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An essential measure of autonomy in assistive service robots is adaptivity to the various contexts of human-oriented tasks, which are subject to subtle variations in task parameters that determine optimal behaviour. In this work, we propose an apprenticeship learning approach to achieving context-aware action generalization on the task of robot-to-human object hand-over. The procedure combines learning from demonstration and reinforcement learning: a robot first imitates a demonstrator’s execution of the task and then learns contextualized variants of the demonstrated action through experience. We use dynamic movement primitives as compact motion representations, and a model-based C-REPS algorithm for learning policies that can specify hand-over position, conditioned on context variables. Policies are learned using simulated task executions, before transferring them to the robot and evaluating emergent behaviours. We additionally conduct a user study involving participants assuming different postures and receiving an object from a robot, which executes hand-overs by either imitating a demonstrated motion, or adapting its motion to hand-over positions suggested by the learned policy. The results confirm the hypothesized improvements in the robot’s perceived behaviour when it is context-aware and adaptive, and provide useful insights that can inform future developments.
Entrepreneurship education serves a conduit for new venture creation as it provides the knowledge and skills needed to increase the self-efficacy of individuals to start and run new businesses and to grow existing ones. This study, therefore, sought to assess the relationship between the approaches to the teaching of entrepreneur-ship and entrepreneurial intention on a cohort of 292 respondents consisting of students who have studied entrepreneurship in three selected Universities. A structured questionnaire was used to obtain data randomly from students. The canonical correlation results indicate that education for and through entrepreneurship is the best approach to promoting entrepreneurial intensity among University students, if the aim of teaching entrepreneur-ship is to promote start-up activities. The findings provide valuable insights for institutions of higher learning and policy makers in Ghana with respect to the appropriate methodologies to be adopted in the teaching of entrepreneurship in our universities.
Robust Indoor Localization Using Optimal Fusion Filter For Sensors And Map Layout Information
(2014)
This paper presents the b-it-bots RoboCup@Work team and its current hardware and functional architecture for the KUKA youBot robot.We describe the underlying software framework and the developed capabilities required for operating in industrial environments including features such as reliable and precise navigation, flexible manipulation and robust object recognition.
Despite perfect functioning of its internal components, a robot can be unsuccessful in performing its tasks because of unforeseen situations. These situations occur when the behavior of the objects in the robot’s environment deviates from its expected values. For robots, such deviations are exhibited in the form of unknown external faults which prohibit them from performing their tasks successfully. In this work we propose to use naive physics knowledge to reason about such faults in the robotics domain. We propose an approach that uses naive physics concepts to find information about the situations which result in a detected unknown fault. The naive physics knowledge is represented by the physical properties of objects which are formalized in a logical framework. The proposed approach applies a qualitative version of physical laws to these properties for reasoning about the detected fault. By interpreting the reasoning results the robot finds the information about the situations which can cause the fault. We apply the proposed approach to the scenarios in which a robot performs manipulation tasks of picking and placing objects. Results of this application show that naive physics holds great promise for reasoning about unknown ex- ternal faults in robotics.
Mergers and acquisitions take place all over the world and in many industries, typically motivated by corporate politics. While IT management is often not involved in the decision-making, it has to solve a wide range of problems in the post-merger phase. Indeed, merging two or more companies implies not only merging their core businesses, but also creating a new and efficiently integrated IT organisation from the individual ones, since persistence of the current IT organisations usually does not make sense. In addition, corporate management frequently imposes constraints, e.g., cost reductions, on the IT infrastructure. The principal critical success factor when merging IT organisations is the uninterrupted operation of the IT business, because a service gap is neither acceptable for in-house functional departments nor for external customers. Therefore, the IT rebuilding phase has to focus on IT services that facilitate the processes of functional departments, support processes, and processes of customers and suppliers, so that any transformation work is transparent to internal and external customers. In this article we describe a real-world but anonymous case study. Our goals are to highlight the points important for merging IT organisations, and to help decision-makers, particularly in the areas of IT organisation and IT personnel. We focus on the arising organisational and non-technical issues from a management perspective, i.e., the CIO's view, and provide checklists intended to help IT managers to address the most pressing issues. To assist CIOs surviving in the post merger phase, we give check lists for merging IT organisations, check lists for merging IT human resources, check lists for IT budgets and reporting, and assess activities in a merger scenario. IT hardware, software and IT infrastructure as well as running IT projects are not considered in this paper.