Effects of hyperlinks on navigation in virtual environments

Hyperlinks introduce discontinuities of movement to 3-D virtual environments (VEs). Nine independent attributes of hyperlinks are defined and their likely effects on navigation in VEs are discussed. Four experiments are described in which participants repeatedly navigated VEs that were either conventional (i.e. obeyed the laws of Euclidean space), or contained hyperlinks. Participants learned spatial knowledge slowly in both types of environment, echoing the findings of previous studies that used conventional VEs. The detrimental effects on participants' spatial knowledge of using hyperlinks for movement were reduced when a time-delay was introduced, but participants still developed less accurate knowledge than they did in the conventional VEs. Visual continuity had a greater influence on participants' rate of learning than continuity of movement, and participants were able to exploit hyperlinks that connected together disparate regions of a VE to reduce travel time

Real-time 2D–3D door detection and state classification on a low-power device

In this paper, we propose three methods for door state classifcation with the goal to improve robot navigation in indoor spaces. These methods were also developed to be used in other areas and applications since they are not limited to door detection as other related works are. Our methods work ofine, in low-powered computers as the Jetson Nano, in real-time with the ability to diferentiate between open, closed and semi-open doors. We use the 3D object classifcation, PointNet, real-time semantic segmentation algorithms such as, FastFCN, FC-HarDNet, SegNet and BiSeNet, the object detection algorithm, DetectNet and 2D object classifcation networks, AlexNet and GoogleNet. We built a 3D and RGB door dataset with images from several indoor environments using a 3D Realsense camera D435. This dataset is freely available online. All methods are analysed taking into account their accuracy and the speed of the algorithm in a low powered computer. We conclude that it is possible to have a door classifcation algorithm running in real-time on a low-power device.info:eu-repo/semantics/publishedVersio

Automatic Mapping of NES Games with Mappy

Game maps are useful for human players, general-game-playing agents, and data-driven procedural content generation. These maps are generally made by hand-assembling manually-created screenshots of game levels. Besides being tedious and error-prone, this approach requires additional effort for each new game and level to be mapped. The results can still be hard for humans or computational systems to make use of, privileging visual appearance over semantic information. We describe a software system, Mappy, that produces a good approximation of a linked map of rooms given a Nintendo Entertainment System game program and a sequence of button inputs exploring its world. In addition to visual maps, Mappy outputs grids of tiles (and how they change over time), positions of non-tile objects, clusters of similar rooms that might in fact be the same room, and a set of links between these rooms. We believe this is a necessary step towards developing larger corpora of high-quality semantically-annotated maps for PCG via machine learning and other applications.Comment: 9 pages, 7 figures. Appearing at Procedural Content Generation Workshop 201