An Improved Navigation Method for Robot in Indoor Dynamic Environment Based on Ground Extraction

Authors: Đỗ Trọng Anh, Đặng Khánh Hòa, Thân Việt Đức, Vũ Song Tùng, Lê Dũng, Nguyễn Tiến Dũng*


This paper presents a navigation method for an indoor robot to hit a predetermined target by combining two technologies consist of depth map mining and self-created 2D mapping. Experimental robots are used the tactic named Always Move Straight to the Destination (AMDS). First, the system extracts the ground plane from the depth map provided by the RGB-D camera to find the robot direction. If there is not any obstacle, it always tries to move straight to the destination. If the robot meets obstacles, it will switch to the improved avoidance mode to overcome them. Then, the robotic system returns to AMDS mode. 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 quantity of navigation direction angles of the proposed method is more than the best compared method twenty times with navigation angle step of 1 degree. The result of this work is a robust proof for integrating the proposed navigation algorithm into low cost robots.


depth map, ground plane, navigation, path direction
Pages : 62-68

Related Articles:

Authors : Hồ Mạnh Linh*, Tạ Sơn Xuất, Nguyễn Khắc Kiểm , Đào Ngọc Chiến
Authors : Nguyễn Anh Thái*, Đào Văn Lân, Hoàng Văn Phúc
Authors : Lê Thanh Hương*, Trần Trọng Nhân
Authors : Đỗ Trọng Hiếu*, Dương Minh Đức*, Hoàng Văn Thắng, Trần Văn Tùng, Nguyễn Trí Kiên
Authors : Phạm Văn Trường*, Trần Thị Thảo*, Trịnh Công Đồng
Authors : Vu Duy Hai*, Lai Huu Phuong Trung*, Phan Dang Hung, Dao Viet Hung, Dao Quang Huan, Chu Quang Dan