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Design Approach for Investigating Multimodal Communication in Dismounted Soldier-Robot Interaction

机译:拆下士兵 - 机器人交互中多式联通信的设计方法

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For several decades there has been continuous growth in the field of robotics, with recent trends driving towards a vision of humans collaborating in a cohesive unit with automated counterparts. Enabling true mixed-initiative teaming between a human and robot will require communication capabilities and cognition comparable to human teammates. Multimodal communication is a framework in which interfaces can be created supporting the flexible selection of different modalities (e.g. speech, gestures) for these transactions. A major challenge for human factors researchers investigating human robot collaboration with multimodal interfaces is the current limitations of robots. Therefore, simulations and wizard-of-oz type experiments are heavily employed to measure performance, workload, and other factors in future mixed-initiative scenarios. Although these techniques facilitate experimentation, it can be difficult to transition findings to working prototypes of today's robots. For example, a researcher finds an effective way to convey a robots decision making rationale in a simulation-based study, but has no working robot that can drive the content in reality. Furthermore, the literature regarding multimodal communication with robots applied to the military domain is limited. For example, evaluation of different modalities as part of an interrupting task has been explored in driving scenarios, but not between robot(s) and soldiers. In many cases there is conflict in findings across domains. To address this challenge, this paper describes how a multimodal interface for a real robotic platform developed under the U.S. Army Research Labs Robotics Collaborative Technology Alliance (RCTA) was extended to support standalone simulation of interactions and integration with simulated virtual environments. This functionality enables researchers to assess new interaction techniques using the same software that will interact with a real platform to facilitate transition of their research. Furthermore, experiment design approaches including theory-based tasks in a military relevant mission (Cordon and Search) are discussed.
机译:几十年来,机器人领域一直在持续增长,近期趋势朝着自动对应物的凝聚力组合的人类展望。在人类和机器人之间实现真正的混合主动组合将需要与人类队友相当的沟通能力和认知。多模式通信是一种框架,其中可以创建接口的接口,支持这些事务的灵活选择不同的模态(例如语音,手势)。人类因素研究人员研究人体机器人与多式联合界面的重大挑战是机器人的当前限制。因此,仿真和向导型型实验受到衡量未来混合主动方案中的性能,工作量和其他因素。虽然这些技术有助于实验,但是难以过渡到今天机器人的工作原型。例如,研究人员发现在基于模拟的研究中传达机器人决策的有效方法,但没有工作机器人可以推动现实内容。此外,关于应用于军事领域的机器人的多式联连通的文献是有限的。例如,在驾驶场景中探讨了作为中断任务的一部分的不同方式的评估,但在机器人和士兵之间没有。在许多情况下,跨域的调查结果存在冲突。为了解决这一挑战,本文介绍了在美国陆军研究实验室机器人协作技术联盟(RCTA)下开发的真正机器人平台的多模式界面是如何扩展到支持与模拟虚拟环境的独立模拟。此功能使研究人员能够使用与真实平台交互的相同软件来评估新的交互技术,以便于转变他们的研究。此外,讨论了在军事相关任务(CORTON和SECARCE)中包括基于理论的任务的实验设计方法。

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