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

String Phenomenology: Past, Present and Future Perspectives

The observation of a scalar resonance at the LHC, compatible with perturbative electroweak symmetry breaking, reinforces the Standard Model parameterisation of all subatomic data. The logarithmic evolution of the SM gauge and matter parameters suggests that this parameterisation remains viable up to the Planck scale, where gravitational effects are of comparable strength. String theory provides a perturbatively consistent scheme to explore how the parameters of the Standard Model may be determined from a theory of quantum gravity. The free fermionic heterotic string models provide concrete examples of exact string solutions that reproduce the spectrum of the Minimal Supersymmetric Standard Model. Contemporary studies entail the development of methods to classify large classes of models. This led to the discovery of exophobic heterotic-string vacua and the observation of spinor-vector duality, which provides an insight to the global structure of the space of (2,0) heterotic-string vacua. Future directions entail the study of the role of the massive string states in these models and their incorporation in cosmological scenarios. A complementary direction is the formulation of quantum gravity from the principle of manifest phase space duality and the equivalence postulate of quantum mechanics, which suggest that space is compact. The compactness of space, which implies intrinsic regularisation, may be tightly related to the intrinsic finite length scale, implied by string phenomenology.Comment: 35 pages. No figures. To appear in the special volume edited by Gerald Cleaver on "Particle Physics and Quantum Gravity Implications for Cosmology". Based on talk presented at the 2012 CERN Summer Institute on String Phenomenolog

A PARTAN-Accelerated Frank-Wolfe Algorithm for Large-Scale SVM Classification

Frank-Wolfe algorithms have recently regained the attention of the Machine Learning community. Their solid theoretical properties and sparsity guarantees make them a suitable choice for a wide range of problems in this field. In addition, several variants of the basic procedure exist that improve its theoretical properties and practical performance. In this paper, we investigate the application of some of these techniques to Machine Learning, focusing in particular on a Parallel Tangent (PARTAN) variant of the FW algorithm that has not been previously suggested or studied for this type of problems. We provide experiments both in a standard setting and using a stochastic speed-up technique, showing that the considered algorithms obtain promising results on several medium and large-scale benchmark datasets for SVM classification

T-duality of NSR superstring: The worldsheet perspective

We formulate target space duality symmetry of NSR superstring from the perspectives of worldsheet. The worldsheet action is presented in the superspace formalism in the presence of massless backgrounds. We start from a ${\hat D}$-dimensional target space worldsheet action and compactify the theory on a d-dimensional torus, $T^d$. It is assumed that the backgrounds are independent of compact (super)coordinates. We adopt the formalism of our earlier work to introduce dual supercoordinates along compact directions and introduce the corresponding dual backgrounds. It is demonstrated that combined equations of motion of the two sets of coordinates can be expressed in a manifestly $O(d,d)$ covariant form analogous to the equations of motions for closed bosonic string derived by us. Furthermore, we show that the vertex operators associated with excited massive levels of NSR string can be expressed in an $O(d,d)$ invariant form generalizing earlier result for closed bosonic string.Comment: 21 page

Quantum Fluctuations and the Unruh Effect in Strongly-Coupled Conformal Field Theories

Through the AdS/CFT correspondence, we study a uniformly accelerated quark in the vacuum of strongly-coupled conformal field theories in various dimensions, and determine the resulting stochastic fluctuations of the quark trajectory. From the perspective of an inertial observer, these are quantum fluctuations induced by the gluonic radiation emitted by the accelerated quark. From the point of view of the quark itself, they originate from the thermal medium predicted by the Unruh effect. We scrutinize the relation between these two descriptions in the gravity side of the correspondence, and show in particular that upon transforming the conformal field theory from Rindler space to the open Einstein universe, the acceleration horizon disappears from the boundary theory but is preserved in the bulk. This transformation allows us to directly connect our calculation of radiation-induced fluctuations in vacuum with the analysis by de Boer et al. of the Brownian motion of a quark that is on average static within a thermal medium. Combining this same bulk transformation with previous results of Emparan, we are also able to compute the stress-energy tensor of the Unruh thermal medium.Comment: 1+31 pages; v2: reference adde

Strong Coupling Fixed Points of Current Interactions and Disordered Fermions in 2D

The all-orders beta function is used to study disordered Dirac fermions in 2D. The generic strong coupling fixed `points' of anisotropic current-current interactions at large distances are actually isotropic manifolds corresponding to subalgebras of the maximal current algebra at short distances. The IR theories are argued to be current algebra cosets. We illustrate this with the simple example of anisotropic su(2), which is the physics of Kosterlitz-Thouless transitions. We work out the phase diagram for the Chalker-Coddington network model which is in the universality class of the integer Quantum Hall transition. One massless phase is in the universality class of dense polymers.Comment: published version (Phys. Rev. B

Recurrence networks - A novel paradigm for nonlinear time series analysis

This paper presents a new approach for analysing structural properties of time series from complex systems. Starting from the concept of recurrences in phase space, the recurrence matrix of a time series is interpreted as the adjacency matrix of an associated complex network which links different points in time if the evolution of the considered states is very similar. A critical comparison of these recurrence networks with similar existing techniques is presented, revealing strong conceptual benefits of the new approach which can be considered as a unifying framework for transforming time series into complex networks that also includes other methods as special cases. It is demonstrated that there are fundamental relationships between the topological properties of recurrence networks and the statistical properties of the phase space density of the underlying dynamical system. Hence, the network description yields new quantitative characteristics of the dynamical complexity of a time series, which substantially complement existing measures of recurrence quantification analysis

Optical Flow Guided Feature: A Fast and Robust Motion Representation for Video Action Recognition

Motion representation plays a vital role in human action recognition in videos. In this study, we introduce a novel compact motion representation for video action recognition, named Optical Flow guided Feature (OFF), which enables the network to distill temporal information through a fast and robust approach. The OFF is derived from the definition of optical flow and is orthogonal to the optical flow. The derivation also provides theoretical support for using the difference between two frames. By directly calculating pixel-wise spatiotemporal gradients of the deep feature maps, the OFF could be embedded in any existing CNN based video action recognition framework with only a slight additional cost. It enables the CNN to extract spatiotemporal information, especially the temporal information between frames simultaneously. This simple but powerful idea is validated by experimental results. The network with OFF fed only by RGB inputs achieves a competitive accuracy of 93.3% on UCF-101, which is comparable with the result obtained by two streams (RGB and optical flow), but is 15 times faster in speed. Experimental results also show that OFF is complementary to other motion modalities such as optical flow. When the proposed method is plugged into the state-of-the-art video action recognition framework, it has 96:0% and 74:2% accuracy on UCF-101 and HMDB-51 respectively. The code for this project is available at https://github.com/kevin-ssy/Optical-Flow-Guided-Feature.Comment: CVPR 2018. code available at https://github.com/kevin-ssy/Optical-Flow-Guided-Featur