Improvements in robot autonomy are changing human-robot interaction from low-level manipulation to high-level task-based collaboration. When a robot can independently and autonomously executes tasks, a human in a human-robot team acts as a collaborator or task supervisor instead of a tele-operator. When applying this to planning paths for a robot's motion, it is very important that the supervisor's qualitative intent is translated into aquantitative model so that the robot can produce a desirable consequence. In robotic path planning, algorithms can transform a human's qualitative requirement into a robot's quantitative model so that the robot behavior satisfies the human's intent. In particular, algorithms can be created that allow a human to express multi-objective and topological preferences, and can be built to use verbal communication. This dissertation presents a series of robot motion-planning algorithms, each of which is designed to support some aspect of a human's intent. Specifically, we present algorithms for the following problems: planning with a human-motion constraint, planning with a topological requirement, planning with multiple objectives, and creating models of constraints, requirements, and objectives from verbal instructions. These algorithms create a set of robot behaviors that support flexible decision-making over a range of complex path-planning tasks.

Service robots are mobile, embodied artefacts that operate in co presence with their users. This is a challenge for human-robot interaction (HRI) design. The robot’s interfaces must support users in understanding the system’s current state and possible next actions. One aspect in the design for such interaction is to understand users’ preferences and expectations by involving them in the design process. This thesis takes a user-centered design (UCD) perspective and tries to understand the different user roles that exist in service robotics in order to consider possible design implications. Another important aim in the thesis is to understand the spatial management that occurs in face-to-face encounters between humans and robotic systems. The Cero robot is an office “fetch-and-carry” robot that supports a user in the transportation of light objects in an office environment. The iterative, user-centered design of the graphical-user interface (GUI) for the Cero robot is presented in Paper I. It is based upon the findings from multiple prototype design- and evaluation iterations. The GUI is one of the robot’s interfacing components, i.e., it is to be seen in the overall interplay of the robot’s physical design and other interface modalities developed in parallel with the GUI. As interaction strategy for the GUI, a graphical representation based upon simplification of the graphical elements as well as hiding the robot system’s complexity in sensing and mission execution is recommended. The usage of the Cero robot by a motion-impaired user over a period of three months is presented in Paper II. This longitudinal user study aims to gain insights into the daily usage of such an assistive robot. This approach is complementary to the described GUI design and development process as it allows empirically investigating situated use of the Cero robot as novel service application over a longer period of time with the provided interfaces. Findings from this trial show that the robot and its interfaces provide a benefit to the user in the transport of light objects, but also implies increased independence. The long-term study also reveals further aspects of the Cero robot system usage as part of a workplace setting, including the social context that such a mobile, embodied system needs to be designed for. During the long-term user study, bystanders in the operation area of the Cero robot were observed in their attempt to interact with it. To understand better how such bystander users may shape the interaction with a service robot system, an experimental study investigates this special type and role of robot users in Paper III. A scenario in which the Cero robot addresses and asks invited trial subjects for a cup of coffee is described. The findings show that the level of occupation significantly influences bystander users’ willingness to assist the Cero robot with its request. The joint handling of space is an important part of HRI, as both users and service robots are mobile and often co-present during interaction. To inform the development of future robot locomotion behaviors and interaction design strategies, a Wizard-of Oz (WOZ) study is presented in Paper IV that explores the role of posture and positioning in HRI. The interpersonal distances and spatial formations that were observed during this trial are quantified and analyzed in a joint interaction task between a robot and its users in Paper V. Findings show that a face-to-face spatial formation and a distance between ~46 to ~122 cm is dominant while initiating a robot mission or instructing it about an object or place. Paper VI investigates another aspect on the role of spatial management in the joint task between a robot and its user based upon the study described in Papers IV and V. Taking the dynamics of interaction into account, the findings are that users structure their activities with the robot and that this organizing is observable as small movements in interaction. These small adaptations in posture and orientation signify the transition between different episodes of interaction and prepare for the next interaction exchange in the shared space. The understanding of these spatial management behaviors allow designing human-robot interaction based upon such awareness and active handling of space as a structuring interaction element. / QC 20100617

<p>With the progress in research and product development humans and robots get more and more close to each other and the idea of a personalised general service robot is not too far fetched. Crucial for such a service robot is the ability to navigate in its working environment. The environment has to be assumed an arbitrary domestic or office-like environment that has to be shared with human users and bystanders. With methods developed and investigated in the field of simultaneous localisation and mapping it has become possible for mobile robots to explore and map an unknown environment, while they can stay localised with respect to their starting point and the surroundings. These approaches though do not consider the representation of the environment that is used by humans to refer to particular places. Robotic maps are often metric representations of features that could be obtained from sensory data. Humans have a more topological, in fact partially hierarchical way of representing environments. Especially for the communication between a user and her personal robot it is thus necessary to provide a link between the robotic map and the human understanding of the robot's workspace.</p><p>The term Human Augmented Mapping is used for a framework that allows to integrate a robotic map with human concepts. Communication about the environment can thus be facilitated. By assuming an interactive setting for the map acquisition process it is possible for the user to influence the process significantly. Personal preferences can be made part of the environment representation that the robot acquires. Advantages become also obvious for the mapping process itself, since in an interactive setting the robot could ask for information and resolve ambiguities with the help of the user. Thus, a scenario of a "guided tour" in which a user can ask a robot to follow and present the surroundings is assumed as the starting point for a system for the integration of robotic mapping, interaction and human environment representations.</p><p>Based on results from robotics research, psychology, human-robot interaction and cognitive science a general architecture for a system for Human Augmented Mapping is presented. This architecture combines a hierarchically organised robotic mapping approach with interaction abilities with the help of a high-level environment model. An initial system design and implementation that combines a tracking and following approach with a mapping system is described. Observations from a pilot study in which this initial system was used successfully are reported and support the assumptions about the usefulness of the environment model that is used as the link between robotic and human representation.</p>

Thesis--Auburn University, 2009. / Abstract. Vita. Includes bibliographical references (p. 123-126).

The development of autonomous social robots is still in its infancy, but there is no reason tothink that it will not continue. In fact, the robotics industry is growing rapidly. Since this trendis showing no signs of abating it is relevant to ask what type of relations we can have withthese machines. Is it for example possible to be friends with them? In this thesis I argue that it is unlikely that we will ever be able to be friends with robots. To believe otherwise is to be deceived, a trap it is all too easy to fall into since the efforts put on making social robots as human-like as possible and to make the human-robot interaction as smooth as possible are huge. But robots are not always what they seem. For instance, the capacity to enter into a friendship of one’s own volition is a core requirement for a relationship to be termed friendship. We also have a duty to act morally towards our friends, to treat them with due respect. To be able to do this we need to have self-knowledge, a sense of ourselves as persons in our own right. We do not have robots who display these capacities today, nor is it a given that we ever will. / Utvecklingen av autonoma sociala robotar är ännu i sin linda men det finns ingen anledning att tro att den inte kommer att fortsätta. Faktum är att robotindustrin växer kraftigt. Då denna trend inte visar några tecken på att avta är det relevant att fråga sig vilket slags relation vi kan ha till dessa maskiner. Är det t.ex. möjligt att bli vän med dem? I denna uppsats argumenterar jag för att det inte är troligt att vi någonsin kommer att kunna utveckla vänskap med en robot. Att tro något annat är en villfarelse, en fälla det är alltför lätt att falla i inte minst på grund av den möda som läggs ned på att göra robotarna så människoliknande som möjligt och robot-människa-interaktionen så smidig som möjligt. Men robotarna är inte alltid vad de verkar vara. Exempelvis är förmågan att kunna inleda ett vänskapsförhållande på eget bevåg engrundförutsättning för att relationen ska kunna klassas som vänskap. Vi har också en plikt att handla moraliskt gentemot våra vänner, att behandla dem med respekt. För att kunna göra detta måste vi ha självkännedom, en uppfattning om oss själva som personer i vår egen rätt. Robotar har inte dessa förmågor idag, och det är inte säkert att de någonsin kommer att besitta dem.

Robotic technologies possess great potential to enter our daily lives because they have the ability to interact with our world. But our world is inherently social. Whilst humans often have a natural understanding of this complex environment, it is much more challenging for robots. The field of social Human-Robot Interaction (HRI) seeks to endow robots with the characteristics and behaviours that would allow for intuitive multimodal interaction. Education is a social process and previous research has found strong links between the social behaviour of teachers and student learning. This therefore presents a promising application opportunity for social human-robot interaction. The thesis presented here is that a robot with tailored social behaviour will positively influence the outcomes of tutoring interactions with children and consequently lead to an increase in child learning when compared to a robot without this social behaviour. It has long been established that one-to-one tutoring provides a more effective means of learning than the current typical school classroom model (one teacher to many students). Schools increasingly supplement their teaching with technology such as tablets and laptops to offer this personalised experience, but a growing body of evidence suggests that robots lead to greater learning than other media. It is posited that this is due to the increased social presence of a robot. This work adds to the evidence that robots hold a social advantage over other technological media, and that this indeed leads to increased learning. In addition, the work here contributes to existing knowledge by seeking to expand our understanding of how to manipulate robot social behaviour in educational interactions such that the behaviour is tailored for this purpose. To achieve this, a means of characterising social behaviour is required, as is a means of measuring the success of the behaviour for the interaction. To characterise the social behaviour of the robot, the concept of immediacy is taken from the human-human literature and validated for use in HRI. Greater use of immediacy behaviours is also tied to increased cognitive learning gains in humans. This can be used to predict the same effect for the use of social behaviour by a robot, with learning providing an objective measure of success for the robot behaviour given the education application. It is found here that when implemented on a robot in tutoring scenarios, greater use of immediacy behaviours generally does tend to lead to increased learning, but a complex picture emerges. Merely the addition of more social behaviour is insufficient to increase learning; it is found that a balance should be struck between the addition of social cues, and the congruency of these cues.

This report will show the development of a Delta Parallel robot, to aid in teaching the basics of robotic motion programming. The platform developed will be created at a fraction of the cost of conventional commercial training systems. This report will therefore show the development procedure as well as the development of some of the example training material. The system will use wireless serial data communication in the form of a Bluetooth connection. This connection will allow an Android tablet, functioning as the human-machine interface (HMI) for the system, to communicate with the motion controller. The motion controller is based in the C environment. This will allow future development of the machine, and allow the system to be used on an integral level, should the trainers require an in depth approach. The motion control software will be implemented on a RoBoard, a development board specifically designed for low- to mid-range robotics. The conclusion of this report will show an example task being completed on the training platform. This will demonstrate some of the basic robotic motion programming aspects which include point to point, linear, and circular motion types but will also include setting and resetting outputs. Performance parameters such as repeatability and reproducibility are important, as it will indirectly show the level of ease with which the system can be manipulated from the software. Finally, the results will be briefly discussed and some recommendations for improvements on the training system and suggestions for future development will be given.

Transparency in HRI describes the method of making the current state of a robotor intelligent agent understandable to a human user. Applying transparencymechanisms to robots improves the quality of interaction as well as the userexperience. Explanations are an effective way to make a robot’s decision making transparent. We introduce a framework that uses natural language labels attached to a region inthe continuous state space of the robot to automatically generate local explanationsof a robot’s policy. We conducted a pilot study and investigated how the generated explanations helpedusers to understand and reproduce a robot policy in a debugging scenario.

abstract: As robotic technology and its various uses grow steadily more complex and ubiquitous, humans are coming into increasing contact with robotic agents. A large portion of such contact is cooperative interaction, where both humans and robots are required to work on the same application towards achieving common goals. These application scenarios are characterized by a need to leverage the strengths of each agent as part of a unified team to reach those common goals. To ensure that the robotic agent is truly a contributing team-member, it must exhibit some degree of autonomy in achieving goals that have been delegated to it. Indeed, a significant portion of the utility of such human-robot teams derives from the delegation of goals to the robot, and autonomy on the part of the robot in achieving those goals. In order to be considered truly autonomous, the robot must be able to make its own plans to achieve the goals assigned to it, with only minimal direction and assistance from the human. Automated planning provides the solution to this problem -- indeed, one of the main motivations that underpinned the beginnings of the field of automated planning was to provide planning support for Shakey the robot with the STRIPS system. For long, however, automated planners suffered from scalability issues that precluded their application to real world, real time robotic systems. Recent decades have seen a gradual abeyance of those issues, and fast planning systems are now the norm rather than the exception. However, some of these advances in speedup and scalability have been achieved by ignoring or abstracting out challenges that real world integrated robotic systems must confront. In this work, the problem of planning for human-hobot teaming is introduced. The central idea -- the use of automated planning systems as mediators in such human-robot teaming scenarios -- and the main challenges inspired from real world scenarios that must be addressed in order to make such planning seamless are presented: (i) Goals which can be specified or changed at execution time, after the planning process has completed; (ii) Worlds and scenarios where the state changes dynamically while a previous plan is executing; (iii) Models that are incomplete and can be changed during execution; and (iv) Information about the human agent's plan and intentions that can be used for coordination. These challenges are compounded by the fact that the human-robot team must execute in an open world, rife with dynamic events and other agents; and in a manner that encourages the exchange of information between the human and the robot. As an answer to these challenges, implemented solutions and a fielded prototype that combines all of those solutions into one planning system are discussed. Results from running this prototype in real world scenarios are presented, and extensions to some of the solutions are offered as appropriate. / Dissertation/Thesis / Doctoral Dissertation Computer Science 2014

abstract: Riding a bicycle requires accurately performing several tasks, such as balancing and navigation, which may be difficult or even impossible for persons with disabilities. These difficulties may be partly alleviated by providing active balance and steering assistance to the rider. In order to provide this assistance while maintaining free maneuverability, it is necessary to measure the position of the rider on the bicycle and to understand the rider's intent. Applying autonomy to bicycles also has the potential to address some of the challenges posed by traditional automobiles, including CO2 emissions, land use for roads and parking, pedestrian safety, high ownership cost, and difficulty traversing narrow or partially obstructed paths. The Smart Bike research platform provides a set of sensors and actuators designed to aid in understanding human-bicycle interaction and to provide active balance control to the bicycle. The platform consists of two specially outfitted bicycles, one with force and inertial measurement sensors and the other with robotic steering and a control moment gyroscope, along with the associated software for collecting useful data and running controlled experiments. Each bicycle operates as a self-contained embedded system, which can be used for untethered field testing or can be linked to a remote user interface for real-time monitoring and configuration. Testing with both systems reveals promising capability for applications in human-bicycle interaction and robotics research. / Dissertation/Thesis / Masters Thesis Software Engineering 2020