# Reliable Visual Exploration System with Fault Tolerance Structure
## 1 Introduction  
Visual exploration plays a crucial role in vision-based mobile robot applications. For visual localization and mapping, many related studies have been published [1; 2] in VSLAM (Visual Simultaneous Localization and Mapping) area, whose focus has often been on precision. As indicated in [3], the improvement of robustness could be a major challenge for practical vision-based navigation system, and many studies have been published to tackle this problem [4; 5]. Nevertheless, comparing with the related works that regard reliability improving as a CV (Computer Vision) problem, we attempt to address the issue by considering vision-based navigation as a fault tolerance system, where both platform driving and exploration termination are considered. Referring to [6; 7], a fault tolerance structure is introduced here, where \"fault\" is defined as the failure of visual tracking and mapping.  
For fault tolerance in mobile robots, besides VSLAM, additional problems should be considered [8]. One such problem involves the design of active controller for the mobile platform to determine the desired robot motion. For controlling, the localization of the mobile platform is always required [9]. Some related works search the goal point in the image space with a Homography transformation [10; 11], where planar assumption is needed, and this assumption limits the generality and robustness of controller. Owing to the tremendous progress in pattern recognition [12; 13] research, a reactive strategy according to the captured image has been proposed in recent years, and it is popularly studied in the community ofautonomous driving [14; 15; 16]. In this paper, an active controller is designed and applied in the continuous operation of a mobile robot.  
In addition to the active controller, termination conditions for exploration are introduced for exploration evaluation. Some existing termination conditions utilize the depth information from LiDAR sensor or RGB-D sensor [17], and makes use of the minimum of system entropy for path planning [18; 19]. These methods are inapplicable to a vision exploration system since no depth information is provided. Based on the SVO system [2], an unknown environment exploration study has been developed [20]; the triangulation of visual features is required for frontier detection, which is fragile due to the nature of feature-based triangulation. Using the prior knowledge of the environment, such as its frontier or CAD (computer aided design) model, some termination conditions have been introduced [21; 22]. Based on to the existing related works, without requiring any prior knowledge or computing feature triangulation, a coarse-to-fine termination condition is proposed in this study, and it is exploited for fault prevention.  
With visual localization and mapping, active controller and termination condition, we are able to introduce a complete exploration system for reliable mobile robot mapping and tracking. The experimental results demonstrate the advantage of exploration with the proposed solutions to the failure in visual tracking and mapping. Our main contribution is proposing a fault tolerance structure for autonomous visual exploration. Besides visual mapping and localization, the active controller and the exploration termination condition are introduced for overcoming visual tracking and mapping failures at the level of mobile robot systems.  
The rest of this paper is organized as follows: Section 2 presents the framework of our fault-tolerant robot navigation system. Section 4 introduces the vision-based mapping and localization. In Section 3, an active controller based on image semantic segmentation is described. Section 5 details the termination condition for environment exploration. Section 6 provides the evaluation of our proposed system, and Section 7 discusses of the experimental results. Section 8 concludes the paper.