An Improved Navigation Method for Robot in Indoor Dynamic Environment Based on Ground Extraction - Dang, Khanh Hoa; Than, Viet Duc; Do, Trong Anh; Vu, Song Tung; Le, Dzung; Nguyen, Tien Dzung (Old Journal, 2018)
This paper presents a ground-based navigation method for an indoor robot to reach a predetermined target. By mining depth maps effectively, a mobile robot could find right path and self-locate with a proposed algorithm named Always Move Straight to the Destination (AMDS). The proposed navigation system extracts the ground plane from the depth map provided by an RGB-D camera. Then the navigation system has established an optimal obstacle avoiding strategy with a success rate of 98.7% which is better than some recent comparison methods based on Artificial Neural Network (ANN) classifiers or method of combination of two algorithm of Dynamic Window Approach (DWA) and Anytime Repairing A* (ARA*). The robot’s navigational capability is more flexible than the comparison methods because the angle of direction adjustment is 1 degree. The proposed ground-based navigation method could be integrated into low cost robots.