User Study Exploring the Role of Explanation of Failures by Robots in Human Robot Collaboration Tasks

Despite great advances in what robots can do, they still experience failures in human-robot collaborative tasks due to high randomness in unstructured human environments. Moreover, a human's unfamiliarity with a robot and its abilities can cause such failures to repeat. This makes the ability to failure explanation very important for a robot. In this work, we describe a user study that incorporated different robotic failures in a human-robot collaboration (HRC) task aimed at filling a shelf. We included different types of failures and repeated occurrences of such failures in a prolonged interaction between humans and robots. The failure resolution involved human intervention in form of human-robot bidirectional handovers. Through such studies, we aim to test different explanation types and explanation progression in the interaction and record humans.Comment: Contributed to the: "The Imperfectly Relatable Robot: An interdisciplinary workshop on the role of failure in HRI", ACM/IEEE International Conference on Human-Robot Interaction HRI 2023. Video can be found at: https://sites.google.com/view/hri-failure-ws/teaser-video

A complementing approach for identifying ethical issues in care robotics – grounding ethics in practical use

We use a long-term study of a robotic eating-aid for disabled users to illustrate how empirical use give rise to a set of ethical issues that might be overlooked in ethic discussions based on theoretical extrapolation of the current state-of-the-art in robotics. This approach provides an important complement to the existing robot ethics by revealing new issues as well as providing actionable guidance for current and future robot design. We discuss our material in relation to the literature on robot ethics, specifically the risk of robots performing care taking tasks and thus causing increased isolation for care recipients. Our data identifies a different set of ethical issues such as independence, privacy, and identity where robotics, if carefully designed and developed, can make positive contributions

A corpus-based analysis of route instructions in human-robot interaction

This paper investigates how users employ spatial descriptions to navigate a speech-enabled robot. We created a simulated environment in which users gave route instructions in a dialogic real-time interaction with a robot, which was operated by naïve participants. The ability of robot monitoring was also manipulated in two experimental conditions. The results provide evidence that the content of the instructions and strategies of the users vary depending on the conditions and demands of the interaction. As expected, the route instructions frequently were underspecified and arbitrary. The findings of this study elucidate the complexity in interpreting spatial language in HRI. However, they also point to the need for endowing mobile robots with richer dialogue resources to compensate for the uncertainties arising from language as well as the environment

How do you Play with a Robotic Toy Animal? A long-term study of Pleo

Pleo is one of the more advanced interactive toys currently available for the home market, taking the form of a robotic dinosaur. We present an exploratory study of how it was interacted with and reflected upon in the homes of six families during 2 to 10 months. Our analysis emphasizes a discrepancy between the participants’ initial desires to borrow a Pleo and what they reported later on about their actual experiences. Further, the data suggests an apparent tension between participants expecting the robot to work as a ‘toy’ while making consistent comparisons with real pet animals. We end by discussing a series of implications for design of this category of toys, in order to better maintain interest and engagement over time

Disability rights and robotics: Co-producing futures

This project brought together a team of 25 co-researchers from the University of the West of England, Fairfield Farm College and Wiltshire Centre of Independent Living. The co-researchers are a diverse group including disabled people, carers, students, and academics from social work, psychology and sociology to robotics. Our research team demonstrates a wealth of experiences as some members had both lived experience of disability, in addition to being involved in teaching, learning and research. The research question for the project was:How can robotic technologies support disability rights? Rights are about everyday opportunities to live life to the full, human rights that everyone is entitled to (The Convention on the Rights of Persons with Disabilities (CRPD) 2009 (Enable.un.org, 2019). In this time of rapid social change to our social and work lives, relationships and leisure, there are new technologies that might support disability rights like ‘driverless cars’, smart phones, social media and new robotic technologies. The project had two aims:•to identify priority research questions into disability rights and robotics•to develop the co-production process for future researc

Roborodentia Robot (Duct Tape Craze)

Roborodentia is an annual autonomous robotics competition held at Cal Poly in April. In 2017, Roborodentia was a head-to-head double elimination tournament with the winner being the robot that moves more rings onto the scoring pegs. For this year’s competition, I designed, built, programmed, and tested a robot

Learning to reach and reaching to learn: a unified approach to path planning and reactive control through reinforcement learning

The next generation of intelligent robots will need to be able to plan reaches. Not just ballistic point to point reaches, but reaches around things such as the edge of a table, a nearby human, or any other known object in the robot’s workspace. Planning reaches may seem easy to us humans, because we do it so intuitively, but it has proven to be a challenging problem, which continues to limit the versatility of what robots can do today. In this document, I propose a novel intrinsically motivated RL system that draws on both Path/Motion Planning and Reactive Control. Through Reinforcement Learning, it tightly integrates these two previously disparate approaches to robotics. The RL system is evaluated on a task, which is as yet unsolved by roboticists in practice. That is to put the palm of the iCub humanoid robot on arbitrary target objects in its workspace, start- ing from arbitrary initial configurations. Such motions can be generated by planning, or searching the configuration space, but this typically results in some kind of trajectory, which must then be tracked by a separate controller, and such an approach offers a brit- tle runtime solution because it is inflexible. Purely reactive systems are robust to many problems that render a planned trajectory infeasible, but lacking the capacity to search, they tend to get stuck behind constraints, and therefore do not replace motion planners. The planner/controller proposed here is novel in that it deliberately plans reaches without the need to track trajectories. Instead, reaches are composed of sequences of reactive motion primitives, implemented by my Modular Behavioral Environment (MoBeE), which provides (fictitious) force control with reactive collision avoidance by way of a realtime kinematic/geometric model of the robot and its workspace. Thus, to the best of my knowledge, mine is the first reach planning approach to simultaneously offer the best of both the Path/Motion Planning and Reactive Control approaches. By controlling the real, physical robot directly, and feeling the influence of the con- straints imposed by MoBeE, the proposed system learns a stochastic model of the iCub’s configuration space. Then, the model is exploited as a multiple query path planner to find sensible pre-reach poses, from which to initiate reaching actions. Experiments show that the system can autonomously find practical reaches to target objects in workspace and offers excellent robustness to changes in the workspace configuration as well as noise in the robot’s sensory-motor apparatus

Making robotic autonomy through science and law?

This document reports on the Epinet workshop on the making of robot autonomy, held in Utrecht 16-17 February 2014. The workshop was part of a case study focused on developments in this area, in particular, autonomy for assistive robots in care and companionship roles. Our participants were of relevant expertise and professional experience: law and ethics, academic and industry robotics, vision assessment and science and technology studies (STS). The workshop was intended to explore the expectations of robot autonomy amongst our participants, against a backdrop of recent policy views and research trends that are openly pushing an agenda of "smarter", more dynamic and more autonomous systems (e.g. European Commission, 2008; EUROP, 2009; Robot Companions for Citizens, 2012). Robotics development is intimately connected with visions of robot autonomy, however, as a practical achievement, robot autonomy remains till this day part real, part promise. Ideas of robot autonomy are nevertheless powerful societally and culturally-specific visions, even if the very notion of "autonomy" is vague and inconsistent in recent accounts of future robots. These accounts still come together with considerable force in directing the efforts of researchers and experimenters, for example, in establishing funding priorities. They have a function in strategic planning for future developments. Accounts of future robots are also informing and shaping the efforts of legislators, ethicists and lawyers. To that effect, one can say that there is an official vision of future robots, a yardstick with which everyone implicated in robotics development has to measure their expectations