Artificial Intelligence for Human-Robot Interaction

人机交互人工智能

• 批准号: 442588247
• 负责人: Professor Dr. Michael Beetz, Ph.D.
• 金额: --
• 依托单位: Groupe RIS - Robotique et Intéractions
• 依托单位国家: 德国
• 项目类别: Research Grants
• 资助国家: 德国
• 项目状态: 未结题
• 来源: https://gepris.dfg.de/gepris/projekt/442588247?language=en
• 关键词: Artificial; Intelligence; Human; Robot; Interaction

Europe and Japan both face problems of shrinking and aging population. This raises a number of issues like missing workforce, and robots are often seen as a possible way for alleviating them. However, that would require that robots are introduced into human societies and work in direct contact with people.The field of Human-Robot Interaction (HRI) is concerned with the ways in which robots should interact with people in the social world. But dealing with humans is notoriously difficult and represents a huge challenge. At the same time, there are many successful applications of Artificial Intelligence techniques to increasingly complex tasks. Regardless of that, the field of HRI has largely not yet taken benefit from advanced AI techniques. Conversely, HRI can be considered as a very motivating challenge for AI, where the human is physically and mentally in the loop. The goal of the AI4HRI project will be to both develop and tightly integrate several crucial AI technologies that will allow social robots to appropriately and skillfully deal with humans around them. HRI is currently missing sophisticated knowledge management methods and models, as well as knowledge reasoning abilities that can be used by a robot interacting with humans. What we are interested in: is what needs to be implemented successfully in the knowledge management system, which kind of models of the humans the robot should build, and which kind of reasoning abilities the robot should have regarding itself and the human it interacts with. Building upon this knowledge, we will study how a robot needs to socially interact with a human. Explicit manual programming of the interaction behaviors that the robot should execute is often done in HRI, but it is very difficult to create interactions that are robust to all variations of environment or human behavior. Therefore we will use machine learning techniques to learn the interaction patterns that humans use in interactions with other humans and copy them to a human-robot interaction context. The AI4HRI project brings together three teams from LAAS (France), University of Bremen (Germany), and Kyoto University (Japan), who are not only world leaders in AI or HRI, but who also have very complementary approaches to solving the issues addressed by the project. Through their synergies, we will be able to develop the integrated open-source architecture described above, which is something that could not have been possible by any of the teams alone. The goal will be achieved through continuous collaboration and meetings of the involved researchers. We are confident that the result of this project will become an important milestone for achieving a future with socially interactive robots working in close vicinity to us.

欧洲和日本都面临着人口减少和老龄化的问题。这引发了一些问题，如劳动力短缺，机器人通常被视为缓解这些问题的可能途径。然而，这需要机器人被引入人类社会，并与人类直接接触。人机交互（Human-Robot Interaction，HRI）领域关注的是机器人在社会世界中与人类互动的方式。但与人类打交道是出了名的困难，是一个巨大的挑战。与此同时，人工智能技术在越来越复杂的任务中有许多成功的应用。尽管如此，HRI领域在很大程度上还没有从先进的人工智能技术中受益。相反，HRI可以被认为是人工智能的一个非常激励人心的挑战，因为人类在身体和精神上都处于循环之中。AI4HRI项目的目标是开发并紧密集成几项关键的人工智能技术，使社交机器人能够适当而熟练地与周围的人类打交道。 HRI目前缺乏复杂的知识管理方法和模型，以及机器人与人类互动时可以使用的知识推理能力。我们感兴趣的是：是知识管理系统中需要成功实现的，机器人应该建立什么样的人类模型，以及机器人应该具有什么样的推理能力。基于这些知识，我们将研究机器人如何与人类进行社交互动。机器人应该执行的交互行为的显式手动编程通常在HRI中完成，但是很难创建对环境或人类行为的所有变化都鲁棒的交互。因此，我们将使用机器学习技术来学习人类在与其他人交互时使用的交互模式，并将其复制到人机交互环境中。AI4HRI项目汇集了来自LAAS（法国），不莱梅大学（德国）和京都大学（日本）的三个团队，他们不仅是人工智能或HRI的世界领导者，而且还拥有非常互补的方法来解决该项目所解决的问题。通过他们的协同作用，我们将能够开发上述集成的开源架构，这是任何团队都无法单独实现的。这一目标将通过有关研究人员的持续合作和会议来实现。我们相信，这个项目的结果将成为一个重要的里程碑，为实现未来的社会互动机器人在我们附近工作。