A long-standing goal is the realization of robots that can easily join and effectively work alongside people within our homes, manufacturing centers, and healthcare facilities. In order to achieve this vision, we need to develop robots that people are able to command, control, and communicate with in ways that are intuitive, expressive, and flexible. Recognizing this need, much attention has been paid of late to natural language speech as an effective medium for humans and robots to communicate. A primary challenge to language understanding is to relate free-form language to a robot's world model --- its understanding of our unstructured environments and the ways in which it can act in these environments. This problem dates back to the earliest days of artificial intelligence and has witnessed renewed interest with advances in machine learning and probabilistic inference.
We welcome contributions from a broad range of areas related to the development of models and algorithms that enable natural communication between humans and robots. We particularly encourage recent and ongoing research at the intersection of robotics and fields that include natural language processing, machine learning, and computer vision.
The workshop is intended for a broad audience working on problems related to representations of environments across a variety of domains. We anticipate participation by researchers whose interests draw from robotics, machine learning, perception, mapping, motion planning, and human-robot interaction, among others.
Topics of interest include, but are not limited to:
We invite participants to submit extended abstracts or full papers that describe recent or ongoing research. We encourage authors to accompany their submissions with a video that describes or demonstrates their work. Authors of accepted abstracts/papers will have the opportunity to disseminate their work through an oral presentation and/or interactive poster session.
Papers (max eight pages, excluding references) and abstracts (max two pages, excluding references) should be in PDF format and adhere to the RSS paper format. Note that reviews will not be double blind and submissions should include the author names and affiliations.
Papers, abstracts, and supplementary materials can be submitted by logging in to the conference management website located at https://cmt3.research.microsoft.com/MRHRC2018.
University of North Carolina, Chapel Hill
Georgia Institute of Technology
University of Washington
Michigan State University
University of California, Berkeley
University of Maryland, Baltimore County
University of California, Davis
|Abstract/Paper Submission||May 31, 2018|
|Abstract/Paper Notification||June 8, 2018|
|Camera-ready Submission||June 25, 2018|
|Workshop Dates||June 29-30, 2018|
Location: The workshop will be held over two days during RSS 2018 at Carnegie Mellon University in GHC 6115.
The Workshop on Models and Representations for Natual Human-Robot Communication is a two day workshop composed of invited talks, contributed papers, and poster presentations. The detailed program is listed below.
(This program is subject to change!
Last updated: June 29.)
If you'd like to suggest questions for the discussion forum, please use this Google Form (link)
|Friday, June 29|
|09:15am–09:45am||A-STAR: Agents that See, Talk, Act, and Reason (Invited Talk)|
|Dhruv Batra (Georgia Tech/FAIR)|
|09:45am–10:00am||Towards Learning User Preferences for Remote Robot Navigation|
|Cory Hayes (ARL), Matthew Marge (ARL), and Ethan Stump (ARL)|
|10:30am–10:45am||Establishing Common Ground for Learning Robots|
|Preeti Ramaraj (UMich) and John E Laird (UMich)|
|10:45am–11:00am||Simultaneous Intention Estimation and Knowledge Augmentation via Human-Robot Dialog|
|Sujay Bajracharya (Cleveland U), Saeid Amiri (Cleveland U), Jesse Thomason (UW), and Shiqi Zhang (SUNY Binghampton)|
|11:00am–11:30am||Communication as Belief Influence (Invited Talk)|
|Anca Dragan (UC Berkeley)|
|11:30am–11:45am||Specifying and Achieving Goals in Open Uncertain Robot-Manipulation Domains|
|Leslie Kaelbling (MIT), Alex LaGrassa (MIT), and Tomas Lozano-Perez (MIT)|
|11:45am–12:00pm||Optimal Semantic Distance for Negative Example Selection in Grounded Language Acquisition|
|Nisha Pillai (UMBC), Frank Ferraro (UMBC), and Cynthia Matuszek (UMBC)|
|03:00pm–03:30pm||Poster Session (cont.)|
|03:30pm–04:00pm||Communicative Actions in Human-Robot Teams (Invited Talk)|
|Ross Knepper (Cornell)|
|04:00pm–04:30pm||Simple Models and Representations for Effective (but Perhaps Unnatural) Human-Robot Communication (Invited Talk)|
|Maya Cakmak (UW)|
|04:30pm–05:30pm||Discussion (submit questions here)|
|Saturday, June 30|
|09:15am–09:45am||Invited Talk - Joyce Chai|
|09:45am–10:00am||Towards Givenness and Relevance-Theoretic Open World Reference Resolution|
|Thomas Williams (Mines), Evan Krause (Tufts), Bradley Oosterveld (Tufts), and Matthias Scheutz (Tufts)|
|10:30am–10:45am||Jointly Improving Parsing and Perception for Natural Language Commands through Human-Robot Dialog|
|Jesse Thomason (UW), Aishwarya Padmakumar (UTA), Jivko Sinapov (Tufts), Nick Walker (UW), Yuqian Jiang (UTA), Harel Yedidsion (UTA), Justin Hart (UTA), Peter Stone (UTA), and Raymond Mooney (UTA)|
|10:45am–11:00am||Designing Questioning Strategies for an Active Learning Agent employing Diverse Query Types|
|Kalesha Bullard (GT), Sonia Chernova (GT), and Andrea Thomaz (UTA)|
|11:00am–11:30am||Invited Talk - Cynthia Matuszek|
|11:30am–11:45am||A Formal Model for Human Robot Collaboration using Hybrid Conditional Planning|
|Momina Rizwan (Sabanci U), Volkan Patoglu (Sabanci U), and Esra Erdem (Sabanci U)|
|11:45am–12:00pm||Learning Group Communication from Demonstration|
|Navyata Sanghvi (CMU), Ryo Yonetani (U Tokyo), and Kris Kitani (CMU)|
|03:00pm–03:30pm||Poster Session (cont.)|
|03:30pm–04:00pm||Spatially-Grounded, Personable, and Sensible Human-Robot Dialog (Invited Talk)|
|Invited Talk - Mohit Bansal|
|04:00pm–04:30pm||Grounding Reinforcement Learning with Real-world Dialog Tasks (Invited Talk)|
|Zhou Yu (UC Davis)|
|04:30pm–05:30pm||Discussion/Closing (submit questions here)|