BSL: Navigation Method Considering Blind Spots Based on ROS Navigation Stack and Blind Spots Layer for Mobile Robot

This article proposes a navigation method considering blind spots based on the robot operating system (ROS) navigation stack and blind spots layer (BSL) for a wheeled mobile robot. In this article, environmental information is recognized using a laser range finder (LRF) and RGB-D cameras. Blind spots occur when corners or obstacles are present in the environment, and may lead to collisions if a human or object moves toward the robot from these blind spots. To prevent such collisions, this article proposes a navigation method considering blind spots based on the local cost map layer of the BSL for the wheeled mobile robot. Blind spots are estimated by utilizing environmental data collected through RGB-D cameras. The navigation method that takes these blind spots into account is achieved through the implementation of the BSL and a local path planning method that employs an enhanced cost function of dynamic window approach. The effectiveness of the proposed method was further demonstrated through simulations and experiments.