Related papers: A Human-In-The-Loop Simulation Framework for Evalu…
The utility of Human-in-the-loop telerobotic systems (HiLTS) is driven in part by the quality of feedback it can provide to the operator. While the dynamic interaction between robot and environment can often be sensed or modeled, the…
Autonomous vehicles must remain safe and effective when encountering rare long-tailed scenarios or cyber-physical intrusions during driving. We present RAIL, a risk-aware human-in-the-loop framework that turns heterogeneous runtime signals…
This paper presents a method for tailoring a parametric controller based on human ratings. The method leverages supervised learning concepts in order to train a reward model from data. It is applied to a gait rehabilitation robot with the…
Human-in-the-loop (HITL) UAV operation is essential in complex and safety-critical aerial surveying environments, where human operators provide navigation intent while onboard autonomy must maintain accurate and robust state estimation. A…
We tackle the problem of developing humanoid loco-manipulation skills with deep imitation learning. The difficulty of collecting task demonstrations and training policies for humanoids with a high degree of freedom presents substantial…
In this paper, we introduce a novel conceptual model for a robot's behavioral adaptation in its long-term interaction with humans, integrating dynamic robot role adaptation with principles of flow experience from psychology. This…
Effective human-AI collaboration for physical task completion has significant potential in both everyday activities and professional domains. AI agents equipped with informative guidance can enhance human performance, but evaluating such…
Physical Human-Robot Interaction (pHRI) is critical for implementing Industry 5.0, which focuses on human-centric approaches. However, few studies explore the practical alignment of pHRI to industrial-grade performance. This paper…
Rendering accurate multisensory feedback is critical to ensure natural user behavior in driving simulators. In this work, we present a virtual reality (VR)-based Vehicle-in-the-Loop (ViL) simulator that provides visual, vestibular, and…
This paper proposes a method for designing human-robot collaboration tasks and generating corresponding trajectories. The method uses high-level specifications, expressed as a Signal Temporal Logic (STL) formula, to automatically synthesize…
This work presents algorithms for the feedback-stabilised walking of bipedal humanoid robotic platforms, along with the underlying theoretical and sensorimotor frameworks required to achieve it. Bipedal walking is inherently complex and…
Recent advances in reinforcement learning (RL) have enabled impressive humanoid behaviors in simulation, yet transferring these results to new robots remains challenging. In many real deployments, the primary bottleneck is no longer…
In this paper, we present a novel nonparametric motion flow model that effectively describes a motion trajectory of a human and its application to human robot cooperation. To this end, motion flow similarity measure which considers both…
With the rapid development of Aerial Physical Interaction, the possibility to have aerial robots physically interacting with humans is attracting a growing interest. In one of our previous works, we considered one of the first systems in…
Physically assistive robots in home environments can enhance the autonomy of individuals with impairments, allowing them to regain the ability to conduct self-care and household tasks. Individuals with physical limitations may find existing…
Human-robot interaction (HRI) has long studied how agents and people coordinate to achieve shared goals. In this work, we formalize and benchmark the non-intrusive assistance as an independent paradigm of HRI, where a robot proactively…
Information systems increasingly leverage artificial intelligence (AI) and machine learning (ML) to generate value from vast amounts of data. However, ML models are imperfect and can generate incorrect classifications. Hence,…
Motion imitation is a pivotal and effective approach for humanoid robots to achieve a more diverse range of complex and expressive movements, making their performances more human-like. However, the significant differences in kinematics and…
Agentic AI systems, powered by Large Language Models (LLMs), offer transformative potential for value co-creation in technical services. However, persistent challenges like hallucinations and operational brittleness limit their autonomous…
Autonomous robots have the potential to serve as versatile caregivers that improve quality of life for millions of people worldwide. Yet, conducting research in this area presents numerous challenges, including the risks of physical…