Ontology-based collaborative framework for disaster recovery scenarios

This paper aims at designing of adaptive framework for supporting collaborative work of different actors in public safety and disaster recovery missions. In such scenarios, firemen and robots interact to each other to reach a common goal; firemen team is equipped with smart devices and robots team is supplied with communication technologies, and should carry on specific tasks. Here, reliable connection is mandatory to ensure the interaction between actors. But wireless access network and communication resources are vulnerable in the event of a sudden unexpected change in the environment. Also, the continuous change in the mission requirements such as inclusion/exclusion of new actor, changing the actor's priority and the limitations of smart devices need to be monitored. To perform dynamically in such case, the presented framework is based on a generic multi-level modeling approach that ensures adaptation handled by semantic modeling. Automated self-configuration is driven by rule-based reconfiguration policies through ontology

A corpus-based analysis of route instructions in human-robot interaction

This paper investigates how users employ spatial descriptions to navigate a speech-enabled robot. We created a simulated environment in which users gave route instructions in a dialogic real-time interaction with a robot, which was operated by naïve participants. The ability of robot monitoring was also manipulated in two experimental conditions. The results provide evidence that the content of the instructions and strategies of the users vary depending on the conditions and demands of the interaction. As expected, the route instructions frequently were underspecified and arbitrary. The findings of this study elucidate the complexity in interpreting spatial language in HRI. However, they also point to the need for endowing mobile robots with richer dialogue resources to compensate for the uncertainties arising from language as well as the environment

Challenges in Collaborative HRI for Remote Robot Teams

Collaboration between human supervisors and remote teams of robots is highly challenging, particularly in high-stakes, distant, hazardous locations, such as off-shore energy platforms. In order for these teams of robots to truly be beneficial, they need to be trusted to operate autonomously, performing tasks such as inspection and emergency response, thus reducing the number of personnel placed in harm's way. As remote robots are generally trusted less than robots in close-proximity, we present a solution to instil trust in the operator through a `mediator robot' that can exhibit social skills, alongside sophisticated visualisation techniques. In this position paper, we present general challenges and then take a closer look at one challenge in particular, discussing an initial study, which investigates the relationship between the level of control the supervisor hands over to the mediator robot and how this affects their trust. We show that the supervisor is more likely to have higher trust overall if their initial experience involves handing over control of the emergency situation to the robotic assistant. We discuss this result, here, as well as other challenges and interaction techniques for human-robot collaboration.Comment: 9 pages. Peer reviewed position paper accepted in the CHI 2019 Workshop: The Challenges of Working on Social Robots that Collaborate with People (SIRCHI2019), ACM CHI Conference on Human Factors in Computing Systems, May 2019, Glasgow, U

A gentle transition from Java programming to Web Services using XML-RPC

Exposing students to leading edge vocational areas of relevance such as Web Services can be difficult. We show a lightweight approach by embedding a key component of Web Services within a Level 3 BSc module in Distributed Computing. We present a ready to use collection of lecture slides and student activities based on XML-RPC. In addition we show that this material addresses the central topics in the context of web services as identified by Draganova (2003)

Digital Systems Teaching and Research (DSTR) Robot: A Flexible Platform for Education and Applied Research

The DSTR (pronounced “Disaster”) robot has a strong history of being adaptable to different user’s needs, and there are many opportunities ahead that indicate that the sky, quite literally, is not the limit for this robust platform. This paper provides a historical perspective on the development of the DSTR robot as a collaborative design developed by the Mobile Integrated Solutions Laboratory (MISL) at Texas A&M University and ASEP 4X4 Inc. Texas Instruments has been a major partner in the integration of the control electronics, and Texas Space Technology Applications and Research (T STAR) LLC has played a significant role in the propagation of the DSTR robot as an adaptable applied research/education/STEM outreach platform. The paper will present examples of the strong industry-academic relationships that allow the DSTR robot to be utilized in a multitude of experiential learning environments. In addition to a number of STEM outreach activities, the DSTR robots are being used in the Introduction to Engineering course at Blinn College and in the Freshman Engineering curriculum at Texas A&M University. DSTRs have also been selected by NASA scientists as a low-cost lunar sample collector. The paper will also discuss the newly developed DSTR-E (DSTR Engineering) unit which requires students to perform several engineering tasks during the build process. The paper will also include the lessons learned from initial design through its transfer to the private sector for commercialization and future plans.Cockrell School of Engineerin