User interface and function library for ground robot navigation

Master's Project (M.S.) University of Alaska Fairbanks, 2017A web application user interface and function library were developed to enable a user to program a ground robot to navigate autonomously. The user interface includes modules for generating a grid of obstacles from a map image, setting waypoints for a path through the map, and programming a robot in a code editor to navigate autonomously. The algorithm used for navigation is an A* algorithm modified with obstacle padding to accommodate the width of the robot and path smoothing to simplify the paths. The user interface and functions were designed to be simple so that users without technical backgrounds can use them, and by doing so they can engage in the development process of human-centered robots. The navigation functions were successful in finding paths in test configurations, and the performance of the algorithms was fast enough for user interactivity up to a certain limit of grid cell sizes

User interface and function library for ground robot navigation

Master's Project (M.S.) University of Alaska Fairbanks, 2017A web application user interface and function library were developed to enable a user to program a ground robot to navigate autonomously. The user interface includes modules for generating a grid of obstacles from a map image, setting waypoints for a path through the map, and programming a robot in a code editor to navigate autonomously. The algorithm used for navigation is an A* algorithm modified with obstacle padding to accommodate the width of the robot and path smoothing to simplify the paths. The user interface and functions were designed to be simple so that users without technical backgrounds can use them, and by doing so they can engage in the development process of human-centered robots. The navigation functions were successful in finding paths in test configurations, and the performance of the algorithms was fast enough for user interactivity up to a certain limit of grid cell sizes

Toward a unified PNT, Part 1: Complexity and context: Key challenges of multisensor positioning

The next generation of navigation and positioning systems must provide greater accuracy and reliability in a range of challenging environments to meet the needs of a variety of mission-critical applications. No single navigation technology is robust enough to meet these requirements on its own, so a multisensor solution is required. Known environmental features, such as signs, buildings, terrain height variation, and magnetic anomalies, may or may not be available for positioning. The system could be stationary, carried by a pedestrian, or on any type of land, sea, or air vehicle. Furthermore, for many applications, the environment and host behavior are subject to change. A multi-sensor solution is thus required. The expert knowledge problem is compounded by the fact that different modules in an integrated navigation system are often supplied by different organizations, who may be reluctant to share necessary design information if this is considered to be intellectual property that must be protected

Fast processing of grid maps using graphical multiprocessors

Grid mapping is a very common technique used in mobile robotics to build a continuous 2D representation of the environment useful for navigation purposes. Although its computation is quite simple and fast, this algorithm uses the hypothesis of a known robot pose. In practice, this can require the re-computation of the map when the estimated robot poses change, as when a loop closure is detected. This paper presents a parallelization of a reference implementation of the grid mapping algorithm, which is suitable to be fully run on a graphics card showing huge processing speedups (up to 50×) while fully releasing the main processor, which can be very useful for many Simultaneous Localization and Mapping algorithms

In-Network View Synthesis for Interactive Multiview Video Systems

To enable Interactive multiview video systems with a minimum view-switching delay, multiple camera views are sent to the users, which are used as reference images to synthesize additional virtual views via depth-image-based rendering. In practice, bandwidth constraints may however restrict the number of reference views sent to clients per time unit, which may in turn limit the quality of the synthesized viewpoints. We argue that the reference view selection should ideally be performed close to the users, and we study the problem of in-network reference view synthesis such that the navigation quality is maximized at the clients. We consider a distributed cloud network architecture where data stored in a main cloud is delivered to end users with the help of cloudlets, i.e., resource-rich proxies close to the users. In order to satisfy last-hop bandwidth constraints from the cloudlet to the users, a cloudlet re-samples viewpoints of the 3D scene into a discrete set of views (combination of received camera views and virtual views synthesized) to be used as reference for the synthesis of additional virtual views at the client. This in-network synthesis leads to better viewpoint sampling given a bandwidth constraint compared to simple selection of camera views, but it may however carry a distortion penalty in the cloudlet-synthesized reference views. We therefore cast a new reference view selection problem where the best subset of views is defined as the one minimizing the distortion over a view navigation window defined by the user under some transmission bandwidth constraints. We show that the view selection problem is NP-hard, and propose an effective polynomial time algorithm using dynamic programming to solve the optimization problem. Simulation results finally confirm the performance gain offered by virtual view synthesis in the network