# WARM: Wearable AR and Tablet-Based Assistant Systems for Bus Maintenance
## 2 State of the Art  
The main challenge of an AR system is to obtain perfect alignment between real and virtual objects in order to create the illusion that both worlds coexist. To that end, the position and orientation of the observer (i.e., the localization of the human with respect to the environment) has to be determined in order to configure a virtual camera that displays the virtual objects in their corresponding position. This problem is known as tracking and, although there are many alternatives to address it by using different sensors, tracking based on optical sensors is the most popular solution. In the last years, markerless monocular solutions have gained in popularity due to their simplicity and low cost (one single camera) and by avoiding having to position markers in the scene. They take advantage of the visual cues that are naturally in the scene. Depending on whether the scene geometry is known or not, the markerless tracking is divided into two groups [4]. In Structure From Motion (SFM) approaches the camera movement is estimated while the 3D reconstruction of the scene is performed [5]. On the other hand, model-based techniques store the knowledge about the scene in a 3D model, which is available before the camera tracking begins. The 3D model could be represented by its simple 3D geometry [6], or by a more detailed description, that includes the geometry and the texture of its surface [7]. However, despite many years of research, optical tracking of industrial objects is not a solved problem (metallic objects with reflections, poor textures, dirty environment, etc.) and many studies have to be conducted yet [8; 9] to provide reliable solutions that can be used in a factory. Errors in the estimation of the position of the virtual objects added to a scene greatly reduces the realism and quality of the integration of the information in the real context. This can severely limit the relevance of the information received by the user. Focusing on industrial environments, AR solutions can also be found but, even markers-based solutions, most of them are in an experimental/lab prototype status [1; 2; 3]. Several works [8; 10; 11; 12; 13; 14] demonstrate the benefits of AR based approaches applied to the assistance in maintenance, assembly and repair operations in terms of operation efficiency. These works argue that AR enriches the way in which users understand the real world, i.e., AR let users understand clearly what to do at any time. Compared to VR, AR offers information that is integrated into the real world, while VR manipulates virtual objects. For this reason, AR is used for both training as VR, but it is mainly used for guidance. Some works [15] studied the long-term usage of high-quality AR technology in industrial training and determined that it reduces stress for the user compared to traditional training procedures, and therefore, improves worker satisfaction. Current approaches use AR to present the worker with an \"on-line\" virtual manual of the task. In many cases, this is simply a list of the different steps that the user has to complete in order to finish a task. More advanced approaches present a virtual model integrated into the real world [16]. These works describe algorithms that recognize the 3D objects and track them meanwhile disassembly instructions are overlapping in the real scene guiding the user along the task. In this case, the disassembly sequence is computed in a pre-process following automatic methods based on the object geometry [17; 18]. A very systematic review papers can be seen in [19; 20; 21] works. In all of these works, the common points are that AR has a lot of previous works showing tracking and registering applications in most of the market sectors. However, they agree that AR is still not mature for complying with industrial requirements of robustness and reliability. In fact, looking the experiments, we have the same conclusions in our work. AR technology tries to improve the traditional concept of digital maintenance.