Cantrell, Rehj
Novel Mechanisms for Natural Human-Robot Interactions in the DIARC Architecture
Scheutz, Matthias (Tufts University) | Briggs, Gordon (Tufts University) | Cantrell, Rehj (Indiana University) | Krause, Evan (Tufts University) | Williams, Thomas (Tufts University) | Veale, Richard (Indiana University)
Natural human-like human-robot interactions require many functional capabilities from a robot that have to be reflected in architectural components in the robotic control architecture. In particular, various mechanisms for producing social behaviors , goal-oriented cognition , and robust intelligence are required. In this paper, we present an overview of the most recent version of our DIARC architecture and show how several novel algorithms attempt to address these three areas, leading to more natural interactions with humans, while also extending the overall capability of the integrated system.
Toward Humanlike Task-Based Dialogue Processing for Human Robot Interaction
Scheutz, Matthias (Tufts University) | Cantrell, Rehj (Indiana University) | Schermerhorn, Paul (Indiana University)
Many human social exchanges and coordinated activities critically involve dialogue interactions. Hence, we need to develop natural humanlike dialogue processing mechanisms for future robots if they are to interact with humans in natural ways. In this article we discuss the challenges of designing such flexible dialogue-based robotic systems. We report results from data we collected in human interaction experiments in the context of a search task and show how we can use these results to build more flexible robotic architectures that are starting to address the challenges of task-based humanlike natural language dialogues on robots.
Toward Humanlike Task-Based Dialogue Processing for Human Robot Interaction
Scheutz, Matthias (Tufts University) | Cantrell, Rehj (Indiana University) | Schermerhorn, Paul (Indiana University)
Many human social exchanges and coordinated activities critically involve dialogue interactions. Hence, we need to develop natural humanlike dialogue processing mechanisms for future robots if they are to interact with humans in natural ways. In this article we discuss the challenges of designing such flexible dialogue-based robotic systems. We report results from data we collected in human interaction experiments in the context of a search task and show how we can use these results to build more flexible robotic architectures that are starting to address the challenges of task-based humanlike natural language dialogues on robots.