UavisBug: Vision-based 3D motion planning and obstacle avoidance for a mini-UAV in an unknown indoor environment

被引：1

作者：

Ebrahimi, Amir ^{[1
]}

Janabi-Sharifi, Farrokh ^{[2
]}

Ghanbari, Ahmad ^{[3
]}

机构：

[1] School of Engineering Emerging Technology, Department of Mechatronics, Tabriz University, Tabriz, Iran

[2] Robotics Mechatronics and Manufacturing Automation Laboratory (RMAL), Department of Mechanical and Industrial Engineering, Ryerson University, 350 Victoria Street, Toronto,ON,M5M 2K3, Canada

[3] School of Engineering Emerging Technology, Department of Mechanical Engineering and Mechatronic Engineering, Head of Mechatronic Research Laboratory, Tabriz University, Tabriz, Iran

来源：

Canadian Aeronautics and Space Journal | 2014年 / 60卷 / 01期

关键词：

Visual servoing - Robot programming - Motion planning;

D O I：

10.5589/q14-005

中图分类号：

学科分类号：

摘要：

This paper introduces a new class of Bug algorithm that combines local planning with global information to guarantee convergence. Existing Bug algorithms are typically designed for 2D robot navigation in 2D environments and do not integrate vision information within their planning algorithm. In this paper a new algorithm, uavisBug, is proposed for small quadrotor UAV navigation in a 3D environment. On-board vision perception is incorporated to enable 3D way-finding behaviors in an initially unknown environment. The proposed algorithm shows non-oscillatory behaviors in the UAV's flight in proximity of obstacles. It is also immune to potential local minima exhibited by artificial force field approaches. In addition to system and sensors modeling, UAV control, UAV pose estimation, and fast environment mapping are also included. Simulation results are used to validate the proposed approach. © 2014 CASI.

引用

页码：9 / 21