# Visuospatial Working Memory for Autonomous UAVs: A Bio-Inspired Computational Model
## 2 A Bio-Inspired Computational Model for Autonomous UAVs
### Spatial Working Memory  
* SPL module. This module represents the superior parietal lobe. This brain area has been associated with tasks related to spatial working memory, maps of coordinates, spatial shifting, and spatial attention [17; 33; 34]. Therefore, the SPL module is responsible for decoding visual cues sent by the VC module through the IPS module. Information of these cues is used by the SPL module for creating maps of coordinates. These maps are encoded in an egocentric fashion, according to relative coordinates of the UAV and its orientation. Allocentric representations, relative to environmental references, are not considered yet in this first version of the bio-inspired VSWM computational model. Neurophysiological studies suggest that the superior parietal lobe is part of the networking involved in visual search tasks [33; 34]. Therefore, the SPL module helps with spatial shifting and spatial attentional tasks in order to detect displacement of visual stimuli. Additionally, this module shares visuospatial information with the IPS module. Figure 4 shows an example of coordinate maps created by the SPL module. Fuzzy spatial information of the relationship between the UAV and ROIs identified in the environment is processed and included in these maps. For instance, Figure 4a shows that in a first scene two ROIs have been identified. According to the ROIs' coordinates, the SPL module has considered that ROI 1 is located to the front left of the UAV, and ROI 2 is located to the front right of the UAV. On the other hand, Figure 4b shows a second scene, where two new ROIs have been identified. When two or more ROIs are close to each other, the SPL module generates additional fuzzy spatial information of the relationship between these ROIs. In order to establish the positions of the identified ROIs relative to the UAV, Equations (5) and (6) are defined for segmenting the UAV's field of view into five regions as shown in Figure 5. These trivial equations allow the UAV to situate ROIs in the environment. \[f(x)=\left\{ \begin{array}{cc}-2x,&x<0\\ 2x,&x\geq 0\end{array} \right. \tag{5}\]  
Equation (5) establishes the limit between the region classified as front and the regions classified as front left and front right when \(x\) and \(f(x)\) represent the \(x\)-_coordinate_ and \(y\)-_coordinate_, respectively. \[f(x)=\left\{ \begin{array}{cc}-\frac{x}{4},&x<0\\ \frac{x}{4},&x\geq 0\end{array} \right. \tag{6}\]  
Equation (6) establishes the limit between the region classified as front left and left and front right and right. Moreover, a local matrix of \(N\cdot M\) dimensions is applied over each ROI to generate additional fuzzy spatial information when two or more ROIs are close to each other. Equations (5) and (6), and their reflecting functions in relation to the \(x\) axis are applied for segmenting this local matrix to establish spatial relationships between ROIs. Figure 4: (**a**) A coordinate map that represents the spatial relationship between the UAV and ROIs identified in the environment. (**b**) A second coordinate map with additional spatial information between ROIs that are close to each other. Figure 5: The UAV’s view field segmentation. * IPS module. This module represents the intraparietal sulcus. In monkeys and humans, the IPS subdivides the PPC into a superior and an inferior parietal lobe [17]. The IPS has been associated with the creation of attentional priority maps, also known as saliency maps. This brain area is part of networking involved in the visual search task [33]. Therefore, the IPS module has bidirectional communication with the SPL and IPL modules, which are involved in the visual search task too. The IPS module is responsible for decoding visual cues coming from the VC module in order to represent spatial information for the SWM. The creation of attentional priority maps is part of the tasks done by this module. An attentional priority map is a topographic representation of the distribution of attentional weights.