scholarly journals Indoor Path-Planning Algorithm for UAV-Based Contact Inspection

Sensors ◽  
2021 ◽  
Vol 21 (2) ◽  
pp. 642
Author(s):  
Luis Miguel González de Santos ◽  
Ernesto Frías Nores ◽  
Joaquín Martínez Sánchez ◽  
Higinio González Jorge
Keyword(s):  
Path Planning ◽  
Real Time ◽  
Execution Time ◽  
Point Cloud ◽  
Indoor Environments ◽  
Calculation Algorithm ◽  
Time Restrictions ◽  
Planning Algorithm ◽  
Inspection Tasks ◽  
Path Planning Algorithm

Nowadays, unmanned aerial vehicles (UAVs) are extensively used for multiple purposes, such as infrastructure inspections or surveillance. This paper presents a real-time path planning algorithm in indoor environments designed to perform contact inspection tasks using UAVs. The only input used by this algorithm is the point cloud of the building where the UAV is going to navigate. The algorithm is divided into two main parts. The first one is the pre-processing algorithm that processes the point cloud, segmenting it into rooms and discretizing each room. The second part is the path planning algorithm that has to be executed in real time. In this way, all the computational load is in the first step, which is pre-processed, making the path calculation algorithm faster. The method has been tested in different buildings, measuring the execution time for different paths calculations. As can be seen in the results section, the developed algorithm is able to calculate a new path in 8–9 milliseconds. The developed algorithm fulfils the execution time restrictions, and it has proven to be reliable for route calculation.

scholarly journals PATH PLANNING FOR INDOOR CONTACT INSPECTION TASKS WITH UAVS

2020 ◽  
Vol XLIII-B4-2020 ◽  
pp. 345-351
Author(s):  
L. M. González-deSantos ◽  
J. Martínez-Sánchez ◽  
H. González-Jorge ◽  
P. Arias
Keyword(s):  
Path Planning ◽  
Point Cloud ◽  
Initial Position ◽  
Target Point ◽  
Monitoring Methods ◽  
Planning Algorithm ◽  
Close Range ◽  
Inspection Tasks ◽  
Path Planning Algorithm ◽  
Contact Sensors

Abstract. UAV technology has become a useful tool for the inspection of infrastructures. Structural Health Monitoring methods are already implementing these vehicles to obtain information about the condition of the structure. Several systems based on close range remote sensing and contact sensors have been developed. In both cases, in order to perform autonomous missions in hard accessible areas or with obstacles, a path planning algorithm that calculates the trajectory to be followed by the UAV to navigate these areas is mandatory. This works presents a UAV path planning algorithm developed to navigate indoors and outdoors. This algorithm does not only calculate the waypoints of the path, but the orientation of the vehicle for each location. This algorithm will support a specific UAV-based contact inspection of vertical structures. The required input data consist of a point cloud of the environment, the initial position of the UAV and the target point of the structure where the contact inspection will be performed.

scholarly journals Path Planning for Highly Automated Driving on Embedded GPUs

2018 ◽  
Vol 8 (4) ◽  
pp. 35 ◽  
Author(s):  
Jörg Fickenscher ◽  
Sandra Schmidt ◽  
Frank Hannig ◽  
Mohamed Bouzouraa ◽  
Jürgen Teich
Keyword(s):  
Path Planning ◽  
Real Time ◽  
Autonomous Driving ◽  
Automated Driving ◽  
Computing Power ◽  
Planning Algorithm ◽  
Time Requirements ◽  
Evaluation Platform ◽  
Path Planning Algorithm ◽  
Highly Automated Driving

The sector of autonomous driving gains more and more importance for the car makers. A key enabler of such systems is the planning of the path the vehicle should take, but it can be very computationally burdensome finding a good one. Here, new architectures in ECU are required, such as GPU, because standard processors struggle to provide enough computing power. In this work, we present a novel parallelization of a path planning algorithm. We show how many paths can be reasonably planned under real-time requirements and how they can be rated. As an evaluation platform, an Nvidia Jetson board equipped with a Tegra K1 SoC was used, whose GPU is also employed in the zFAS ECU of the AUDI AG.

scholarly journals 2D Lidar-Based SLAM and Path Planning for Indoor Rescue Using Mobile Robots

2020 ◽  
Vol 2020 ◽  
pp. 1-14
Author(s):  
Xuexi Zhang ◽  
Jiajun Lai ◽  
Dongliang Xu ◽  
Huaijun Li ◽  
Minyue Fu
Keyword(s):  
Path Planning ◽  
Mobile Robots ◽  
Real Time ◽  
Obstacle Avoidance ◽  
Basic System ◽  
Rescue Robot ◽  
Planning Algorithm ◽  
Local Path ◽  
Slam Algorithm ◽  
Path Planning Algorithm

As the basic system of the rescue robot, the SLAM system largely determines whether the rescue robot can complete the rescue mission. Although the current 2D Lidar-based SLAM algorithm, including its application in indoor rescue environment, has achieved much success, the evaluation of SLAM algorithms combined with path planning for indoor rescue has rarely been studied. This paper studies mapping and path planning for mobile robots in an indoor rescue environment. Combined with path planning algorithm, this paper analyzes the applicability of three SLAM algorithms (GMapping algorithm, Hector-SLAM algorithm, and Cartographer algorithm) in indoor rescue environment. Real-time path planning is studied to test the mapping results. To balance path optimality and obstacle avoidance, A ∗ algorithm is used for global path planning, and DWA algorithm is adopted for local path planning. Experimental results validate the SLAM and path planning algorithms in simulated, emulated, and competition rescue environments, respectively. Finally, the results of this paper may facilitate researchers quickly and clearly selecting appropriate algorithms to build SLAM systems according to their own demands.

Autonomous Collision Imminent Steering Maneuver in Presence of Surrounding Obstacles

2016 ◽  
Author(s):  
Rouhollah Jafari ◽  
Shuqing Zeng ◽  
Nikolai Moshchuk
Keyword(s):  
Path Planning ◽  
Real Time ◽  
Collision Avoidance ◽  
Geometric Method ◽  
Target Vehicle ◽  
Virtual Target ◽  
Planning Algorithm ◽  
Simulation Results ◽  
Collision Avoidance System ◽  
Path Planning Algorithm

In this paper, a collision avoidance system is proposed to steer away from a leading target vehicle and other surrounding obstacles. A virtual target lane is generated based on an object map resulted from perception module. The virtual target lane is used by a path planning algorithm for an evasive steering maneuver. A geometric method which is computationally fast for real-time implementations is employed. The algorithm is tested in real-time and the simulation results suggest the effectiveness of the system in avoiding collision with not only the leading target vehicle but also other surrounding obstacles.

scholarly journals A Path Planning Algorithm for a Dynamic Environment Based on Proper Generalized Decomposition

Mathematics ◽  
2020 ◽  
Vol 8 (12) ◽  
pp. 2245
Author(s):  
Antonio Falcó ◽  
Lucía Hilario ◽  
Nicolás Montés ◽  
Marta C. Mora ◽  
Enrique Nadal
Keyword(s):  
Path Planning ◽  
Mobile Robot ◽  
Real Time ◽  
Potential Field ◽  
Dynamic Environment ◽  
Artificial Potential Field ◽  
Proper Generalized Decomposition ◽  
Partial Differential ◽  
Planning Algorithm ◽  
Path Planning Algorithm

A necessity in the design of a path planning algorithm is to account for the environment. If the movement of the mobile robot is through a dynamic environment, the algorithm needs to include the main constraint: real-time collision avoidance. This kind of problem has been studied by different researchers suggesting different techniques to solve the problem of how to design a trajectory of a mobile robot avoiding collisions with dynamic obstacles. One of these algorithms is the artificial potential field (APF), proposed by O. Khatib in 1986, where a set of an artificial potential field is generated to attract the mobile robot to the goal and to repel the obstacles. This is one of the best options to obtain the trajectory of a mobile robot in real-time (RT). However, the main disadvantage is the presence of deadlocks. The mobile robot can be trapped in one of the local minima. In 1988, J.F. Canny suggested an alternative solution using harmonic functions satisfying the Laplace partial differential equation. When this article appeared, it was nearly impossible to apply this algorithm to RT applications. Years later a novel technique called proper generalized decomposition (PGD) appeared to solve partial differential equations, including parameters, the main appeal being that the solution is obtained once in life, including all the possible parameters. Our previous work, published in 2018, was the first approach to study the possibility of applying the PGD to designing a path planning alternative to the algorithms that nowadays exist. The target of this work is to improve our first approach while including dynamic obstacles as extra parameters.

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