Various strategies have been explored for robots to prevent navigation blocks. However, such blocks may still happen and robots then need to resolve them. Blocks may happen either on the robot’s path or target location and may be caused either by human or object obstacles. In this paper we explore the design of robot behaviors to resolve such navigation blocks by asking humans for help. These behaviors combine different communication modalities in steps with increasing urgency. We focus on robots with limited sensing capabilities and present findings from an in-person experiment evaluating these behaviors. Our findings illustrate that humans can be more easily engaged to solve blocks caused by themselves rather than by third party objects. They also highlight the complexity of having robots with limited sensing capabilities successfully enact sequential interactions with their bystanders.

As robots increasingly share spaces with people, it becomes important for them to behave according to our social norms. In this paper, we explore the problem of finding socially acceptable locations for a robot to wait for a shared elevator by learning from expert annotations. Access to relevant, unlabeled data is however scarce in this setting and annotations expensive to gather, as they require explicit knowledge about the social norms, the robot, and the service it carries out. We tackle this low-data regime as follows. First, we use Procedural Content Generation to generate plausible waiting scenes to be annotated. Second, we leverage available sociological studies and operationalize relevant social norms as feature maps. We train a variety of models with only 125 procedurally-generated expert-annotated scenes, testing the impact of the proposed feature maps. In our ablation study, the feature maps help the models’ performance and their generalization capabilities to non-synthetic, real scenes. We inspect the decisions taken by the best models, probing their strengths and weaknesses, and identifying general issues and discussing potential solutions.

Many features of a wheelchair affect users' actions in a manual wheelchair, determining the overall mobility performance. Based on an ethnographic study of wheelchair users in India, we develop a trajectory analysis centered on the wheelchair as an artefact and the stages in its lifecycle from design to use. This paper focuses on the decisions made and practices in the production and acquisition phases and the consequences further down the line for the end user. In particular, we focus on how different configurations of the user across production and acquisition can make it difficult for users to find a wheelchair well adapted to their situated needs once they bring the artefact into their home and daily routines.

This paper examines the advantages and disadvantages of combining Human-Like and Machine-Like behaviors for a robot taking a shared elevator with a bystander as part of an office delivery service scenario. We present findings of an in-person wizard-of-oz experiment that builds on and implements behavior policies developed in a previous study. In this experiment, we found that the combination of Machine-Like and Human-Like behaviors was perceived as better than Human-Like behaviors alone. We discuss possible reasons and point to key capabilities that a socially competent robot should have to achieve better Human-Like behaviors in order to seamlessly negotiate a social encounter with bystanders in a shared elevator or similar scenario. We found that establishing and maintaining a shared transactional space is one of these key requirements.

The design and development of robots involve the essential step of selecting and testing robotic interfaces. This interface selection requires careful consideration as the robot’s physical embodiment influences and adds to the traditional interfaces’ complexities. Our paper presents a decision support design framework for the a priori selection of robotic interface that was inductively formulated from our case study of designing a robot to collaborate with employees with cognitive disabilities. Our main contribution is to provide a novel framework that outlines the interface requirements according to user, robot, tasks and environment and facilitates a structured comparison of interfaces against those requirements. The framework is assessed for its potential applicability and usefulness through a qualitative study with HRI experts. The framework is appreciated as a systematic tool that enables documentation and discussion, and identified issues inform the framework’s iteration. The themes of ownership of this process in interdisciplinary teams and its role in iteratively designing interfaces are discussed.

In this paper, we present our ongoing research on socially acceptable robot navigation for an indoor elevator sharing scenario. Informed by naturalistic observations of human elevator use, we discuss the social nuances involved in a seemingly simple activity like taking an elevator and the challenges and limitations of modeling robot behaviors based on a full human-like approach. We propose the principle of machine-like for the design of robot behavior policies that effectively accomplish tasks without being disruptive to the routines of people sharing the elevator with the robots. We explored this approach in a bodystorming session and conducted a preliminary evaluation of the resulting considerations through an online user study. Partic-ipants differentiated robots from humans for issues of proxemics and priority, and machine-like behaviors were preferred over human-like behaviors. We present our findings and discuss the advantages and limitations identified for both approaches for designing socially acceptable navigation behaviors.

In this paper we compare two departments of a public administration body carrying out similar work. In one department two sections, telephony and processing, are collocated whereas in the other they are not. We demonstrate the costs of distribution, in particular how the strictly enforced division of labour and limited visibility onto the workflow of the other section causes problems when dealing with normal, natural exceptions. The setting is one of seemingly routine bureaucratic work rather than high-skilled cooperative work, thus the impact of distribution might be considered rather surprising. We argue that a key requirement for any solution is to enable practitioners on the 'shop floor' the freedom to find elegant solutions to problems.

This paper describes how achieving consistent colour reproduction across different devices is a complicated matter. Although there is a technological infrastructure for managing colour across devices this is very rarely used as intended. This infrastructure has been created by modelling the problem of colour management as a wholly technical one. In this paper we illustrate the importance of understanding the management of colour as a socio-technical problem, by describing the findings of a multi-sited ethnography of designers and print shops. Our analysis of the ethnography reveals that designers build up practical, tangible, visual understandings of colour and that these do not fit with the current solution, which requires users to deal with colour in an abstract manner. This paper builds on previous research in CSCW which has considered the importance of socio-technical systems, bringing the work into a previously unexplored domain. It shows how an understanding of the social can also be central when designing technical infrastructures.

This paper argues that the design of remote help-giving systems should be grounded in articulation work and the methodical ways in which help-givers and help-seekers coordinate their problem solving activities. We provide examples from ethnographic studies of both immediate and remote help-giving to explicate what we mean by articulation work and to tease out common and characteristic methods involved in help-seeking and the giving of expert advice. We then outline how emerging technologies might best be used to support articulation work in the design and development of systems for remote troubleshooting of devices with embedded computing capabilities.