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This paper presents a survey of research into interactive robotic systems for the purpose of identifying the state of the art capabilities as well as the extant gaps in this emerging field. Communication is multimodal. Multimodality is a representation of many modes chosen from rhetorical aspects for its communication potentials. The author seeks to define the available automation capabilities in communication using multimodalities that will support a proposed Interactive Robot System (IRS) as an AI mounted robotic platform to advance the speed and quality of military operational and tactical decision making.

This review will begin by presenting key developments in the robotic interaction field with the objective of identifying essential technological developments that set conditions for robotic platforms to function autonomously. After surveying the key aspects in Human Robot Interaction (HRI), Unmanned Autonomous System (UAS), visualization, Virtual Environment (VE) and prediction, the paper then proceeds to describe the gaps in the application areas that will require extension and integration to enable the prototyping of the IRS. A brief examination of other work in HRI-related fields concludes with a recapitulation of the IRS challenge that will set conditions for future success.

Using insights from a balanced cross section of sources from the government, academic, and commercial entities that contribute to HRI a multimodal IRS in military communication is introduced. Multimodal IRS (MIRS) in military communication has yet to be deployed.

Multimodal robotic interface for the MIRS is an interdisciplinary endeavour. This is not realistic that one can comprehend all expert and related knowledge and skills to design and develop such multimodal interactive robotic interface. In this brief preliminary survey, the author has discussed extant AI, robotics, NLP, CV, VDM, and VE applications that is directly related to multimodal interaction. Each mode of this multimodal communication is an active research area. Multimodal human/military robot communication is the ultimate goal of this research.

A multimodal autonomous robot in military communication using speech, images, gestures, VST and VE has yet to be deployed. Autonomous multimodal communication is expected to open wider possibilities for all armed forces. Given the density of the land domain, the army is in a position to exploit the opportunities for human–machine teaming (HMT) exposure. Naval and air forces will adopt platform specific suites for specially selected operators to integrate with and leverage this emerging technology. The possession of a flexible communications means that readily adapts to virtual training will enhance planning and mission rehearsals tremendously.

Interaction, perception, cognition and visualization based multimodal communication system is yet missing. Options to communicate, express and convey information in HMT setting with multiple options, suggestions and recommendations will certainly enhance military communication, strength, engagement, security, cognition, perception as well as the ability to act confidently for a successful mission.

The objective is to develop a multimodal autonomous interactive robot for military communications. This survey reports the state of the art, what exists and what is missing, what can be done and possibilities of extension that support the military in maintaining effective communication using multimodalities. There are some separate ongoing progresses, such as in machine-enabled speech, image recognition, tracking, visualizations for situational awareness, and virtual environments. At this time, there is no integrated approach for multimodal human robot interaction that proposes a flexible and agile communication. The report briefly introduces the research proposal about multimodal interactive robot in military communication.

The purpose of this study is to assess the influence of Al and Ag addition on thermal, mechanical and shape memory properties of Cu-Al-Ag alloy.

The material is synthesized in a controlled atmosphere to minimize the reaction of alloying elements with the atmosphere. Cast samples were homogenized, then subjected to hot rolling and further betatized, followed by step quenching. Eight samples were chosen for study among which first four samples varied in Al content, and the next set of four samples varied in Ag composition.

The testing yielded a result that the increase in binary alloying element decreased transformation temperature range but increased entropy and elastic energy values. It also improved the shape memory effect and mechanical properties (UTS and hardness). An increase in ternary alloying element increased transformation temperature range, entropy and elastic energy values. The shape memory effect and mechanical properties are enhanced by the increase in ternary alloying element. The study revealed that compositional variation of Al should be limited to a range of 8 to 14 Wt.% and Ag from 2 to 8 Wt.%. Microstructural and diffraction studies identified the ß’1 martensite as a desirable phase for enhancing shape memory properties.

Numerous studies have been made in exploring the transformation temperature and phase formation for similar Cu-Al-Ag shape memory alloys, but their influence on shape memory effect was not extensively studied. In the present work, the influence of Al and Ag content on shape memory characteristics is carried out to increase the design choice for engineering applications of shape memory alloy. These materials exhibit mechanical and shape memory properties within operating ranges similar to other copper-based shape memory alloys.