## 5 Sensors
### RGB-D Cameras  
RGB-D cameras capture both color and depth data, making their use essential in robotics and unmanned ground vehicles for navigation, obstacle avoidance, and object manipulation. Their ability to provide detailed scene reconstructions and spatial awareness enhances object recognition, path planning, and environmental interaction, highlighting their critical role in these advanced applications. Although the RGB component is extracted similarly to conventional cameras, using an array of photosensitive elements to capture red, green, and blue light, depth information is obtained through various methods, primarily time-of-flight (ToF), structured light, and stereo vision. ToF cameras emit infrared light pulses and measure the time taken for the light to reflect back from the scene. The time delay is proportional to the distance, enabling the calculation of depth for each pixel. Structured Light (SL) cameras project a known pattern of light onto the scene. The deformation of this pattern when viewed from a different angle is analyzed to compute the depth. The stereo vision (SV) working principle uses two or more cameras positioned at different viewpoints. By comparing the disparity between corresponding points in the images captured by each camera, depth information is derived using triangulation [27; 28; 29].  
While ToF cameras are highly effective in controlled lighting conditions, their performance can degrade in external sunlight scenes due to interference from ambient light, reduced SNR, overexposure, thermal effects, increased power demands, and limited range. These challenges necessitate additional design considerations and mitigation strategies for outdoor applications. To improve daylight accuracy in ToF RGB-D cameras, several strategies are put in place, such as optical filtering (i.e., using narrow-band infrared filters to block out the broad spectrum of sunlight while allowing the specific wavelength used by the ToF camera to pass through) and high-frequency modulation (i.e., modulating the emitted light at a high frequency that is less likely to be affected by ambient light).  
An overview of the main RGB-D cameras is outlined in Table 1. Different models for outdoor use are compared according to their different characteristics, such as their principle of working, shutter type, measuring range, pixel resolution, frame rate, and interface.  
Figure 4: Prevalence and distribution of hardware ICT components for monitoring UGVs. This study examines the number of scientific publications from the last 10 years, as investigated using Google Scholar. On the left: sensors. On the right: computational devices (CPUs are ubiquitous and therefore are not included in the statistics).  
In the authors' experience, global shutter technology may be a better solution than rolling shutter technology. In the latter approach, the optical sensor is exposed to incoming light in a row-by-row sequence, unlike the global shutter, where the entire sensor is read simultaneously. This causes a delay in reading the last 'pixel' compared to the first (readout time), which can degrade image quality due to the motion of the UGV. While global shutters were traditionally associated with more expensive cameras, affordable options are now available on the market. For example, the Orbbec Gemini 336 L in in Table 1 can be purchased for less than EUR 500.