Man-Machine Interoperation in Training for Large Force Exercise Air Missions

Patrick L. Craven, Kevin B. Oden,

Kevin J. Landers, David J. Macannuco

更多

Ankit J. Shah and Julie A. Shah

Lockheed Martin Corporation

Massachusetts Institute of Technology

Orlando, Florida

Cambridge, Massachusetts

patrick.craven@lmco.com, kevin.oden@lmco.com, kevin.j.landers@lmco.com, david.j.macannuco@lmco.com

ajshah@mit.edu, julie_a_shah@csail.mit.edu

收起

This article discusses the technology of city digital twins (CDTs) and its potential applications in the policymaking context. The article analyzes the history of the development of the concept of digital twins and how it is now being adopted on a city-scale. One of the most advanced projects in the field—Virtual Singapore—is discussed in detail to determine the scope of its potential domains of application and highlight challenges associated with it. Concerns related to data privacy, availability, and its applicability for predictive simulations are analyzed, and potential usage of synthetic data is proposed as a way to address these challenges. The authors argue that despite the abundance of urban data, the historical data are not always applicable for predictions about the events for which there does not exist any data, as well as discuss the potential privacy challenges of the usage of micro-level individual mobility data in CDTs. A task-based approach to urban mobility data generation is proposed in the last section of the article. This approach suggests that city authorities can establish services responsible for asking people to conduct certain activities in an urban environment in order to create data for possible policy interventions for which there does not exist useful historical data. This approach can help in addressing the challenges associated with the availability of data without raising privacy concerns, as the data generated through this approach will not represent any real individual in society.

Revitalizing Human-Machine Interaction for the Advancement of Society

Introduction

This acatech DISCUSSION identifies specific societal problems in the two focus countries. Like this, it shows possible ways in which new approaches to human-machine interaction can have a positive impact on the development of a more sustainable society. The paper was developed in collaboration with Platform Industrie 4.0 and the Robot Revolution and Industrial IoT Initiative (RRI).

更多

An aging workforce, a shortage of skilled workers, and aging machinery and infrastructure present countries such as Japan and Germany with similar social challenges. To counteract these potential problems, maintain productivity and competitiveness at a high level, and promote sustainability, digital technologies are being employed. Examples are cyber-physical systems (CPS), artificial intelligence (AI) and robotics. The collaboration or interaction between people and machines plays an important role here. Initiatives such as Industrie 4.0 in Germany or Society 5.0 in Japan provide support.

The implementation of these technologies also has a significant impact on the development or change in society. They will primarily perform cognitive routine work previously reserved for humans.

In the course of the digital transformation, however, conditions are being created for a new, human-centered model of human-machine interaction.

The solutions of the two analyzed countries diverge due to different social developments and culturally-induced differences in the approaches. This publication highlights the country-specific differences and similarities and thus identifies potential areas of cooperation for future German-Japanese initiatives.

收起

ESB Business School Reutlingen / Fraunhofer Austria Research / TU Vienna

Implications for Learning Factories from Industry 4.0

Challenges for the human factor in future production scenarios

更多

Andreas Jäger, MSc, MBA

Prof. Dr. Wilfried Sihn

Fraunhofer Austria Research GmbH

Vienna University of Technology

Fabian Ranz, MSc

Prof. Dr. Vera Hummel

ESB Business School, Reutlingen University

收起

Bringing technology to the people

Research programme on human-machine interaction

Three Faces of Human–Computer Interaction

Jonathan Grudin

Microsoft Research

通过这份技术文档，可以了解无人驾驶运输系统手势控制的技术基础。

VideoPlace系统和Theremin系统能够对自由手势的回应，但功能更加广泛的界面可能需要一个标志性的手势界面。在这种情况下，某些指令则牵涉到一些预先练习过的手势。标志性手势界面经常用于沉浸式虚拟环境中，相比传统输入设备，用户无法在其中看到现实世界。这种设置通常配有一套预练习过的手势，用于在虚拟环境中导航和与虚拟物件进行交互。例如在Rubber Rocks虚拟环境中，用户可以通过做拳头手势拾起虚拟的石块，展开手掌即可掷出石块(Codella, 1992)。“手势驱动的虚拟环境交互”（GIVEN，Gesture-driven Interactions in VirtualEnvironments）是一个虚拟环境应用神经网络，它可识别达到20个静态和动态手势(Vaananen and Bohm, 1993)。这些手势功能包括：指向手势表示飞行，拳头手势表示抓取，以及其他全手掌手势表示释放物件或者在虚拟界面中回到出发点。尽管Baudel和 Beaudouin-Lafon (1993)指出使用标志性手势在交互功能方面的许多优点，包括：

更多

•自然交互：手势是一种自然的交互形式并且容易使用。

•简洁有力：一个手势可以用于指定命令和命令参数。

•直接交互：手作为输入设备可免除中介传感器。

但是，在交互界面中仅使用标志性手势的做法存在一些缺点。例如：用户可能会因为需要记忆大量的手势而厌烦。显然，随着手势功能的增多，手势指令就越难被用户记住。同时，这里也存在切分手势的问题。很多时候，用户所选用的手势可能不过是重复日常生活中用到的十分自然的手势。识别系统会捕捉所有的用户动作，那么任何一个手势指令都需要在被识别出来之前从连续的动作流中切分。

收起