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 and consider future directions. 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?

/pdf/past-present-and-future-of-simultaneous-localization-and-27i1pn9khc.pdf

Past, Present, and Future of Simultaneous Localization and Mapping: Toward 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?

/pdf/past-present-and-future-of-simultaneous-localization-and-dhljw0akg5.pdf

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

A survey on coverage path planning for robotics

A hierarchy of low-dimensional Galerkin models is proposed for the viscous, incompressible flow around a circular cylinder building on the pioneering works of Stuart (1958), Deane et al. (1991), and Ma & Karniadakis (2002). The empirical Galerkin model is based on an eight-dimensional Karhunen–Loeve decomposition of a numerical simulation and incorporates a new ‘shift-mode’ representing the mean-field correction. The inclusion of the shift-mode significantly improves the resolution of the transient dynamics from the onset of vortex shedding to the periodic von Karman vortex street. In addition, the Reynolds-number dependence of the flow can be described with good accuracy. The inclusion of stability eigenmodes further enhances the accuracy of fluctuation dynamics. Mathematical and physical system reduction approaches lead to invariant-manifold and to mean-field models, respectively. The corresponding two-dimensional dynamical systems are further reduced to the Landau amplitude equation.

/pdf/a-hierarchy-of-low-dimensional-models-for-the-transient-and-mndofad8te.pdf

A hierarchy of low-dimensional models for the transient and post-transient cylinder wake

Preface Introduction 1. Fluid field equations and modal analysis in rigid containers 2. Linear forced sloshing 3. Viscous damping and sloshing suppression devices 4. Weakly nonlinear lateral sloshing 5. Equivalent mechanical models 6. Parametric sloshing (Faraday's waves) 7. Dynamics of liquid sloshing impact 8. Linear interaction of liquid sloshing with elastic containers 9. Nonlinear interaction under external and parametric excitations 10. Interactions with support structures and tuned sloshing absorbers 11. Dynamics of rotating fluids 12. Microgravity sloshing dynamics Bibliography Index.

/pdf/liquid-sloshing-dynamics-4apevf1yp2.pdf

Liquid Sloshing Dynamics

Autonomous underwater vehicle (AUV) navigation and localization in underwater environments is particularly challenging due to the rapid attenuation of Global Positioning System (GPS) and radio-frequency signals. Underwater communications are low bandwidth and unreliable, and there is no access to a global positioning system. Past approaches to solve the AUV localization problem have employed expensive inertial sensors, used installed beacons in the region of interest, or required periodic surfacing of the AUV. While these methods are useful, their performance is fundamentally limited. Advances in underwater communications and the application of simultaneous localization and mapping (SLAM) technology to the underwater realm have yielded new possibilities in the field. This paper presents a review of the state of the art of AUV navigation and localization, as well as a description of some of the more commonly used methods. In addition, we highlight areas of future research potential.

/pdf/auv-navigation-and-localization-a-review-2aaowbjv0i.pdf

AUV Navigation and Localization: A Review

Simultaneous localization and mapping SLAM in unknown GPS-denied environments is a major challenge for researchers in the field of mobile robotics. Many solutions for single-robot SLAM exist; however, moving to a platform of multiple robots adds many challenges to the existing problems. This paper reviews state-of-the-art multiple-robot systems, with a major focus on multiple-robot SLAM. Various issues and problems in multiple-robot SLAM are introduced, current solutions for these problems are reviewed, and their advantages and disadvantages are discussed.

/pdf/multiple-robot-simultaneous-localization-and-mapping-a-qeqtr8xeje.pdf

Multiple-Robot Simultaneous Localization and Mapping: A Review

At present, autonomous underwater vehicle (AUV) mine countermeasure (MCM) surveys are normally preplanned by operators using ladder or zig-zag paths. Such surveys are conducted with side-looking sonar sensors whose performance is dependent on environmental, target, sensor, and AUV platform parameters. It is difficult to obtain precise knowledge of all of these parameters to be able to design optimal mission plans offline. This research represents the first known sensor driven online approach to seabed coverage for MCM. A method is presented where paths are planned using a multiobjective optimization. Information theory is combined with a new concept coined branch entropy based on a hexagonal cell decomposition. The result is a planning algorithm that not only produces shorter paths than conventional means, but is also capable of accounting for environmental factors detected in situ. Hardware-in-the-loop simulations and in water trials conducted on the IVER2 AUV show the effectiveness of the proposed method.

http://people.csail.mit.edu/lpaull/publications/Paull_TMECH_2012.pdf

Sensor-Driven Online Coverage Planning for Autonomous Underwater Vehicles

Multi-robot deployments have the potential for completing tasks more efficiently. For example, in simultaneous localization and mapping (SLAM), robots can better localize themselves and the map if they can share measurements of each other (direct encounters) and of commonly observed parts of the map (indirect encounters). However, performance is contingent on the quality of the communications channel. In the underwater scenario, communicating over any appreciable distance is achieved using acoustics which is low-bandwidth, slow, and unreliable, making cooperative operations very challenging. In this paper, we present a framework for cooperative SLAM (C-SLAM) for multiple autonomous underwater vehicles (AUVs) communicating only through acoustics. We develop a novel graph-based C-SLAM algorithm that is able to (optimally) generate communication packets whose size scales linearly with the number of observed features since the last successful transmission, constantly with the number of vehicles in the collective, and does not grow with time even the case of dropped packets, which are common. As a result, AUVs can bound their localization error without the need for pre-installed beacons or surfacing for GPS fixes during navigation, leading to significant reduction in time required to complete missions. The proposed algorithm is validated through realistic marine vehicle and acoustic communication simulations.

/pdf/communication-constrained-multi-auv-cooperative-slam-200kdsy1ei.pdf

Communication-constrained multi-AUV cooperative SLAM

This paper presents the development of a nonlinear quadrotor simulation framework together with a nonlinear controller. The quadrotor stabilization and navigation problems are tackled using a nested loops control architecture. A nonlinear Backstepping controller is implemented for the inner stabilization loop. It asymptotically tracks reference attitude, altitude and heading trajectories. The outer loop controller generates the reference trajectories for the inner loop controller to reach the desired waypoint. To ensure boundedness of the reference trajectories, a PD controller with a saturation function is used for the outer loop. Due to the complexity involved in controller development and testing, a simulation framework has been developed. It is based on the Gazebo 3D robotics simulator and the Open Dynamics Engine (ODE) library. The framework can effectively facilitate the development and validation of controllers. It has been released and is available at Gazebo quadrotor simulator (2012).

/pdf/control-and-navigation-framework-for-quadrotor-helicopters-16pgnizbc7.pdf

Mae Seto

Papers

AUV Navigation and Localization: A Review

Multiple-Robot Simultaneous Localization and Mapping: A Review

Sensor-Driven Online Coverage Planning for Autonomous Underwater Vehicles

Communication-constrained multi-AUV cooperative SLAM

Control and Navigation Framework for Quadrotor Helicopters