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Social communication between people and social robots has been studied extensively and found to have various notable benefits, including the enhancement of human-robot team cohesion and the development of rapport and trust. However, the…
It is incredibly easy for a system designer to misspecify the objective for an autonomous system ("robot''), thus motivating the desire to have the robot learn the objective from human behavior instead. Recent work has suggested that people…
The state of the art in human computer conversation leaves something to be desired and, indeed, talking to a computer can be down-right annoying. This paper describes an approach to identifying ``opportunities for improvement'' in these…
Allowing humans to communicate through natural language with robots requires connections between words and percepts. The process of creating these connections is called symbol grounding and has been studied for nearly three decades.…
Robots applications in our daily life increase at an unprecedented pace. As robots will soon operate "out in the wild", we must identify the safety and security vulnerabilities they will face. Robotics researchers and manufacturers focus…
We consider a service robot that offers chocolate treats to people passing in its proximity: it has the capability of predicting in advance a person's intention to interact, and to actuate an "offering" gesture, subtly extending the tray of…
A single mobile service robot may generate hundreds of encounters with pedestrians, yet there is little published data on the factors influencing these incidental human-robot encounters. We report the results of a between-subjects…
When humans design cost or goal specifications for robots, they often produce specifications that are ambiguous, underspecified, or beyond planners' ability to solve. In these cases, corrections provide a valuable tool for human-in-the-loop…
Recent success of machine learning in many domains has been overwhelming, which often leads to false expectations regarding the capabilities of behavior learning in robotics. In this survey, we analyze the current state of machine learning…
Despite great advances in what robots can do, they still experience failures in human-robot collaborative tasks due to high randomness in unstructured human environments. Moreover, a human's unfamiliarity with a robot and its abilities can…
Concerns over the risks associated with advances in Artificial Intelligence have prompted calls for greater efforts toward robust and beneficial AI, including machine ethics. Recently, roboticists have responded by initiating the…
As social robots become more common, many have adopted cute aesthetics aiming to enhance user comfort and acceptance. However, the effect of this aesthetic choice on human feedback in reinforcement learning scenarios remains unclear.…
While thinking aloud has been reported to positively affect problem-solving, the effects of the presence of an embodied entity (e.g., a social robot) to whom words can be directed remain mostly unexplored. In this work, we investigated the…
Integrating generative AI such as Large Language Models into social robots has improved their ability to engage in natural, human-like communication. This study presents a method to examine their persuasive capabilities. We designed an…
When a robot learns from human examples, most approaches assume that the human partner provides examples of optimal behavior. However, there are applications in which the robot learns from non-expert humans. We argue that the robot should…
Personality has been identified as a vital factor in understanding the quality of human robot interactions. Despite this the research in this area remains fragmented and lacks a coherent framework. This makes it difficult to understand what…
It is intractable for assistive robots to have all functionalities pre-programmed prior to deployment. Rather, it is more realistic for robots to perform supplemental, on-site learning about user's needs and preferences, and particularities…
Robust, faithful and harm-free pronoun use for individuals is an important goal for language model development as their use increases, but prior work tends to study only one or two of these characteristics at a time. To measure progress…
One of the most crucial components of natural human-robot interaction is artificial intuition and its influence on dialog systems. The intuitive capability that humans have is undeniably extraordinary, and so remains one of the greatest…
Anthropomorphic language describing artificial intelligence (AI) is widespread in media, policy, and everyday discourse; so too are discussions of AI bad behavior, from hallucinations to inappropriate comments. How does humanizing language…