# UWB-Based Human-Following System with Obstacle and Crevasse Avoidance for Polar-Exploration Robots
## 1 Introduction
By presuming that there are always navigable points between the human and the robot, the proposed local map sets the map's edges as non-obstacle areas and omits marking obstacles. Unlike traditional local maps where the presence of obstacles at the destination can prevent path generation, the proposed map allows path creation even when obstacles obscure the destination, as the map edges are not marked with obstacles. Therefore, the newly proposed local obstacle map places the destination in the direction of the human and generates a path that avoids obstacles while reaching the destination. From this newly generated local map, a cost map is created using the wavefront algorithm, and a path to the destination is generated. However, due to the characteristics of paths generated based on a grid map, wavefront algorithm [23], and a* algorithm [24; 25], the robot may move in a zigzag manner or follow a roundabout path even in the absence of obstacles [23; 24; 25]. To mitigate this phenomenon, after generating the local path, the algorithm identifies the farthest path point from the robot's position that can be connected in a straight line without intersecting obstacles, and a new local path is generated accordingly. Consequently, the robot can move directly toward the human in the absence of obstacles and follow the human while avoiding obstacles when they are present. As the robot moves toward the target location via the generated path, it naturally avoids collisions while following the operator. The system introduced in this paper has the following contributions and advantages:  
Firstly, this paper proposes a human-following system applicable to exploration robots operating in extreme environments, such as Antarctica. This system employs a UWB anchor-tag device to enable the robot to follow the explorer even in conditions where vision-based sensors (e.g., vision cameras, RGB-D cameras commonly used in studies for structured environments) fail to function due to factors like strong sunlight, ultraviolet light, whiteouts, or blizzards. Additionally, a real-time obstacle-avoidance algorithm is proposed to cope with the sudden occurrence of crevasses. Second, since existing path-generation methods cannot be directly applied to a human-following system, this paper proposes an improvement. By assuming that the robot can use the space traversed by the human, we enhance the local obstacle map to enable path generation even when obstacles obscure the path between the human and the robot. Additionally, to address the issue of conventional path-generation methods failing to directly point toward the destination, we refine the existing path-planning methods by straightening the generated paths, thereby eliminating unnatural robot movements. Finally, unlike previous human-following studies that operate in structured and predictable environments, this paper proposes a collision-avoidance algorithm that includes local map generation and local path planning, ensuring safe human-following in unknown environments. These contributions enable the explorer to move, operate the robot, and carry out exploration activities simultaneously without considering the robot's collisions. This paper is organized as follows. Section 2 describes the polar-exploration robot KAREX and the integrated human-following system targeted in this study. In Section 3, we explain the UWB-based method for estimating the explorer's position and propose a target position generation algorithm to maintain the distance between the robot and the explorer. Section 4 presents the local obstacle map and local path-planning algorithm for obstacle avoidance. In Section 6, we verify the performance of the proposed system through experimental results, and in Section 7 we conclude the paper.