25,368 research outputs found
Technology assessment of advanced automation for space missions
Six general classes of technology requirements derived during the mission definition phase of the study were identified as having maximum importance and urgency, including autonomous world model based information systems, learning and hypothesis formation, natural language and other man-machine communication, space manufacturing, teleoperators and robot systems, and computer science and technology
Intelligent systems in manufacturing: current developments and future prospects
Global competition and rapidly changing customer requirements are demanding increasing changes in manufacturing environments. Enterprises are required to constantly redesign their products and continuously reconfigure their manufacturing systems. Traditional approaches to manufacturing systems do not fully satisfy this new situation. Many authors have proposed that artificial intelligence will bring the flexibility and efficiency needed by manufacturing systems. This paper is a review of artificial intelligence techniques used in manufacturing systems. The paper first defines the components of a simplified intelligent manufacturing systems (IMS), the different Artificial Intelligence (AI) techniques to be considered and then shows how these AI techniques are used for the components of IMS
Action Sequencing Using Visual Permutations
Humans can easily reason about the sequence of high level actions needed to
complete tasks, but it is particularly difficult to instil this ability in
robots trained from relatively few examples. This work considers the task of
neural action sequencing conditioned on a single reference visual state. This
task is extremely challenging as it is not only subject to the significant
combinatorial complexity that arises from large action sets, but also requires
a model that can perform some form of symbol grounding, mapping high
dimensional input data to actions, while reasoning about action relationships.
This paper takes a permutation perspective and argues that action sequencing
benefits from the ability to reason about both permutations and ordering
concepts. Empirical analysis shows that neural models trained with latent
permutations outperform standard neural architectures in constrained action
sequencing tasks. Results also show that action sequencing using visual
permutations is an effective mechanism to initialise and speed up traditional
planning techniques and successfully scales to far greater action set sizes
than models considered previously.Comment: This paper has been accepted for publication at IEEE RA-
Planning robot actions under position and shape uncertainty
Geometric uncertainty may cause various failures during the execution of a robot control program. Avoiding such failures makes it necessary to reason about the effects of uncertainty in order to implement robust strategies. Researchers first point out that a manipulation program has to be faced with two types of uncertainty: those that might be locally processed using appropriate sensor based motions, and those that require a more global processing leading to insert new sensing operations. Then, they briefly describe how they solved the two related problems in the SHARP system: how to automatically synthesize a fine motion strategy allowing the robot to progressively achieve a given assembly relation despite position uncertainty, and how to represent uncertainty and to determine the points where a given manipulation program might fail
More than a cognitive experience: unfamiliarity, invalidation, and emotion in organizational learning
Literature on organizational learning (OL) lacks an integrative framework that captures the emotions involved as OL proceeds. Drawing on personal construct theory, we suggest that organizations learn where their members reconstrue meaning around questions of strategic significance for the organization. In this 5-year study of an electronics company, we explore the way in which emotions change as members perceive progress or a lack of progress around strategic themes. Our framework also takes into account whether OL involves experiences that are familiar or unfamiliar and the implications for emotions. We detected similar patterns of emotion arising over time for three different themes in our data, thereby adding to OL perspectives that are predominantly cognitive in orientation
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