Jimin Kim

Mobile robot navigation with reactive free space estimation

One of the fundamental requirements of an autonomous mobile robot is that it must not collide with obstacles. This paper addresses the problem of controlling an autonomous robot to avoid obstacles for reactive route following navigation. The four-wheeled mobile robot is equipped with three monocular cameras for route following and a range sensor for obstacle avoidance. The equipped robot moves route environments using a reactive navigation method. When an obstacle is detected by a range sensor, the proposed obstacle avoidance method estimates the free space in the route and generates the turning direction vector for heading the robot to the free space which is wider than other space. We executed experiments about the navigation algorithm of the robot with an obstacle including curved path environments in this paper. Through the experiment results in various cases, it is discovered that the proposed method has a better time performance for obstacle avoidance in comparison with other conventional technique.

Roadmap-based stealth navigation for intercepting an invader

This paper deals with the stealth target-interception problem based on the active prediction planning execution (APPE) strategy. In order to cope with the evasive feature of the invader, we make the robot move stealthily by hiding behind obstacles. We adopt a roadmap-based decoupled approach, which plans the path and the trajectory separately by developing new concept; the detection map. Simulation results demonstrate the efficiency of the proposed algorithm. It has an enough practical running time to be applied to the real-time situation.

Robust scan matching with curvature-based matching region selection

This paper presents a novel scan matching algorithm which uses not whole scan region but only salient scan region selected around curvature-based features. A curvature function computed by the relative coordinates of neighbor scan points is used to extract salient features which are invariant to translation and rotation. Because the scan matching regions are selected around the salient features, the presented algorithm can be robustly performed even in noisy environments. The robustness of the presented algorithm was tested by datasets obtained from various noisy environments and was verified by consistently showing smaller errors than other scan matching algorithms. Moreover, the presented algorithm was successfully applied to SLAM.

Multi-robot enclosing formation for moving target capture

In a problem of target capturing for multiple robots, it is an issue that the target is fixed or movable. When the target is fixed, the problem is solved by enclosing the target. However, it is useless if the target moves. We have investigated the restrictive velocity of the target that the robots can maintain the enclosing formation. The velocity of the target is supposed to be constant and smaller than the maximum velocity of the robots. Simulations demonstrate the restrictive condition for the target by showing the enclosing formation is not maintained when the restrictive condition is not satisfied.