Past, Present, and Future of Simultaneous Localization And Mapping: Towards the Robust-Perception Age

Simultaneous Localization and Mapping (SLAM)consists in the concurrent construction of a model of the environment (the map), and the estimation of the state of the robot moving within it. The SLAM community has made astonishing progress over the last 30 years, enabling large-scale real-world applications, and witnessing a steady transition of this technology to industry. We survey the current state of SLAM. We start by presenting what is now the de-facto standard formulation for SLAM. We then review related work, covering a broad set of topics including robustness and scalability in long-term mapping, metric and semantic representations for mapping, theoretical performance guarantees, active SLAM and exploration, and other new frontiers. This paper simultaneously serves as a position paper and tutorial to those who are users of SLAM. By looking at the published research with a critical eye, we delineate open challenges and new research issues, that still deserve careful scientific investigation. The paper also contains the authors' take on two questions that often animate discussions during robotics conferences: Do robots need SLAM? and Is SLAM solved

Vividness, Consciousness, and Mental Imagery

Today in many studies, mental images are still either treated as conscious by definition, or as empirical operations implicit to completing some type of task, such as the measurement of reaction time in mental rotation, an underlying mental image is assumed, but there is no direct determination of whether it is conscious or not. The vividness of mental images is a potentially helpful construct which may be suitable, as it may correspond to consciousness or aspects of the consciousness of images. In this context, a complicating factor seems to be the surprising variety in what is meant by the term vividness or how it is used or theorized. To fill some of the gaps, the goal of the present Special Issue is to create a publication outlet where authors can fully explore through sound research the missing theoretical and empirical links between vividness, consciousness and mental imagery across disciplines, neuroscience, psychology, philosophy, cognitive science, to mention the most obvious ones, as well as transdisciplinary methodological (single, combined, or multiple) approaches

Comparative social capital: Networks of entrepreneurs and investors in China and Russia

Most studies on entrepreneurs’ networks incorporate social capital and networks as independent variables that affect entrepreneurs’ actions and its outcomes. By contrast, this article examines social capital of the Chinese and Russian entrepreneurs and venture capitalists as dependent variables, and it examines entrepreneurs’ social capital from the perspectives of institutional theory and cultural theory. The empirical data are composed of structured telephone interviews with 159 software entrepreneurs, and the data of 124 venture capital decisions in Beijing and Moscow. The study found that social networks of the Chinese entrepreneurs are smaller in size, denser in structure, and more homogeneous in composition compared to networks of the Russian entrepreneurs due to the institutional and cultural differences between the two countries. Furthermore, the study revealed that dyadic (two-person) ties are stronger and interpersonal trust is greater in China than in Russia. The research and practical implications are discussed.http://deepblue.lib.umich.edu/bitstream/2027.42/40169/3/wp783.pd

Comparative social capital: Networks of entrepreneurs and investors in China and Russia

Most studies on entrepreneurs’ networks incorporate social capital and networks as independent variables that affect entrepreneurs’ actions and its outcomes. By contrast, this article examines social capital of the Chinese and Russian entrepreneurs and venture capitalists as dependent variables, and it examines entrepreneurs’ social capital from the perspectives of institutional theory and cultural theory. The empirical data are composed of structured telephone interviews with 159 software entrepreneurs, and the data of 124 venture capital decisions in Beijing and Moscow. The study found that social networks of the Chinese entrepreneurs are smaller in size, denser in structure, and more homogeneous in composition compared to networks of the Russian entrepreneurs due to the institutional and cultural differences between the two countries. Furthermore, the study revealed that dyadic (two-person) ties are stronger and interpersonal trust is greater in China than in Russia. The research and practical implications are discussed.Social capital, entrepreneurs, venture capitalists, China and Russia.

Entrepreneurship and networked collaboration: synergetic innovation, knowledge and uncertainty.

This conceptual paper examines the nature of entrepreneurship in innovation processes in time of crisis. Crisis is a time of heightened uncertainty, manifested as increased ambiguity about what knowledge is available yet necessary for innovation. It is argued here that connecting this diverse knowledge is essential for innovation and that this is a key entrepreneurial process. Whilst this point is established in the literature, there is perhaps a gap in understanding how such knowledge is entrepreneurially applied. In systems-based views of innovation there seems to be an assumption that knowledge synthesis just happens as a natural occurrence. Reviewing and synthesising disparate literatures, this paper argues that stocks of knowledge are not, in themselves, sufficient to produce innovation. Instead, entrepreneurial agency is required to collaborate, connect and to combine these knowledge stocks to produce innovation. The paper contributes to understanding and theory by demonstrating how and why this 'social' connecting is a critical element of the entrepreneurial role and a crucial part of innovation

Geometric Modeling and Recognition of Elongated Regions in Images.

The goal of this research is the recovery of elongated shapes from patterns of local features extracted from images. A generic geometric model-based approach is developed based on general concepts of 2-d form and structure. This is an intermediate-level analysis that is computed from groupings and decompositions of related low-level features. Axial representations are used to describe the shapes of image objects having the property of elongatedness. Curve-fitting is shown to compute axial sequences of the points in an elongated cluster. Script-clustering is performed about a parametric smooth curve to extract elongated partitions of the data incorporating constraints of point connectivity, curve alignment, and strip boundedness. A thresholded version of the Gabriel Graph (GG) is shown to offer most of the information needed from the Minimum Spanning Tree (MST) and Delauney Triangulation (DT), while being easily computable from finite neighborhood operations. An iterative curve-fitting method, that is placed in the general framework of Random Sample Consensus (RANSAC) model-fitting, is used to extract maximal partitions. The method is developed for general parametric curve-fitting over discrete point patterns. A complete structural analysis is presented for the recovery of elongated regions from multispectral classification. A region analysis is shown to be superior to an edge-based analysis in the early stages of recognition. First, the curve-fitting method is used to recover the linear components of complex object regions. The rough locations to start and end a region delineation are then detected by decomposing extracted linear shape clusters with a circular operator. Experimental results are shown for a variety of images, with the main result being an analysis of a high-resolution aerial image of a suburban road network. Analyses of printed circuit board patterns and a LANDSAT river image are also given. The generality of the curve-fitting approach is shown by these results and by its possible applications to other described image analysis problems

Aerospace Medicine and Biology: A continuing bibliography (supplement 160)

This bibliography lists 166 reports, articles, and other documents introduced into the NASA scientific and technical information system in October 1976

Human Dimensions of the Ecosystem Approach to Fisheries: An Overview of Context, Concepts, Tools and Methods

This document aims to provide a better understanding of the role of the economic, institutional and sociocultural components within the ecosystem approach to fisheries (EAF) process and to examine some potential methods and approaches that may facilitate the adoption of EAF management. It explores both the human context for the ecosystem approach to fisheries and the human dimensions involved in implementing the EAF. For the former, the report provides background material essential to understand prior to embarking on EAF initiatives, including an understanding of key concepts and issues, of the valuation of aquatic ecosystems socially, culturally and economically, and of the many policy, legal, institutional, social and economic considerations relevant to the EAF. With respect to facilitating EAF implementation, the report deals with a series of specific aspects: (1) determining the boundaries, scale and scope of the EAF; (2) assessing the various benefits and costs involved, seen from social, economic, ecological and management perspectives; (3) utilizing appropriate decision-making tools in EAF; (4) creating and/or adopting internal incentives and institutional arrangements to promote, facilitate and fund the adoption of EAF management; and (5) finding suitable external (non-fisheries) approaches for financing EAF implementation

Perceptual Organization

Perceiving the world of real objects seems so easy that it is difficult to grasp just how complicated it is. Not only do we need to construct the objects quickly, the objects keep changing even though we think of them as having a consistent, independent existence (Feldman, 2003). Yet, we usually get it right, there are few failures. We can perceive a tree in a blinding snowstorm, a deer bounding across a tree line, dodge a snowball, catch a baseball, detect the crack of a branch breaking in a strong windstorm amidst the rustling of trees, predict the sounds of a dripping faucet, or track a street musician strolling down the road