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With the rapid development of artificial intelligence, service robots play an increasingly important role in frontline service across various industries. However, many questions surrounding service robots as a novel service option are still less studied, and thus, remain uncertain to marketers. Therefore, this dissertation investigated and addressed some of these questions, by assessing the potential advantages of service robots, not only as compared to human employees, but also among service robots’ different humanlike vocal features, including voice types, accents, and speaking styles. Specifically, to address the research gaps identified through an in-depth literature review conducted in Chapter 2, a series of empirical studies were conducted and presented in Chapter 3 (Essay One) and Chapter 4 (Essay Two). Chapter 3 begins with Study 1a, an investigation into the potential advantages of service robots as compared to human employees in a hotel check-in setting. The findings suggest that service robots outperform human employees in customers’ enjoyment of the interactions. Study 1b replicated the earlier study in a fast-food restaurant setting, where service robots were found to outperform human employees in customers’ word-of-mouth (WOM) intentions as well. In Study 2, an investigation specifically into a service robot’s vocal design was conducted, by comparing three potential voice types (male, female, or robotic) in a movie theater setting. The findings reveal that a human male voice is the most ideal across various customer outcomes, highlighting the importance for marketers to determine the optimal voice type for a service robot. Chapter 4 reports further investigations of service robots’ vocal design, specifically regarding their accents and speaking styles. In Study 3, four subordinate studies were conducted in a hotel check-in setting. The findings suggest that when a service robot’s accent is congruent with its local region, it enhances customers’ perceived enjoyment of the interactions and various customer outcomes. In Study 4, a further investigation was conducted into a service robot’s speaking style, to assess its potential influence under a service failure and recovery context. The findings suggest that a service robot’s use of a colloquial speaking style attenuates customers’ perceived competence of the service robot and related customer outcomes, which further highlight the importance of a service robot’s appropriate language use, especially during a service recovery. A general discussion regarding Study 1 to Study 4 was provided in Chapter 5, offering valuable implications to both scholars and marketers, and suggesting promising avenues for future research.

Mobile robots can be used in situations and environments that are distant from an operator. In order for an operator to control a robot effectively he or she requires an understanding of the environment and situation around the robot. Since the robot is at a remote distant from the operator and cannot be directly observed, the information necessary for an operator to develop an understanding or awareness of the robot's situation comes from the user interface. The usefulness of the interface depends on the manner in which the information from the remote environment is presented. Conventional interfaces for interacting with mobile robots typically present information in a multi-windowed display where different sets of information are presented in different windows. The disjoint sets of information require significant cognitive processing on the part of the operator to interpret and understand the information. To reduce the cognitive effort to interpret the information from a mobile robot, requirements and technology for a three-dimensional augmented virtuality interface are presented. The 3D interface is designed to combine multiple sets of informationinto a single correlated window which can reduce the cognitive processing required to interpret and understand the information in comparison to a conventional (2D) interface. The usefulness of the 3D interface is validated, in comparison to a prototype of conventional 2D interfaces, through a series of navigation- and exploration-based user-studies. The user studies reveal that operators are able to drive the robot, build maps, find and identify items, and finish tasks faster with the 3D interface than with the 2D interface. Moreover, operators have fewer collisions, void walls better, and use a pan-tilt-zoom camera more with the 3D interface than with the 2D interface. Performance with the 3D interface is also more tolerant to network delay and distracting sets of information. Finally, principles for presenting multiple sets of information to a robot operator are presented. The principles are used to discuss and illustrate possible extensions of the 3D interface to other domains.

By observing human driving with a “digital head" (combined video camera and accelerometers) and taking a few hand annotations, we can automatically annotate regions in a robot's field of view that should be interpreted as obstacles to be avoided. This is accomplished by detecting the movement for a given frame in a video. Some hand annotations of video frames are necessary and they are used to create Probability Grids. Using the movement data and the Probability Grids, it is possible to annotate large amounts of video data quickly in an automated system.

This study focused on intervention using a humanoid robot to facilitate social engagement and joint attention in four children with autism. Intervention was conducted over a three month period, with each child receiving pre-testing, intervention, and post-testing. Intervention was based on the SCERTS model (Prizant, Wetherby, Rubin, & Laurent, 2003). Pre- and post-testing involved interactions with a parent, a familiar adult interaction, a less-familiar adult interaction, and a triadic interaction. This study focuses on the baseline and follow-up testing from the interaction with the familiar adult. Following a period of traditional intervention, sessions involving a humanoid robot (named Troy) were conducted. The robot was integrated into the therapy in a low dose model, meaning that during a 50-minute therapy session, approximately 10 minutes were designated to interactions using the robot to facilitate the interaction. Pre- and post-intervention assessments were recorded, analyzed, and coded for social engagement behaviors. Results comparing baseline to follow-up assessments of the interactions with the familiar adult indicated that the most notable changes were observed in reciprocal action and eye contact. Little change was noted in initiation of social engagement, symbolic play, and language. The implications of these results are discussed and recommendations for future research are provided.

This study examined the effects of low dose exposure to a humanoid robot on the social engagement skills of four children with autism during select activities with a familiar adult. Participants included two males and two females who ranged in age from four to nine at the commencement of the study. The current study was part of a larger investigation focused on the effect of exposure to a robot on social engagement with a variety of social partners and situations. Children participated in variable multiple baseline sessions followed by a varied number of sessions of traditional treatment. After traditional treatment, the children participated in 40 minutes of traditional intervention paired with 10 minutes of exposure to a robot designed to elicit social communication skills. The final sessions consisted of follow up assessments. Pre- and posttreatment data were compared and analyzed. Results showed variable performance for each of the participants. Findings and areas of future research are discussed.

This thesis presents the research and development behind the integration of an autonomous propulsion system for a four-wheeled Ground Penetrating Radar (GPR) measurement unit, previously requiring manual operation. In order to ease the administration of the complex new system, Robot Operating System (ROS) 2 was used as middleware, where an implementation of Light Detection And Ranging (LiDAR) 3D-SLAM (Simultaneous Localization And Mapping) served to secure precise localization of the Unmanned Ground Vehicle (UGV) and mapping of its environment. This, with the ultimate goal of enabling accurate survey execution along paths optimized for various dynamic indoor- and outdoor environments. From a more general point of view, this work can also act as a hardware- and software selection guide for similar projects, especially if stricter physical limitations apply and the autonomous system is not considered the primary system, but the majority of the internal enclosed space of the UGV is reserved for higher purpose equipment or storage requirements. In this first prototype iteration, the mapping accuracy of the autonomous system reached centimeter precision and the execution of surveys in grid- and spiral patterns yielded position accuracies of 5(2) cm and 6(4) cm, respectively. These results are indeed very promising and show the proof of concept needed to enter the next development phase.

A disaster usually severely harms human health and property. After a disaster, great amount of information of a disaster area is needed urgently. The information not only indicates the severity of the disaster, but also is crucial for an efficient search and rescue process. In order to quickly and accurately collect real time information in a disaster scenario, a mobile platform is developed for an outdoor scenario and a localization and navigation system for responders is introduced for an indoor scenario. The mobile platform has been integrated to the DIORAMA system. It is built with a 6-wheel robot chassis along with an Arduino microcontroller. Controlled by a mounted Android smartphone, the mobile platform can receive commands from incident commanders and quickly respond to the commands. While patrolling in a disaster area, a constant RFID signal is collected to improve the localization accuracy of victims. Pictures and videos are also captured in order to enhance the situational awareness of rescuers. The design of the indoor information collection is focused on the responder side. During a disaster scenario, it is hard to track responders’ locations in an indoor environment. In this thesis, an indoor localization and navigation system based on Bluetooth low energy and Android is developed for helping responders report current location and quickly find the right path in the environment. Different localization algorithms are investigated and implemented. A navigation system based on A­* is also proposed.

Sending a man in space is extremely dangerous. In order to continue the space exploration, robots have to be used. Designed properly, robots can handle any kind of operations in deep space. But in space there is no support such as an after-sale service. That is why their conception must be as perfect as possible to satisfy many tests. This is also the case of the ERA (European Robotic Arm). Its operations must be tested on the ground. But since forces acting at ground level are different than in space (e.g. gravity), the ERA must be in such position (the Iron Bird project) so that the target that it wants to reach must be brought by another robot. This other robot is called ERICA (Era Iron-bird CLU hArdware simulation). The goal of this project is to make the mechanical conception of the ERICA. The project was carried out in four parts. The first consisted in gathering information about the ERA in order to establish the requirements. The second was a pre-conception part. The third consists in explaining the research that had been made to choose the proper design of the ERICA. In the fourth part, the mechanical and electrical conception is presented. The ERICA is a gantry system where the payload is a gimbal holding a target. That way, the 6 degrees of freedoms of the ERA are achieved. The gantry system is provided by LinMotion and the motors by Maxon. The electronic parts are attached to the gantry at different places. A frame surrounds the working envelope so that the CLU (Camera and Lightning Units) can be fixed on it as well as protective plates against the CLU’s laser.

Human activity regions (HARs) are human-centric semantic partitions where observing and/or interacting with humans is likely in indoor environments. HARs are useful for achieving successful human-robot interaction, such as in safe navigation around a building or to know where to be able to assist humans in their activities. In this thesis, a system is designed for generating HARs automatically based on data recorded by robots. This approach to generating HARs is to cluster the areas that are commonly associated with frequent human presence. In order to detect human positions, we employ state-of-the-art perception techniques. The environment that the robot patrols is assumed to be an indoor environment such as an office. We show how we can generate HARs in correct regions by clustering human position data. The experimental evaluations show that we can do so in different indoor environments, with data acquired from different sensors and that the system can handle noise. / Mänskliga aktivitetsregioner, HARs (Human Activity Regions) är människocentreraderegioner som ger en semantisk partitionering av inomhusmiljöer. HARs är användbara för att uppnå väl fungerande människarobot- interaktioner. I denna avhandling utformas ett system för att generera HARs automatiskt baserat på data från robotar. Detta görs genom att klustra observationer av människor för att på så vis få fram de områden som är associerade med frekvent mänsklig närvaro. Experiment visar att systemet kan hantera data som registrerats av olika sensorer i olika inomhusmiljöer och att det är robust. Framförallt genererar systemet en pålitlig partitionering av miljön.