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As robots get more integrated into human environments, fostering trustworthiness in embodied robotic agents becomes paramount for an effective and safe human-robot interaction (HRI). To achieve that, HRI applications must promote human…
Shared control improves Human-Robot Interaction by reducing the user's workload and increasing the robot's autonomy. It allows robots to perform tasks under the user's supervision. Current eye-tracking-driven approaches face several…
Labor shortages have severely affected the meat processing sector. Automated technology has the potential to support the meat industry, assist workers, and enhance job quality. However, existing automation in meat processing is highly…
To improve the efficiency and reduce the labour cost of the renovation process, this study presents a lightweight Convolutional Neural Network (CNN)-based architecture to extract crack-like features, such as cracks and joints. Moreover,…
Despite the widespread adoption of industrial robots in automotive assembly, wire harness installation remains a largely manual process, as it requires precise and flexible manipulation. To address this challenge, we design a novel AI-based…
Human-robot collaboration (HRC) in the construction industry depends on precise and prompt recognition of human motion intentions and actions by robots to maximize safety and workflow efficiency. There is a research gap in comparing data…
We propose a framework for vision-based human pose estimation and motion prediction that gives conformal prediction guarantees for certifiably safe human-robot collaboration. Our framework combines aleatoric uncertainty estimation with OOD…
The use of a team of humanoid robots to collaborate in completing a task is an increasingly important field of research. One of the challenges in achieving collaboration, is mutual identification and tracking of the robots. This work…
Physical human-robot collaboration (pHRC) requires both compliance and safety guarantees since robots coordinate with human actions in a shared workspace. This paper presents a novel fixed-time adaptive neural control methodology for…
Automating the current bridge visual inspection practices using drones and image processing techniques is a prominent way to make these inspections more effective, robust, and less expensive. In this paper, we investigate the development of…
In the rapidly evolving landscape of Human-Robot Collaboration (HRC), effective communication between humans and robots is crucial for complex task execution. Traditional request-response systems often lack naturalness and may hinder…
Human-robot collaborations have been recognized as an essential component for future factories. It remains challenging to properly design the behavior of those co-robots. Those robots operate in dynamic uncertain environment with limited…
Inspired by the human ability to selectively focus on relevant information, this paper introduces relevance, a novel dimensionality reduction process for human-robot collaboration (HRC). Our approach incorporates a continuously operating…
This research report explores the role of eye gaze in human-robot interactions and proposes a learning system for detecting objects gazed at by humans using solely visual feedback. The system leverages face detection, human attention…
This paper addresses human-robot collaboration (HRC) challenges of integrating predictions of human activity to provide a proactive-n-reactive response capability for the robot. Prior works that consider current or predicted human poses as…
When humans work together to complete a joint task, each person builds an internal model of the situation and how it will evolve. Efficient collaboration is dependent on how these individual models overlap to form a shared mental model…
Human-robot collaboration (HRC) relies on accurate and timely recognition of human intentions to ensure seamless interactions. Among common HRC tasks, human-to-robot object handovers have been studied extensively for planning the robot's…
We present an approach for the verification and validation (V&V) of robot assistants in the context of human-robot interactions (HRI), to demonstrate their trustworthiness through corroborative evidence of their safety and functional…
In the realm of construction safety, the detection of personal protective equipment, such as helmets, plays a critical role in preventing workplace injuries. This paper details the development and evaluation of convolutional neural networks…
The current capabilities of robotic systems make human collaboration necessary to accomplish complex tasks effectively. In this work, we are introducing a framework to ensure safety in a human-robot collaborative environment. The system is…