An Intelligent Ground-Air Cooperative Navigation Framework Basedon Visual-Aided Method in Indoor Environments

2021 ◽  
pp. 1-10
Author(s):  
Zi-Hao Wang ◽  
Kai-Yu Qin ◽  
Te Zhang ◽  
Bo Zhu
Keyword(s):  
Navigation System ◽  
Reconstruction Method ◽  
Indoor Environments ◽  
Ground Vehicle ◽  
Cooperative Navigation ◽  
Localization And Mapping ◽  
Small Uav ◽  
Actual Environment ◽  
Heterogeneous Robots ◽  
Aerial Vehicle

In the future, heterogeneous robots are expected to perform more complex tasks in a cooperative manner, and the onboard navigation system is required to be capable of working safely and effectively in the area where GNSS signal is weak or even could not be received. To demonstrate this concept, we have developed a cooperative navigation system by the use of Ground-Aerial Vehicle Cooperation. The key innovations of the development lie in the following aspects: (1) a local scalable self-organizing network is constructed for data interaction between a small UAV and a reusable ground robot; (2) a new navigation framework is proposed to achieve visual simultaneous localization and mapping (SLAM) where carrying capacity of both the ground vehicle and UAV are systematically considered; (3) an octomap-based 3D environment reconstruction method is developed to achieve map pre-establishment in complex navigation environments, and the classic ORB-SLAM2 system is improved to be adaptive to actual environment exploration and perception. In-door flight experiments demonstrate the effectiveness of the proposed solution. More interestingly, by implementing a centroid tracking algorithm, the cooperative system is further capable of tracking a man moving in indoor environments.

Study of the route correction system for the on-board navigation system of an unmanned aerial vehicle on the grounds of radar images of the terrain

2020 ◽  
pp. 129-134
Keyword(s):  
Predictive Model ◽  
Unmanned Aerial Vehicle ◽  
Predictive Models ◽  
Navigation System ◽  
Error Compensation ◽  
Compensation Scheme ◽  
Radar Images ◽  
Aerial Vehicle ◽  
System Errors ◽  
Correction System

The system of route correction of an unmanned aerial vehicle (UAV) is considered. For the route correction the on-board radar complex is used. In conditions of active interference, it is impossible to use radar images for the route correction so it is proposed to use the on-board navigation system with algorithmic correction. An error compensation scheme of the navigation system in the output signal using the algorithm for constructing a predictive model of the system errors is applied. The predictive model is building using the genetic algorithm and the method of group accounting of arguments. The quality comparison of the algorithms for constructing predictive models is carried out using mathematical modeling.

Flight Path Planning of Robot for Environmental Measurement Considering Accuracy Assurance

Impact ◽  
2019 ◽  
Vol 2019 (10) ◽  
pp. 90-92
Author(s):  
Kae Doki ◽  
Yuki Funabora ◽  
Shinji Doki
Keyword(s):  
Large Scale ◽  
Highway Bridge ◽  
Climate Research ◽  
Small Uav ◽  
Inspection Process ◽  
Aerial View ◽  
Aerial Vehicle ◽  
Infrastructure Inspection ◽  
Institute Of Technology ◽  
Small Team

Every day we are seeing an increasing number of robots being employed in our day-to-day lives. They are working in factories, cleaning our houses and may soon be chauffeuring us around in vehicles. The affordability of drones too has come down and now it is conceivable for most anyone to own a sophisticated unmanned aerial vehicle (UAV). While fun to fly, these devices also represent powerful new tools for several industries. Anytime an aerial view is needed for a planning, surveillance or surveying, for example, a UAV can be deployed. Further still, equipping these vehicles with an array of sensors, for climate research or mapping, increases their capability even more. This gives companies, governments or researchers a cheap and safe way to collect vast amounts of data and complete tasks in remote or dangerous areas that were once impossible to reach. One area UAVs are proving to be particularly useful is infrastructure inspection. In countries all over the world large scale infrastructure projects like dams and bridges are ageing and in need of upkeep. Identifying which ones and exactly where they are in need of patching is a huge undertaking. Not only can this work be dangerous, requiring trained inspectors to climb these megaprojects, it is incredibly time consuming and costly. Enter the UAVs. With a fleet of specially equipped UAVs and a small team piloting them and interpreting the data they bring back the speed and safety of this work increases exponentially. The promise of UAVs to overturn the infrastructure inspection process is enticing, but there remain several obstacles to overcome. One is achieving the fine level of control and positioning required to navigate the robots around 3D structures for inspection. One can imagine that piloting a small UAV underneath a huge highway bridge without missing a single small crack is quite difficult, especially when the operators are safely on the ground hundreds of meters away. To do this knowing exactly where the vehicle is in space becomes a critical variable. The job can be made even easier if a flight plan based on set waypoints can be pre-programmed and followed autonomously by the UAV. It is exactly this problem that Dr Kae Doki from the Department of Electrical Engineering at Aichi Institute of Technology, and collaborators are focused on solving.

scholarly journals Collaborative Pursuit-Evasion Strategy of UAV/UGV Heterogeneous System in Complex Three-Dimensional Polygonal Environment

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Xiao Liang ◽  
Honglun Wang ◽  
Haitao Luo
Keyword(s):  
Visual Field ◽  
Heterogeneous System ◽  
Three Dimensional ◽  
Unmanned Ground Vehicle ◽  
Worst Case ◽  
Ground Vehicle ◽  
Pursuit Evasion ◽  
Evasion Game ◽  
Evasion Strategy ◽  
Aerial Vehicle

The UAV/UGV heterogeneous system combines the air superiority of UAV (unmanned aerial vehicle) and the ground superiority of UGV (unmanned ground vehicle). The system can complete a series of complex tasks and one of them is pursuit-evasion decision, so a collaborative strategy of UAV/UGV heterogeneous system is proposed to derive a pursuit-evasion game in complex three-dimensional (3D) polygonal environment, which is large enough but with boundary. Firstly, the system and task hypothesis are introduced. Then, an improved boundary value problem (BVP) is used to unify the terrain data of decision and path planning. Under the condition that the evader knows the position of collaborative pursuers at any time but pursuers just have a line-of-sight view, a worst case is analyzed and the strategy between the evader and pursuers is studied. According to the state of evader, the strategy of collaborative pursuers is discussed in three situations: evader is in the visual field of pursuers, evader just disappears from the visual field of pursuers, and the position of evader is completely unknown to pursuers. The simulation results show that the strategy does not guarantee that the pursuers will win the game in complex 3D polygonal environment, but it is optimal in the worst case.

Test complex for the onboard navigation system of an airport ground vehicle

2016 ◽  
Vol 55 (5) ◽  
pp. 832-841 ◽  
Author(s):  
D. A. Antonov ◽  
K. K. Veremeenko ◽  
M. V. Zharkov ◽  
R. Yu. Zimin ◽  
I. M. Kuznetsov ◽  
...  
Keyword(s):  
Navigation System ◽  
Ground Vehicle

scholarly journals VECTOR MAPS IN MOBILE ROBOTICS

2015 ◽  
Vol 2 (2) ◽  
pp. 22-28 ◽  
Author(s):  
Ales Jelinek
Keyword(s):  
Data Acquisition ◽  
Navigation System ◽  
Mobile Robotics ◽  
Map Building ◽  
Scan Matching ◽  
Line Extraction ◽  
Current State ◽  
Vector Maps ◽  
Localization And Mapping ◽  
University Of Technology

The aim of this paper is to provide a brief overview of vector map techniques used in mobile robotics and to present current state of the research in this field at the Brno University of Technology. Vector maps are described as a part of the simultaneous localization and mapping (SLAM) problem in the environment without artificial landmarks or global navigation system. The paper describes algorithms from data acquisition to map building but particular emphasis is put on segmentation, line extraction and scan matching algorithms. All significant algorithms are illustrated with experimental results.

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