Game Theoretic Approaches to Advancing Physical Human-Robot Collaborations through Nudging

人类在日常生活中执行许多需要与他人合作的任务。在这些场景中，两个人一起工作，预测对方的行为，并引导他们的伴侣朝着共同的目标前进。例如，两个人可以毫不费力地移动和翻转仓库中的大箱子。同样，一个人可以把酒倒进另一个人拿着的杯子里，而不会洒出来。该项目的主要重点是了解在二元协作场景中隐式沟通的影响。该项目的目标是开发一个机器人系统，能够利用意图估计，博弈论和轻推技术，以提高最先进的物理人类机器人协作。我们相信，一个成功的结果是在工业部门，在酒店业以及我们的家庭更广泛地使用机器人合作伙伴的推动力。该项目内的工作重点是系统的以下具体方面。(i)开发了一个推理模块，可以根据人类的运动历史预测人类的意图和行动。(ii)评估感官前馈线索，可以使合作更直观和消除歧义代理的行动（iii）利用轻推理论来影响人类的行为，以减轻人类意图的消除歧义。(iv)开发一个基于“心理理论”的计划器，该计划器应用博弈论来做出决策，并促进“角色扮演”，以实现有效的协作互动。(v)利用上述框架在现有硬件上演示人机协同操作

Humans perform numerous tasks in their daily life that require collaboration with others. In these scenarios the two humans work together, anticipate how the other will behave and guide their partner towards the joint goal. For instance, two humans can effortlessly move and flip large boxes in a warehouse. Likewise, a human can pour wine into a glass held out by another human, without spilling.The main focus of the project is to understand the effects of implicit communication in dyadic collaborative scenarios. The goal of the project is to develop a robotic system capable of exploiting intention estimation, game theoretic and nudging techniques to improve the state of the art in physical human robot collaboration. We believe that a successful outcome is an enabler for the broader use of robot partners in the industrial sector, in the hospitality sector as well as in our homes.The work within this project with focus on the following specific aspects of the system.(i) Development of an inference module that can predict the human's intentions and action based on the history of the human's motion.(ii) Evaluate sensory feedforward cues that can make collaboration more intuitive and disambiguate agent's actions(iii) Utilise nudge theory to influence the human's behaviour to ease the disambiguation of human intentions.(iv) Develop a planner based on the 'theory of mind' that applies game theory to make decisions and facilitates 'role taking' for effective interactions in collaboration.(v) Exploit the framework above to demonstrate human-robot co-manipulation on existing hardware