Cohen, Adam B. (Independent Consultant) | Chernova, Sonia (Worcester Polytechnic Institute) | Giordano, James (Georgetown University Medical Center) | Guerin, Frank (University of Aberdeen) | Hauser, Kris (Duke University) | Indurkhya, Bipin (AGH University of Science and Technology) | Leonetti, Matteo (University of Texas at Austin) | Medsker, Larry (Siena College) | Michalowski, Martin (Adventium Labs) | Sonntag, Daniel (German Research Center for Artificial Intelligence) | Stojanov, Georgi (American University of Paris) | Tecuci, Dan G. (IBM Watson, Austin) | Thomaz, Andrea (Georgia Institute of Technology) | Veale, Tony (University College Dublin) | Waltinger, Ulli (Siemens Corporate Technology)
The AAAI 2014 Fall Symposium Series was held Thursday through Saturday, November 13–15, at the Westin Arlington Gateway in Arlington, Virginia adjacent to Washington, DC. The titles of the seven symposia were Artificial Intelligence for Human-Robot Interaction, Energy Market Prediction, Expanding the Boundaries of Health Informatics Using AI, Knowledge, Skill, and Behavior Transfer in Autonomous Robots, Modeling Changing Perspectives: Reconceptualizing Sensorimotor Experiences, Natural Language Access to Big Data, and The Nature of Humans and Machines: A Multidisciplinary Discourse. The highlights of each symposium are presented in this report.
Chernova, Sonia (Worcester Polytechnic Institut) | Dodds, Zachary (Harvey Mudd College) | Stilman, Mike (Georgia Institute of Technology) | Touretzky, Dave (Carnegie Mellon University) | Thomaz, Andrea L. (Georgia Institute of Technology)
In this article we report on the exhibits and challenges shown at the AAAI 2011 Robotics Program in San Francisco. The event included a broad demonstration of innovative research at the intersection of robotics and artificial intelligence. Through these multi-year challenge events, our goal has been to focus the research community's energy toward common platforms and common problems to work toward the greater goal of embodied AI.
We present an innovative approach for large-scale data collection in human-robot interaction research through the use of online multi-player games. By casting a robotic task as a collaborative game, we gather thousands of examples of human-human interactions online, and then leverage this corpus of action and dialog data to create contextually relevant, social and task-oriented behaviors for human-robot interaction in the real world. We demonstrate our work in a collaborative search and retrieval task requiring dialog, action synchronization and action sequencing between the human and robot partners. A user study performed at the Boston Museum of Science shows that the autonomous robot exhibits many of the same patterns of behavior that were observed in the online dataset and survey results rate the robot similarly to human partners in several critical measures.
Anderson, Monica (University of Alabama) | Chernova, Sonia (Worcester Polytechnic Institute) | Dodds, Zachary (Harvey Mudd College) | Thomaz, Andrea L. (Georgia Institute of Technology) | Touretsky, David (Carnegie Mellon University)
The 19th robotics program at the annual AAAI conference was held in Atlanta, Georgia in July 2010. In this article we give a summary of three components of the exhibition: small scale manipulation challenge: robotic chess; the learning by demonstration challenge, and the education track. We also describe the participating teams, highlight the research questions they tackled and briefly describe the systems they demonstrated.
CMRoboBits is a course offered at Carnegie Mellon University that introduces students to all the concepts needed to create a complete intelligent robot. This course shows how an AIBO and its software resources make it possible for students to investigate and work with an unusually broad variety of AI topics within a single semester. While material presented in this article describes using AIBOs as the primary platform, the concepts presented in the course are not unique to the AIBO and can be applied on different kinds of robotic hardware.