相关论文: On the Effect of Robot Errors on Human Teaching Dy…

This paper proposes a novel approach that enables a robot to learn an objective function incrementally from human directional corrections. Existing methods learn from human magnitude corrections; since a human needs to carefully choose the…

An outstanding challenge for the widespread deployment of robotic systems like autonomous vehicles is ensuring safe interaction with humans without sacrificing performance. Existing safety methods often neglect the robot's ability to learn…

Trust is a key factor in ensuring acceptable human-robot interaction, especially in settings where robots may be assisting with critical activities of daily living. When practically deployed, robots are bound to make occasional mistakes,…

This article surveys reinforcement learning approaches in social robotics. Reinforcement learning is a framework for decision-making problems in which an agent interacts through trial-and-error with its environment to discover an optimal…

During human-robot interaction (HRI), we want the robot to understand us, and we want to intuitively understand the robot. In order to communicate with and understand the robot, we can leverage interactions, where the human and robot…

With the rapid growth of computing powers and recent advances in deep learning, we have witnessed impressive demonstrations of novel robot capabilities in research settings. Nonetheless, these learning systems exhibit brittle generalization…

Achieving effective and seamless human-robot collaboration requires two key outcomes: enhanced team performance and fostering a positive human perception of both the robot and the collaboration. This paper investigates the capability of the…

Children with Autism Spectrum Disorder find robots easier to communicate with than humans. Thus, robots have been introduced in autism therapies. However, due to the environmental complexity, the used robots often have to be controlled…

Error feedback is known to improve performance by correcting control signals in response to perturbations. Here we show how adding simple error feedback can also accelerate and robustify autonomous learning in a tendon-driven robot. We…

Human-Robot Interaction, in which a robot with some level of autonomy interacts with a human to achieve a specific goal has seen much recent progress. With the introduction of autonomous robots and the possibility of widespread use of those…

Robots are used by humans not only as tools but also to interactively assist and cooperate with humans, thereby forming physical human-robot interactions. In these interactions, there is a risk that a feedback loop causes unstable force…

One of the primary goals of Human-Robot Interaction (HRI) research is to develop robots that can interpret human behavior and adapt their responses accordingly. Adaptive learning models, such as continual and reinforcement learning, play a…

It is difficult for humans to efficiently teach robots how to correctly perform a task. One intuitive solution is for the robot to iteratively learn the human's preferences from corrections, where the human improves the robot's current…

There are many examples of cases where access to improved models of human behavior and cognition has allowed creation of robots which can better interact with humans, and not least in road vehicle automation this is a rapidly growing area…

Robots learn as they interact with humans. Consider a human teleoperating an assistive robot arm: as the human guides and corrects the arm's motion, the robot gathers information about the human's desired task. But how does the human know…

With the advances in robotic technology, research in human-robot collaboration (HRC) has gained in importance. For robots to interact with humans autonomously they need active decision making that takes human partners into account. However,…

Handovers are basic yet sophisticated motor tasks performed seamlessly by humans. They are among the most common activities in our daily lives and social environments. This makes mastering the art of handovers critical for a social and…

In this paper, we develop an embodied AI system for human-in-the-loop navigation with a wheeled mobile robot. We propose a direct yet effective method of monitoring the robot's current plan to detect changes in the environment that impact…

Robots can support humans in tedious tasks, as well as provide social support. However, the decision-making and behavior of robots is not always clear to the human interaction partner. In this work, we discuss the opportunity of using…

The overarching goal of this work is to efficiently enable end-users to correctly anticipate a robot's behavior in novel situations. Since a robot's behavior is often a direct result of its underlying objective function, our insight is that…