Human models for accelerated robot learning and human-robot interaction

用于加速机器人学习和人机交互的人体模型

• 批准号: DP240101458
• 负责人: Prof Dana Kulic
• 金额: $ 37.06万
• 依托单位: Monash University
• 依托单位国家: 澳大利亚
• 项目类别: Discovery Projects
• 财政年份: 2024
• 资助国家: 澳大利亚
• 起止时间: 2024-01-01 至 2026-12-31
• 项目状态: 未结题
• 来源: https://dataportal.arc.gov.au/RGS/Web/Grants/DP240101458
• 关键词: Human; models; accelerated; robot; learning

This project aims to develop novel approaches to teach robots to proficiently interact with humans in a safe and low-cost manner. To achieve this aim, this project will develop novel models from which various human behaviours can be generated and used to train human-robot interaction policies in simulation. Expected outcomes of this project include new computational models of human behaviour built using cognitive science theories and limited data and new training schemes for robot learning in simulation. By training robots in simulation with accurate human models, this research will enable fast and safe robot training to support the deployment and adoption of robots in human contexts such as healthcare facilities, homes, and workplaces.

该项目旨在开发新颖的方法来教机器人以安全和低成本的方式熟练地与人互动。为了实现这一目标，该项目将开发新的模型，从中可以从中产生各种人类行为，并用于训练模拟中的人类机器人相互作用策略。该项目的预期结果包括使用认知科学理论和有限的数据以及用于模拟中机器人学习的新培训方案建立的人类行为的新计算模型。通过与准确的人类模型进行模拟的培训机器人，这项研究将使快速安全的机器人培训能够支持在医疗机构，房屋和工作场所等人类环境中的部署和采用机器人。