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

Interactive exploration of historic information via gesture recognition

Developers of interactive exhibits often struggle to �nd appropriate input devices that enable intuitive control, permitting the visitors to engage e�ectively with the content. Recently motion sensing input devices like the Microsoft Kinect or Panasonic D-Imager have become available enabling gesture based control of computer systems. These devices present an attractive input device for exhibits since the user can interact with their hands and they are not required to physically touch any part of the system. In this thesis we investigate techniques to enable the raw data coming from these types of devices to be used to control an interactive exhibit. Object recognition and tracking techniques are used to analyse the user's hand where movement and clicks are processed. To show the e�ectiveness of the techniques the gesture system is used to control an interactive system designed to inform the public about iconic buildings in the centre of Norwich, UK. We evaluate two methods of making selections in the test environment. At the time of experimentation the technologies were relatively new to the image processing environment. As a result of the research presented in this thesis, the techniques and methods used have been detailed and published [3] at the VSMM (Virtual Systems and Multimedia 2012) conference with the intention of further forwarding the area

Geometric data for testing implementations of point reduction algorithms : case study using Mapshaper v 0.2.28 and previous versions

There are several open source and commercial implementations of the Visvalingam algorithm for line generalisation. The algorithm provides scope for implementation-specific interpretations, with different outcomes. This is inevitable and sometimes necessary and, they do not imply that an implementation is flawed. The only restriction is that the output must not be so inconsistent with the intent of the algorithm that it becomes inappropriate. The aim of this paper is to place the algorithm within the literature, and demonstrate the value of the teragon-test for evaluating the appropriateness of implementations; Mapshaper v 0.2.28 and earlier versions are used for illustrative purposes. Data pertaining to natural features, such as coastlines, are insufficient for establishing whether deviations in output are significant. The teragon-test produced an unexpected loss of symmetry from both the Visvalingam and Douglas-Peucker options, making the tested versions unsuitable for some applications outside of cartography. This paper describes the causes, and discusses their implications. Mapshaper 0.3.17 passes the teragon test. Other developers and users should check their implementations using contrived geometric data, such as the teragon data provided in this paper, especially when the source code is not available. The teragon-test is also useful for evaluating other point reduction algorithms