## 2 Related Work  
To date, several approaches for BVI people's navigation have been tested [3]. According to the objectives pursued, the requirements of the human-machine interface vary. The first distinction can be made between those that focus on assisting the user in orientation and/or mobility tasks. Although there is no standard definition of these terms, in the literature 'orientation' or 'wayfinding' relates to the ability to know and continuously update one's own position, and moving in the environment in relation to a destination [4]. Conversely,'mobility' relates to \"immediate responses to environmental features\" [5], involving the \"detection and avoidance of obstacles or drop-offs in the path of travel\" [4]. Linguistic-based interfaces are the most extended for orientation purposes. This could be appreciated in currently available smartphone applications such as WayFindr [6], NavCog [1] or NaviLens [7]. However, these interfaces showed severe throughput restrictions [3] and were found non-optimal even for simple left/right cues [8]. Other interfaces incorporated non-linguistic solutions, ranging from spatialized audio to haptic displays. For instance, Head-Related Transfer Function (HRTF) sound processing and motion capture systems were applied to guide BVI users along a route by reproducing virtual sound sources at intermediate points [9]. Also, hand-held devices were developed which provided verbal messages according to the position pointed at, or tapped, on a map [10; 11]; others change shape to provide heading cues [12]. Another main set of non-linguistic solutions adapted stimuli from one sensor modality to another, i.e., sensory substitution. Not limited to orientation, systems in this line of work strive to assist BVI people in navigation by mapping visual-to-tactile and visual-to-acoustic stimuli. Some of the first devices encoded low-level visual information in acoustic/tactile stimuli, e.g., pixel data from video frames. As could be appreciated in [PERSON]'s et al. 's TVSS [13] and [PERSON]'s vOICe [14] these systems do provide users with visual-like perceptions [15; 16] but the amount of data that can be conveyed is severely restricted. Some of the major constraints are the \"difference of throughput data capability between sensory modalities (bandwidth), and the compatibility with higher-nature cognitive processes\" [3; 17]. On the other hand, several sensory substitution systems extracted high-level information out of raw measurements and exploited the natural capabilities of the remaining sensory modalities to assimilate such information. As an example of the latter, in the Virtual Acoustic Space project [18] the 3D surfaces in front of the user were captured by means of stereovision, and thereafter an array of virtual sound sources--stereopixels--were generated over these surfaces. As stated, this was perceived as a \"large number of raindrops striking the surface of a pane of glass\". This specific visual-to-auditory mapping made use of the capability of hearing to locate audio sources, infer room size from the reverberation, etc. A later test showed how blind subjects were able to use these acoustic cues to build a schematic of their environment without relying on touch [19]. Additionally, the haptic Radar project [20] consisted of a wearable set of IR proximity sensors paired with haptic actuators. Distance measurements from objects were encoded in vibration intensity, effectively providing the user with intuitive information regarding the presence/absence of and distance from objects in multiple directions at the same time. Untrained test subjects were able to detect and avoid unseen approaching objects. Similarly, the ENVS project [21] encoded distance measurements as haptic stimuli in the user's fingers. As stated by the researchers, it seemed as if things were touched from a distance. Although these visual-to-auditory and visual-to-tactile sensory substitution interfaces showed positive results, their development was conditioned to the currently available technology.