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The new industrial settings are characterized by the presence of human and robots that work in close proximity, cooperating in performing the required job. Such a collaboration, however, requires to pay attention to many aspects. Firstly,…
Recent advancements in humanoid robotics, including the integration of hierarchical reinforcement learning-based control and the utilization of LLM planning, have significantly enhanced the ability of robots to perform complex tasks. In…
Effective human-robot collaboration requires robot to adopt their roles and levels of support based on human needs, task requirements, and complexity. Traditional human-robot teaming often relies on a pre-determined robot communication…
This paper introduces CognitiveDog, a pioneering development of quadruped robot with Large Multi-modal Model (LMM) that is capable of not only communicating with humans verbally but also physically interacting with the environment through…
We perform a Systematic Literature Review to discover how Humanoid robots are being applied in Socially Assistive Robotics experiments. Our search returned 24 papers, from which 16 were included for closer analysis. To do this analysis we…
Large-language models (LLMs) hold significant promise in improving human-robot interaction, offering advanced conversational skills and versatility in managing diverse, open-ended user requests in various tasks and domains. Despite the…
We propose augmenting the empathetic capacities of social robots by integrating non-verbal cues. Our primary contribution is the design and labeling of four types of empathetic non-verbal cues, abbreviated as SAFE: Speech, Action (gesture),…
Legacy (unsupported) robotic platforms often lose research utility when manufacturer support ends, preventing integration of modern sensing, speech, and interaction capabilities. We present the Enhanced NAO, a revitalized version of…
The growing presence of service robots in human-centric environments, such as warehouses, demands seamless and intuitive human-robot collaboration. In this paper, we propose a collaborative shelf-picking framework that combines multimodal…
The development of human-robot collaboration has the ability to improve manufacturing system performance by leveraging the unique strengths of both humans and robots. On the shop floor, human operators contribute with their adaptability and…
Humanoid social robots are increasingly present in daily life, making sustained user engagement a critical factor for their effectiveness and acceptance. While prior work has often examined affective evaluations or anthropomorphic design,…
Natural language interfaces can simplify interaction with multi-robot systems, especially when non-expert users need to issue high-level commands. Acoustic manipulation using ultrasonic phased arrays also enables contactless object handling…
Social robots aim to establish long-term bonds with humans through engaging conversation. However, traditional conversational approaches, reliant on scripted interactions, often fall short in maintaining engaging conversations. This paper…
In this paper, we present a framework for real-time autonomous robot navigation based on cloud and on-demand databases to address two major issues of human-like robot interaction and task planning in global dynamic environment, which is not…
The integration of collaborative robots into industrial environments has improved productivity, but has also highlighted significant challenges related to operator safety and ergonomics. This paper proposes an innovative framework that…
Recent advancements in multimodal Human-Robot Interaction (HRI) datasets have highlighted the fusion of speech and gesture, expanding robots' capabilities to absorb explicit and implicit HRI insights. However, existing speech-gesture HRI…
To facilitate natural and intuitive interactions with diverse user groups in real-world settings, social robots must be capable of addressing the varying requirements and expectations of these groups while adapting their behavior based on…
Large Language Models (LLMs) present a promising frontier in robotic task planning by leveraging extensive human knowledge. Nevertheless, the current literature often overlooks the critical aspects of robots' adaptability and error…
Human emotions are expressed through multiple modalities, including verbal and non-verbal information. Moreover, the affective states of human users can be the indicator for the level of engagement and successful interaction, suitable for…
We present a novel framework for designing emotionally agile robots with dynamic personalities and memory-based learning, with the aim of performing adaptive and non-deterministic interactions with humans while conforming to shared social…