Related papers: A Hierarchical Architecture for Human-Robot Cooper…
This paper presents a planning algorithm designed to improve cooperative robot behavior concerning human comfort during forceful human-robot physical interaction. Particularly, we are interested in planning for object grasping and…
To understand and collaborate with humans, robots must account for individual human traits, habits, and activities over time. However, most robotic assistants lack these abilities, as they primarily focus on predefined tasks in structured…
Designing an efficient and resilient human-robot collaboration strategy that not only upholds the safety and ergonomics of shared workspace but also enhances the performance and agility of collaborative setup presents significant challenges…
In collaborative robotic applications, human and robot have to work together during a whole shift for executing a sequence of jobs. The performance of the human robot team can be enhanced by scheduling the right tasks to the human and the…
Human-robot collaboration frequently requires extensive communication, e.g., using natural language and gestures. Augmented reality (AR) has provided an alternative way of bridging the communication gap between robots and people. However,…
Effective human-robot collaboration requires informed anticipation. The robot must anticipate the human's actions, but also react quickly and intuitively when its predictions are wrong. The robot must plan its actions to account for the…
We propose a hierarchical framework for collaborative intelligent systems. This framework organizes research challenges based on the nature of the collaborative activity and the information that must be shared, with each level building on…
Though construction robots have drawn attention in research and practice for decades, human-robot collaboration (HRC) remains important to conduct complex construction tasks. Considering its complexity and uniqueness, it is still unclear…
The new paradigm of human-robot collaboration has led to the creation of shared work environments in which humans and robots work in close contact with each other. Consequently, the safety regulations have been updated addressing these new…
Human-robot collaborative assembly systems enhance the efficiency and productivity of the workplace but may increase the workers' cognitive demand. This paper proposes an online and quantitative framework to assess the cognitive workload…
Efficient and robust task planning for a human-robot collaboration (HRC) system remains challenging. The human-aware task planner needs to assign jobs to both robots and human workers so that they can work collaboratively to achieve better…
Large Language Models (LLMs) are gaining popularity in the field of robotics. However, LLM-based robots are limited to simple, repetitive motions due to the poor integration between language models, robots, and the environment. This paper…
Remarkable capabilities have been achieved by robotics and AI, mastering complex tasks and environments. Yet, humans often remain passive observers, fascinated but uncertain how to engage. Robots, in turn, cannot reach their full potential…
Mammals can generate autonomous behaviors in various complex environments through the coordination and interaction of activities at different levels of their central nervous system. In this paper, we propose a novel hierarchical learning…
In this work, we propose a distributed hierarchical locomotion control strategy for whole-body cooperation and demonstrate the potential for migration into large numbers of agents. Our method utilizes a hierarchical structure to break down…
The rise of automation has provided an opportunity to achieve higher efficiency in manufacturing processes, yet it often compromises the flexibility required to promptly respond to evolving market needs and meet the demand for…
We present a novel framework for human-robot \emph{logical} interaction that enables robots to reliably satisfy (infinite horizon) temporal logic tasks while effectively collaborating with humans who pursue independent and unknown tasks.…
Applying Deep Reinforcement Learning (DRL) to Human-Robot Cooperation (HRC) in dynamic control problems is promising yet challenging as the robot needs to learn the dynamics of the controlled system and dynamics of the human partner. In…
The increasing presence of robots alongside humans, such as in human-robot teams in manufacturing, gives rise to research questions about the kind of behaviors people prefer in their robot counterparts. We term actions that support…
Transporting large and heavy objects can benefit from Human-Robot Collaboration (HRC), increasing the contribution of robots to our daily tasks and reducing the risk of injuries to the human operator. This approach usually posits the human…