Shirley A. Elprama

Attitudes of Factory Workers towards Industrial and Collaborative Robots

Despite the predicted growth of the amount of collaborative robots, little attention has been paid to the attitudes and needs of potential future users of these robots (e.g. factory workers). The main goal of our study was to identify recommendations to improve collaboration between robots and factory workers. We used the collaborative robot Baxter as a probe to elicit repsonses from factory workers in order to explore their perceptions regarding working with robots. We conducted four interviews with two factory workers simultaneously participating in each interview (n = 8). These interviews were analyzed and our findings suggest that workers believe robots can and have taken peoples jobs. However, they also believe that robots can decrease their workload.

Effect of video lag on laparoscopic surgery: correlation between performance and usability at low latencies.

Few telesurgery studies assess the impact of latency on user experience, low latencies are often not studied despite evidence of negative effects, and some studies recruit inexperienced subjects instead of surgeons without evidence that latency affects both groups similarly.

Internet of Robotic Things: Context-Aware and Personalized Interventions of Assistive Social Robots (Short Paper)

Assistive service and companion robots are versatile and dexterous actuators that operate in our daily living environment. These robots are able to manipulate physical objects, to displace themselves and to engage in conversations. Human behavior is dynamic and oftentimes unpredictable, therefore it is crucial for such robotic systems to be assisted by a cloud-backend which: i) analyzes data from sensor and wearables ii) determines which robotic tasks need to be executed and iii) provides the necessary support for the execution of these tasks in our daily living environment. In this paper, we present our Internet-of-Robotic-Things system architecture design for a case study on personal interactions by a companion robot to alleviate behavioral disturbances of people with dementia.

Social-aware Event Handling within the FallRisk Project

OBJECTIVES With the uprise of the Internet of Things, wearables and smartphones are moving to the foreground. Ambient Assisted Living solutions are, for example, created to facilitate ageing in place. One example of such systems are fall detection systems. Currently, there exists a wide variety of fall detection systems using different methodologies and technologies. However, these systems often do not take into account the fall handling process, which starts after a fall is identified or this process only consists of sending a notification. The FallRisk system delivers an accurate analysis of incidents occurring in the home of the older adults using several sensors and smart devices. Moreover, the input from these devices can be used to create a social-aware event handling process, which leads to assisting the older adult as soon as possible and in the best possible way. METHODS The FallRisk system consists of several components, located in different places. When an incident is identified by the FallRisk system, the event handling process will be followed to assess the fall incident and select the most appropriate caregiver, based on the input of the smartphones of the caregivers. In this process, availability and location are automatically taken into account. RESULTS The event handling process was evaluated during a decision tree workshop to verify if the current day practices reflect the requirements of all the stakeholders. Other knowledge, which is uncovered during this workshop can be taken into account to further improve the process. CONCLUSIONS The FallRisk offers a way to detect fall incidents in an accurate way and uses context information to assign the incident to the most appropriate caregiver. This way, the consequences of the fall are minimized and help is at location as fast as possible. It could be concluded that the current guidelines on fall handling reflect the needs of the stakeholders. However, current technology evolutions, such as the uptake of wearables and smartphones, enables the improvement of these guidelines, such as the automatic ordering of the caregivers based on their location and availability.

What Could Go Wrong: Lessons Learned When Doing HRI User Studies with Off-the-Shelf Social Robots

Today, off-the-shelf social robots are used increasingly in the HRI community to research social interactions with different target user groups across a range of domains (e.g. healthcare, education, retail and other public spaces). We invite everyone doing HRI studies with end users, in the lab or in the wild, to collect past experiences of methods and practices that had issues or did not turn out as expected. This could include but is not limited to experimental setup, unplanned interactions, or simply the difficulty in transferring theory to the real world. In order to be able to generalize and compare differences across multiple HRI domains and create common solutions, we are focusing in this workshop on experiences with often used off-the-shelf social robots. We are interested in identifying the underlying causes of the unexpected HRI results, e.g. the contextual, task, and user related factors that influence interaction with a robot platform. We will furthermore discuss and document (ad hoc) solutions and/or lessons learned such that they can be shared with the HRI community. As well as sharing specific case studies documenting real world HRI experiences, we further hope to inspire the continued sharing of open and insightful reflections within the HRI community.

Exploring Privacy and Trust Issues in a Future Immersive Videoconferencing System

Existing standard videoconferencing tools have failed in creating an experience equal to formal face-to-face meetings. In an effort to overcome this challenge, ICOCOON was developed to create an immersive meeting experience. In its current state this videoconferencing tool displays video streams of all participants and a Virtual Meeting Room (VMR) portraying participants as avatars around one table. To create an effortless meeting experience in the immersive environment, the Virtual Director (VD) translates behaviors such as speaking and raising ones hand from the video stream to the VMR with the help of smart software. However, when delegating power to technology, privacy concerns arise. By creating a video prototype of the tool, we probed and discussed topics such as privacy and trust in technology. We found that users trade off their privacy concerns with benefits of using the proposed technology. To illustrate this trade-off, we extended an existing privacy perception model.