increases perceived self-efficacy in HRI in comparison to reading a fact sheet about the robot’s capabilities. Moreover, interacting with the robot itself regardless of the previous treatment increased self-efficacy. In a second study with elderly users (n=60) we could replicate the positive effect of the interaction on self-efficacy, but not the effect of do-it-yourself customization by training the robot. We discuss limitations of the setting and implications for questionnaire design for elderly participant