Abstract
In this article, we design a low-cost navigation system for a quadrotor working in unknown outdoor environments. To reduce the computing burden of the quadrotor, we build a separated system and transfer the computing resources from onboard side to ground station side. Both sides’ communication is guaranteed by 5G wireless networks. We utilize a stereo camera to acquire point clouds and build Octomap for the quadrotor’s navigation. Then, the trajectory is generated in two stages. In the first stage, a modified RRT*-CONNECT algorithm is adopted to generate a set of collision-free waypoints. In the second stage, a curve fitting algorithm is utilized to get a smooth piecewise Bezier trajectory. The advantage of the proposed method is to optimize the path into a safe, smooth, and dynamically feasible trajectory in real time. The modules of the state estimation, dense mapping, and motion planning are integrated into a DJI Matrice 100 quadrotor. Finally, simulation and experiments are both conducted to show the validity and practicality of our method.
Highlights
Micro aerial vehicles (MAVs) are becoming more and more popular in many fields
In cluttered outdoor scenes such as forests and ruined places, these application scenarios are unfriendly and accidents may happen sometimes, which is a deadly threat for the quadrotors to carry out missions in these environments
This article is focused on how to design and implement a low-cost separated system for quadrotors to carry out autonomous path planning in cluttered outdoor scenes
Summary
Micro aerial vehicles (MAVs) are becoming more and more popular in many fields. It is convenient to utilize such platforms to execute flight missions in complex scenes for their wide coverage, high mobility, and agility. As the applications in the fields of bridge inspection, power line inspection, forest fire prevention, search, and rescue, the demand for MAVs’ autonomous flight in unknown scenes has become extremely larger than before. The purpose of this article is to build an inexpensive platform for a quadrotor to navigate autonomously in complex environments, such as woods and ruins. The huge breakthroughs in localization, mapping, navigation, and planning have made autonomous onboard flight possible in complex places.[1,2,3] These works need the quadrotors to carry on an advanced onboard computer to process localization, mapping, planning, and flight control simultaneously. In cluttered outdoor scenes such as forests and ruined places, these application scenarios are unfriendly and accidents may happen sometimes, which is a deadly threat for the quadrotors to carry out missions in these environments. Once the quadrotors are missing or broken badly, it will cause significant economic losses to Information Science and Technology College, Dalian Maritime University, Dalian, Liaoning, China
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