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

Remote real-time monitoring of subsurface landfill gas migration

The cost of monitoring greenhouse gas emissions from landfill sites is of major concern for regulatory authorities. The current monitoring procedure is recognised as labour intensive, requiring agency inspectors to physically travel to perimeter borehole wells in rough terrain and manually measure gas concentration levels with expensive hand-held instrumentation. In this article we present a cost-effective and efficient system for remotely monitoring landfill subsurface migration of methane and carbon dioxide concentration levels. Based purely on an autonomous sensing architecture, the proposed sensing platform was capable of performing complex analytical measurements in situ and successfully communicating the data remotely to a cloud database. A web tool was developed to present the sensed data to relevant stakeholders. We report our experiences in deploying such an approach in the field over a period of approximately 16 months

Computational steering of a multi-objective evolutionary algorithm for engineering design

The execution process of an evolutionary algorithm typically involves some trial and error. This is due to the difficulty in setting the initial parameters of the algorithm—especially when little is known about the problem domain. This problem is magnified when applied to many-objective optimisation, as care is needed to ensure that the final population of candidate solutions is representative of the trade-off surface. We propose a computational steering system that allows the engineer to interact with the optimisation routine during execution. This interaction can be as simple as monitoring the values of some parameters during the execution process, or could involve altering those parameters to influence the quality of the solutions produced by the optimisation process. The implementation of this steering system should provide the ability to tailor the client to the hardware available, for example providing a lightweight steering and visualisation client for use on a PDA

Making Heat Visible: Promoting Energy Conservation Behaviors Through Thermal Imaging

Householders play a role in energy conservation through the decisions they make about purchases and installations such as insulation, and through their habitual behavior. The present U.K. study investigated the effect of thermal imaging technology on energy conservation, by measuring the behavioral effect after householders viewed images of heat escaping from or cold air entering their homes. In Study 1 (n = 43), householders who received a thermal image reduced their energy use at a 1-year follow-up, whereas householders who received a carbon footprint audit and a non-intervention control demonstrated no change. In Study 2 (n = 87), householders were nearly 5 times more likely to install draught proofing measures after seeing a thermal image. The effect was especially pronounced for actions that addressed an issue visible in the images. Findings indicate that using thermal imaging to make heat loss visible can promote energy conservation

From Keyword Search to Exploration: How Result Visualization Aids Discovery on the Web

A key to the Web's success is the power of search. The elegant way in which search results are returned is usually remarkably effective. However, for exploratory search in which users need to learn, discover, and understand novel or complex topics, there is substantial room for improvement. Human computer interaction researchers and web browser designers have developed novel strategies to improve Web search by enabling users to conveniently visualize, manipulate, and organize their Web search results. This monograph offers fresh ways to think about search-related cognitive processes and describes innovative design approaches to browsers and related tools. For instance, while key word search presents users with results for specific information (e.g., what is the capitol of Peru), other methods may let users see and explore the contexts of their requests for information (related or previous work, conflicting information), or the properties that associate groups of information assets (group legal decisions by lead attorney). We also consider the both traditional and novel ways in which these strategies have been evaluated. From our review of cognitive processes, browser design, and evaluations, we reflect on the future opportunities and new paradigms for exploring and interacting with Web search results

Proximity Map Projection: Interactive Visualisation for Image-Guided Surgery

This thesis describes a new interface technique for neurosurgeons and interventional radiologists performing image-guided therapies such as the ablation of brain tumours. This new technique is called Proximity Map Projection (PMP). Based on an analysis of related work, including the documented recent progress in enabling technologies, a case is made that present-day interactive visualisations supporting image-guided treatment of tumours will need to be dramatically improved to take advantage of the increased image refresh rates available as soon as 2020. This probable requirement for improved visualisation technology in the very near future motivated the invention and investigation of the PMP technique described in this thesis. The PMP technique is an interactive 2-D visual projection of the proximity of two 3-D surfaces – in particular, the surface representing the boundary of a thermal treatment region, and the surface of a tumour that is the target of this treatment. By clicking on interesting points in the PMP, surgeons are able to quickly select the 2-D MRI slices corresponding to those interesting points. The PMP provides a quick way of selecting a desired image from a large stack of 2-D MRI data, thus freeing up surgeons to spend a greater proportion of their time applying their expertise to decision making, rather than to navigating through image data. In this thesis, the PMP technique is presented and then refined as user studies are undertaken. In a series of investigations exploring its effectiveness, it is shown that the PMP technique enables non-expert users to quickly and accurately navigate to, and observe, desired individual medical images within large stacks of such images. A further experiment finds no significant differences in the way that medically experienced and inexperienced users use PMP to complete tasks. That study also verifies that users pay visual attention to PMP, regardless of whether or not they have interacted with it via the mouse. Observation of the visual attention of users during simulated tasks is used to provide further explanation of why PMP is effective. PMP’s potential to be used by medical professionals is then assessed via a series of semi-structured interviews with surgeons and interventional radiologists. Such experts are found to be optimistic about the potential for PMP to be incorporated into their workflows. This last phase of the research then culminates with observations of a number of medical procedures on human patients that are similar to the kinds of procedures to which PMP might be applied. From these observations it appears that, while they do enable life-saving therapies, present software interfaces are not entirely satisfying for the surgeons who use them. Opportunities for significant future research collaborations were identified during these interviews and observations. This thesis concludes by describing a practical path towards achieving its ultimate goal: the use of PMP in real-time image-guided medical procedures on human patients. Key activities on this path include: integration of PMP into the training and simulation version of a collaborator’s therapy system; conducting a case study to allow further refinement of the PMP technique; and inclusion of PMP in a clinical trial with surgeons