## 5 Autonomous Navigation Technology
### Positioning Technology  
The positioning technology for the underground intelligent scraper refers to the determination of its position in a two-dimensional coordinate system and its own attitude as well or it can also be expressed as the relative position of the scraper to the coordinate of a known location (beacon point) in the underground tunnel. Thus, positioning technology is the basis for autonomous navigation of LHD. GPS-based autonomous positioning technology is known to be popular in many fields, but as the GPS signal is too weak in the underground roadway, other methods need to be found for scraper positioning [67]. At present, there is much research on the LHD positioning technology at home and abroad, mainly as the dead reckoning method, inertial navigation technology, ultra-wide band (UWB) positioning technology, visual positioning technology and information fusion positioning technology, etc. [68; 69; 70]. (1) Dead reckoning method  
The basic principle of the dead reckoning method is with known initial coordinates of the scraper, collecting the information of heading angle, speed and time using the sensors installed on the scraper (such as heading gyro, speedometer, odometer, etc.) and calculating the data for the current position of the shovel [71]. This method has good accuracy and low cost for short-term positioning, but has accumulated errors for long-term positioning estimation, which need to be corrected by correction techniques [68; 72]. (2) Inertial navigation technology  
The inertial navigation system is a completely independent system that does not rely on external information, but obtains the information of the speed, position and attitude  
Figure 8: Example for improper shoveling trajectory planning [47]. of the vehicle by its own inertial components, such as gyroscopes and accelerometers [68]. Although the inertial navigation technology exhibits good concealment, it has advantages, such as being affected by neither natural, man-made factors nor external electromagnetic interference, and there will be inevitable accumulative errors after a long-time server. In order to improve the absolute accuracy of the system, other auxiliary positioning sensors are necessarily installed. To be specified, the cost for the equipment in this system is reported to be quite expensive [73; 74]. 1. UWB Positioning  
UWB technology locates in real time the vehicle through building a base station in the roadway, obtaining signals between the base station and the vehicle tag, then attaining the real-time location information of the tag. This method is reviewed to be insensitive to channel fading, showing high positioning accuracy and low system complexity [75; 76]. To position the accurate two-dimensional location of the vehicles, [PERSON] et al. [77] conducted tests to collect the distance signals and position the tags, especially for narrow-long underground coal mine roadways, through UWB technology and TOA algorithms, respectively. It was found that this method was proved to show higher positioning accuracy than regular methods in both visual and non-visual distance. However, in UWB positioning technology, the location information of at least three base stations needs to be received for calculation about the tags' location in the targeted area zone. Since the underground tunnels are always long and narrow, multiple base stations must be constructed and high cost would be consumed for higher positioning accuracy [67]. 1. Visual Positioning  
Visual positioning technology refers to collecting the surrounding environment of the roadway by cameras or other visual sensors, setting, identifying and tracking special route markers by the scraper, analyzing the signals and finally obtain the location information of the scraper. [PERSON] et al. [78] proposed a form of visual serving control, which can overcome uncertainties in the calculation models (including robots, vision systems and environments) and improve the accuracy of visual positioning or tracking. [PERSON] et al.