# Topological Navigation and Localization in
## 2 Related Work  
Autonomous navigation of LHDs has been a subject of scientific research since the late 1990s [2; 3; 4]. The main objectives have been to improve productivity and increase safety for the personnel, but simultaneously to benefit from reduced machine maintenance due to less wear of components. The theoretical development, and experimental evaluation, of a navigation system for an autonomous articulated vehicle is described in [4]. This system is based on the results obtained during extensive in-situ field trials and showed the relevance of wheel-slip for the navigation of center-articulated machines. In [5], one of the earlier industrial automation implementations is reviewed. It is mentioned there, that the use of automation in day-to-day operations offers flexibility and convenience for the operators. The development of what would become the first commercially available solutions for autonomous navigation of LHD machines followed shortly thereafter. The work of [PERSON] [6] set the basis for the AutoMine software of the LHD manufacturer Sandvik, while the work of [PERSON], [PERSON], and [PERSON] [7; 8; 9] set a similar precedent for the software MINEGEM of Caterpillar. Only a few years later, the work by [PERSON], [PERSON], and [PERSON] [10; 11; 12] configured what would become Scooptram Automation of the company Atlas Copco (now Epiroc). These companies have applied their automation solutions directly to their articulated vehicles [13]. Because of their commercial applica  
Figure 2: Example of _inversion_ maneuver. tion, only the initial work on the development of the autonomous systems from LHD manufacturers is available in the literature. For instance, autonomous navigation from the manufacturer Sandvik is based on an absolute localization paradigm, i.e., it relies on odometry and detection of natural markers of the tunnel network [6]. Localization is achieved by taking a profile of the tunnel in a 5 [m] long section and comparing it to a known map. Caterpillar, on the other hand, initially based its system on mainly reactive techniques (wall following), in conjunction with a topological map with information about loading points, dump points, intersections, and other markers that are used in an opportunistic location scheme [9]. Finally, Epiroc made use of a hybrid navigation paradigm [11]. A set of behaviors was programmed under a fuzzy logic scheme to form the reactive part, while a higher level (deliberative) planner was used at intersections or open spaces. Despite its success in delivering a product to market, research in autonomous navigation for underground tunnels continues to be a relevant topic. In [14], a review is given on the performance of automated LHDs in mining operations. It also mentions some issues and challenges that remain. The dynamic and highly variable nature of mining operations underlines the need for flexible and quickly deployable systems, features that earlier commercial solutions lacked [15; 16]. These shortcomings are also known to LHD manufacturers, who continue to improve their systems [17]. Automation in mining is, most certainly, a widespread trend that has already shown corporate benefits, and it will continue to drive the modernization of the mining industry [18]. Cost, productivity, and safety are still the driving forces for investments in automated systems. Recent publications in the field also suggest the increasing interest of China in the application of automation technologies [19; 20; 21]. Particular attention has been paid to modeling, and control techniques. The autonomous navigation system presented in this paper is based on topological navigation, and model predictive control (MPC). Underground mining environments have been shown to be suited for the extraction of features needed to build topological maps [22], and a mixture of topological and metric maps has been used successfully to map and navigate in large environments [23]. MPC has also been proven to perform well in the high-speed control of vehicles with nonlinear kinematics [24; 25; 26].