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How do humans want to interact with collaborative robots? As robots become more common and useful not only in industry but also in the home, they will need to interact with humans to complete many varied tasks. Previous studies have demonstrated that autonomous robots are often more efficient and preferred over those that need to be commanded, or those that give instructions to humans. We believe that the types of actions that make up a task affect the preference of participants for different interaction styles. In this work, our goal is to explore tasks with different action types together with different interaction styles to find the specific situations in which different interaction styles are preferred. We have identified several classifications for table-top tasks and have developed a set of tasks that vary along two of these dimensions together with a set of different interaction styles that the robot can use to choose actions. We report on results from a series of human-robot interaction studies involving a PR2 completing table-top tasks with a human. The results suggest that people prefer robot-led interactions for tasks with a higher cognitive load and human-led interactions for joint actions. [ABSTRACT FROM AUTHOR]

How do humans want to interact with collaborative robots? As robots become more common and useful not only in industry but also in the home, they will need to interact with humans to complete many varied tasks. Previous studies have demonstrated that autonomous robots are often more efficient and preferred over those that need to be commanded, or those that give instructions to humans. We believe that the types of actions that make up a task affect the preference of participants for different interaction styles. In this work, our goal is to explore tasks with different action types together with different interaction styles to find the specific situations in which different interaction styles are preferred. We have identified several classifications for table-top tasks and have developed a set of tasks that vary along two of these dimensions together with a set of different interaction styles that the robot can use to choose actions. We report on results from a series of human-robot interaction studies involving a PR2 completing table-top tasks with a human. The results suggest that people prefer robot-led interactions for tasks with a higher cognitive load and human-led interactions for joint actions. [ABSTRACT FROM AUTHOR]

For robots to use language effectively, they need to refer to combinations of existing concepts, as well as concepts that have been directly experienced. In this paper, we introduce the term generative grounding to refer to the establishment of shared meaning for concepts referred to using relational terms. We investigated a spatial domain, which is both experienced and constructed using mobile robots with cognitive maps. The robots, called Lingodroids, established lexicons for locations, distances, and directions through structured conversations called where-are-we, how-far, what-direction, and where-is-there conversations. Distributed concept construction methods were used to create flexible concepts, based on a data structure called a distributed lexicon table. The lexicon was extended from words for locations, termed toponyms, to words for the relational terms of distances and directions. New toponyms were then learned using these relational operators. Effective grounding was tested by using the new toponyms as targets for go-to games, in which the robots independently navigated to named locations. The studies demonstrate how meanings can be extended from grounding in shared physical experiences to grounding in constructed cognitive experiences, giving the robots a language that refers to their direct experiences, and to constructed worlds that are beyond the here-and-now. [ABSTRACT FROM PUBLISHER]

Time and space are fundamental to human language and embodied cognition. In our early work we investigated how Lingodroids, robots with the ability to build their own maps, could evolve their own geopersonal spatial language. In subsequent studies we extended the framework developed for learning spatial concepts and words to learning temporal intervals. This paper considers a new aspect of time, the naming of concepts like morning, afternoon, dawn, and dusk, which are events that are part of day-night cycles, but are not defined by specific time points on a clock. Grounding of such terms refers to events and features of the diurnal cycle, such as light levels. We studied event-based time in which robots experienced day-night cycles that varied with the seasons throughout a year. Then we used meet-at tasks to demonstrate that the words learned were grounded, where the times to meet were morning and afternoon, rather than specific clock times. The studies show how words and concepts for a novel aspect of cyclic time can be grounded through experience with events rather than by times as measured by clocks or calendars. [ABSTRACT FROM PUBLISHER]

For mobile robots to communicate meaningfully about their spatial environment, they require personally constructed cognitive maps and social interactions to form languages with shared meanings. Geographic spatial concepts introduce particular problems for grounding—connecting a word to its referent in the world—because such concepts cannot be directly and solely based on sensory perceptions. In this article we investigate the grounding of geographic spatial concepts using mobile robots with cognitive maps, called Lingodroids. Languages were established through structured interactions between pairs of robots called where-are-we conversations. The robots used a novel method, termed the distributed lexicon table, to create flexible concepts. This method enabled words for locations, termed toponyms, to be grounded through experience. Their understanding of the meaning of words was demonstrated using go-to games in which the robots independently navigated to named locations. Studies in real and virtual reality worlds show that the system is effective at learning spatial language: robots learn words easily—in a single trial as children do—and the words and their meaning are sufficiently robust for use in real world tasks. [ABSTRACT FROM PUBLISHER]

An understanding of time and temporal concepts is critical for interacting with the world and with other agents in the world. What does a robot need to know to refer to the temporal aspects of events—could a robot gain a grounded understanding of “a long journey,” or “soon?” Cognitive maps constructed by individual agents from their own journey experiences have been used for grounding spatial concepts in robot languages. In this paper, we test whether a similar methodology can be applied to learning temporal concepts and an associated lexicon to answer the question “how long” did it take to complete a journey. Using evolutionary language games for specific and generic journeys, successful communication was established for concepts based on representations of time, distance, and amount of change. The studies demonstrate that a lexicon for journey duration can be grounded using a variety of concepts. Spatial and temporal terms are not identical, but the studies show that both can be learned using similar language evolution methods, and that time, distance, and change can serve as proxies for each other under noisy conditions. Effective concepts and names for duration provide a first step towards a grounded lexicon for temporal interval logic. [ABSTRACT FROM PUBLISHER]

During exponential growth of Streptococcus faecalis, the distribution of cell arrangements remains constant, but depends on the growth rate. The predominant cell arrangements are diplococci (about 60-80% of total cells) the amount of which varies only little with the growth rate. A clear correlation exists for cells growing as chains; the amount decreases from about 20% at μ=2.0 to about 6% at μ=0.45. After cessation of growth in the stationary phase, the number of diplococci and chains decreases and the number of monococci increases; after 10 h in the stationary phase, more than 50% of the cells have become monococci. The dry weight of 2.5×10 mg/cell remains constant at different growth rates, while cell size shows small differences on different growth media. Treatment of exponentially growing cultures with crystal violet or nitrofurantoin results in faster sedimentation on sucrose gradients of treated cultures compared to untreated cultures. While crystal violet effects an increased chain formation, treatment with nitrofurantoin results in an increase of the size of the individual cell. [ABSTRACT FROM AUTHOR]

The influence of microenvironment on the course of CD8+ T cell responses in vivo was investigated by injecting H-2Kb-specific T cells from donor TCR transgenlc (TCR-Tg) mice into H-2Kb-tag mice. H-2Kb expression in recipients was either ubiquitous (CBK mice) or restricted to myeloid and erythroid cells (Kβ mice). Donor T cells proliferated as extensively and acquired similar surface phenotypes in spleen of both recipient types. Thus, neither the restricted pattern of H-2Kb expression nor the significantly reduced level of H-2Kb expression by myelold cells in Kβ recipients affects the ability of the splenic microenvironment to prime T cell proliferation in vivo. However, an unsustained burst of cytolytic activity was generated rapidly in spleen of CBK recipients, whereas relatively little cytolytic activity was generated in Kβ spleen. This indicates that effector T cells were not generated efficiently in spleen of Kβ recipients even though extensive T cell proliferation was taking place in this microenvironment. Furthermore, activated donor T cells dispersed rapidly throughout primary and secondary lymphoid organs of Kβ recipients, whereas few T cells migrated from spleen in CBK recipients. Consequently, the course of CD8+ T cell responses and the anatomical distribution of activated T cells are profoundly influenced by the nature of the antigenlc microenvironment encountered in vivo. We conclude that T cells rapidly proliferate and acquire new tissue-homing characteristics but do not differentiate into cytolytic effector cells at the site of priming when they encounter myelold cells expressing low levels of antigen in vivo. [ABSTRACT FROM AUTHOR]

Immature thymocytes expressing TCRs which confer reactivity to self-MHC molecules are subject to efficient elimination as a result of negative selection. Previously, we have identified a lineage of H-2K Tg mice, CD2K-3, which fails to reject skin grafts from mice expressing H-2K even though H-2K-specrfic cytotoxlc T cells can be generated . We now show that bone marrow derived cells are responsible for tolerance induction and that tolerance is acquired, at toast in part, by negative selection in CD2K-3 mice. Thymocytes expressing two different transgenic TCR (TCR-T) clonotypes conferring reactivity to H-2K are eliminated prior to the CD8CD4 stage of differentiation in double Tg (CD2K-3×TCR-T)F mice. As in other cases where thymocytes from TCR-T mice develop in the presence of deleting ligands, large numbers of TCR CD8CD4 T cells accumulate in double Tg mice. However, these T cells fail to respond to H-2K but can be activated with immobilized anti-clonotyplc antibody. Consequently, thymocytes expressing these types of TCR molecules represent a fraction of H-2K-reactive thymocytes which are unable to mature into T cells capable of mounting H-2K-specific cytotoxic responses. Presumably, precursors of H-2K-spicific cytotoxlc T cells found in the periphery of CD2K-3 mice express a distinct repertoire of TCR molecules conferring reactivity to H-2K. We consider potential explanations to account for this discrepancy and their wider implications, including the possibility that the repertoire of thymocytea able to recognize setf-H-2Kb molecules In CD2K -3 mice is divided into distinct subsets; those which are, and those which are not, subject to negative selection. [ABSTRACT FROM PUBLISHER]

Mobile robots and animals alike must effectively navigate their environments in order to achieve their goals. For animals goal-directed navigation facilitates finding food, seeking shelter or migration; similarly robots perform goal-directed navigation to find a charging station, get out of the rain or guide a person to a destination. This similarity in tasks extends to the environment as well; increasingly, mobile robots are operating in the same underwater, ground and aerial environments that animals do. Yet despite these similarities, goal-directed navigation research in robotics and biology has proceeded largely in parallel, linked only by a small amount of interdisciplinary research spanning both areas. Most state-of-the-art robotic navigation systems employ a range of sensors, world representations and navigation algorithms that seem far removed from what we know of how animals navigate; their navigation systems are shaped by key principles of navigation in 'real-world' environments including dealing with uncertainty in sensing, landmark observation and world modelling. By contrast, biomimetic animal navigation models produce plausible animal navigation behaviour in a range of laboratory experimental navigation paradigms, typically without addressing many of these robotic navigation principles. In this paper, we attempt to link robotics and biology by reviewing the current state of the art in conventional and biomimetic goal-directed navigation models, focusing on the key principles of goal-oriented robotic navigation and the extent to which these principles have been adapted by biomimetic navigation models and why., (© 2014 The Author(s) Published by the Royal Society. All rights reserved.)