13 accepted papers
Offline reinforcement learning (Offline RL) provides a compelling solution for applying RL in high-risk or resourceconstrained real-world domains such as healthcare, autonomous driving, and robotic manipulation, where online exploration can be unsafe or impractical. However, Offline RL faces critica
Offline reinforcement learning (Offline RL) provides a compelling solution for applying RL in high-risk or resource-constrained real-world domains such as healthcare, autonomous driving, and robotic manipulation. However, Offline RL faces critical challenges arising from limited data coverage and po…
Due to recent advances in large language models and robotics, social robots will potentially play an important role in people’s daily lives soon, and are expected to improve dynamic multi-party group discussions in social scenarios. In this paper, we developed a system to assist dynamic group discus
Socially assistive robots are potentially to be integrated with human daily lives in the near future, and expected to be able to improve group dynamics when interacting with groups of people in social settings. In this paper, we developed a system with desktop robot Haru to assist group discussions.…
Social robots are gradually integrating into human’s daily lives. Storytelling by social robots could bring a different experience to users through non-verbal and emotional capabilities compared to text-only one. However, as user needs and preferences over storytelling might change over time during…
Social robots for children have focused mainly on conventional education domains such as teaching language, science, and math, while applications focusing on the enhancement of cultural competency are quite scarce. In this paper, we present a prototype of a robot-mediation framework for cross-cultur…
In this paper, building on recent advances in the fields of gaming AI and social robotics, we present a new approach to facilitate the social robot Haru to imitate game strategies from human players’ demonstrated trajectories and evaluative feedback in a real-time two-player game. Our research shows…
Deep reinforcement learning has achieved great success in many challenging domains. However, sample efficiency and safety issues still prevent from applying deep reinforcement learning directly in robotics. Sim-to-real transfer learning is one feasible solution to tackle these problems and address t
Conveying a robot's target mood is crucial to successful social interactions. The robot's expressive performance must be appropriate, persuasive, and consistent. However, this is challenging when interactions contain a mixture of scripted and improvised content, such as those generated by language m…
This paper describes the development of a 3- stage signalling framework to trigger a social robot's bottom- up reactive behavior inspired by a biological model. In the first stage, low-level firing of stimuli due to external sources is constructed through perception grounding. This is followed by a…
Conversation can play an essential role in forging bonds between humans and social robots, but participants need to feel like they are being listened to, remembered, and cared about in order to effectively build rapport. In this paper, we propose a novel strategy for conducting small talk with a soc…
Storytelling plays a central role in human socializing and entertainment, and research on conducting storytelling with robots is gaining interest. However, much of this research assumes that story content is curated. In this paper, we expand the recently-proposed task of collaborative storytelling,…
Realistic recordings of soundscapes often have multiple sound events co-occurring, such as car horns, engine and human voices. Sound event retrieval is a type of contentbased search aiming at finding audio samples, similar to an audio query based on their acoustic or semantic content. State of the a…