NRI: Collaborative Goal and Policy Learning from Human Operators of Construction Co¬-Robots

本研究的总体目标是调查和显著推进人类操作员和协作机器人之间的协作交互科学。这包括算法的开发，可用于训练协作机器人从熟练的人类操作员有效地执行复杂的任务，面对现实世界的不确定性，并指导新手操作员执行这些任务。主要目标应用是建筑和农业设备行业，包括复杂的协作机器人，如挖掘机、轮式装载机、拖拉机、饲草收割机，这些行业非常需要理解和改进人机协作学习。为协作机器人开发有效的算法存在重大的科学挑战，这些算法可以通过观察和提出适当的查询来主动向熟练的人类操作员学习，以关闭协作机器人和人类操作员之间的反馈回路。该项目通过系统地制定和调查重点问题来解决这些挑战，以创建可以增强人机协作学习的有效算法。为了实现这一目标，设计了从定义不清的复杂任务中协同学习潜在子目标结构的算法，开发了用于协作机器人实现学习到的子目标的实时路径规划和控制算法，并开发了针对操作员技能的任务分解和运动执行指导技术。此外，所开发的算法通过模拟器、实验室和现场协作机器人的硬件实验以及理论分析得到了验证。

The overall goal of this research is to investigate and significantly advance the science of collaborative interaction between human operators and co-robots. This includes the development of algorithms that can be used to train co-robots from skilled human operators to efficiently perform complex tasks in the face of real-world uncertainty, and to guide novice operators in performing such tasks. The primary targeted application is the construction and farming equipment industry that includes complex co-robots such as excavators, wheel loaders, tractors, forage harvesters where there is a significant need to understand and improve human-robot collaborative learning.There are significant scientific challenges in developing efficient algorithms for co-robots that can actively learn from skilled human operators by observing and posing appropriate queries to close the feedback loop between the co-robot and the human operator. This project addresses these challenges by systematically formulating and investigating focused problems to create efficient algorithms that can enhance collaborative human-robot learning. To achieve the goal, algorithms are designed to collaboratively learn latent subgoal structures from ill-defined complex tasks, real-time path planning and control algorithms are developed for co-robots to achieve the learned subgoals, and techniques are developed to provide operator skill specific task decomposition and motion execution guidance. In addition, the developed algorithms are corroborated by simulators, hardware experimentation on laboratory and field co-robots, and theoretical analysis.