scholarly journals Ellipsoidal Path Planning for Unmanned Aerial Vehicles

2021 ◽  
Vol 11 (17) ◽  
pp. 7997
Author(s):  
Carlos Villaseñor ◽  
Alberto A. Gallegos ◽  
Gehova Lopez-Gonzalez ◽  
Javier Gomez-Avila ◽  
Jesus Hernandez-Barragan ◽  
...  
Keyword(s):  
Path Planning ◽  
Unmanned Aerial Vehicles ◽  
Clustering Algorithms ◽  
Computational Cost ◽  
Mapping Algorithm ◽  
Planning Strategy ◽  
Aerial Vehicles ◽  
Planning Algorithm ◽  
Trained Neural Network ◽  
Path Planning Algorithm

The research in path planning for unmanned aerial vehicles (UAV) is an active topic nowadays. The path planning strategy highly depends on the map abstraction available. In a previous work, we presented an ellipsoidal mapping algorithm (EMA) that was designed using covariance ellipsoids and clustering algorithms. The EMA computes compact in-memory maps, but still with enough information to accurately represent the environment and to be useful for robot navigation algorithms. In this work, we develop a novel path planning algorithm based on a bio-inspired algorithm for navigation in the ellipsoidal map. Our approach overcomes the problem that there is no closed formula to calculate the distance between two ellipsoidal surfaces, so it was approximated using a trained neural network. The presented path planning algorithm takes advantage of ellipsoid entities to represent obstacles and compute paths for small UAVs regardless of the concavity of these obstacles, in a very geometrically explicit way. Furthermore, our method can also be used to plan routes in dynamical environments without adding any computational cost.

scholarly journals Review on path planning algorithm for unmanned aerial vehicles

2021 ◽  
Vol 24 (2) ◽  
pp. 1017
Author(s):  
Nurul Saliha Amani Ibrahim ◽  
Faiz Asraf Saparudin
Keyword(s):  
Path Planning ◽  
Unmanned Aerial Vehicles ◽  
Autonomous Vehicles ◽  
Autonomous Vehicle ◽  
Optimal Path ◽  
Computation Time ◽  
Planning Problem ◽  
Aerial Vehicles ◽  
Planning Algorithm ◽  
Path Planning Algorithm

The path planning problem has been a crucial topic to be solved in autonomous vehicles. Path planning consists operations to find the route that passes through all of the points of interest in a given area. Several algorithms have been proposed and outlined in the various literature for the path planning of autonomous vehicle especially for unmanned aerial vehicles (UAV). The algorithms are not guaranteed to give full performance in each path planning cases but each one of them has their own specification which makes them suitable in sophisticated situation. This review paper evaluates several possible different path planning approaches of UAVs in terms optimal path, probabilistic completeness and computation time along with their application in specific problems.

Cooperative Search and Path Planning of Multi-Unmanned Aerial Vehicles in Uncertain Environment Based on Bayes Theory

2013 ◽  
Vol 336-338 ◽  
pp. 843-846 ◽  
Author(s):  
Xia Chen ◽  
Jing Zhang ◽  
Zhen Yu Lu
Keyword(s):  
Path Planning ◽  
Physical Properties ◽  
Unmanned Aerial Vehicles ◽  
Search Theory ◽  
A Algorithm ◽  
Uncertain Environment ◽  
Aerial Vehicles ◽  
Bayes Theory ◽  
Planning Algorithm ◽  
Path Planning Algorithm

In order to solve the question of cooperative searching target in uncertain environment, this paper comes up with a algorithm. Firstly it analysis the uncertainty about measure of UAV sensors and environment, we built the information model of uncertain environment. Then, considering about UAV physical properties and optimal search theory, it designs the award function, gives the path planning algorithm of cooperative searching based on the Bayes theory. The algorithm ensures that the UAV formation could search unknown environment as far as possible, evade the known environment and avoid no-fly zone completely. Finally, the simulation proves the rationality and effectiveness of algorithm.

scholarly journals Low-Complexity Path Planning Algorithm for Unmanned Aerial Vehicles in Complicated Scenarios

IEEE Access ◽  
2018 ◽  
Vol 6 ◽  
pp. 57049-57055 ◽  
Author(s):  
Zhiqiang Xiao ◽  
Bingcheng Zhu ◽  
Yongjin Wang ◽  
Pu Miao
Keyword(s):  
Path Planning ◽  
Unmanned Aerial Vehicles ◽  
Low Complexity ◽  
Aerial Vehicles ◽  
Planning Algorithm ◽  
Path Planning Algorithm

scholarly journals A Path-Planning Strategy for Unmanned Surface Vehicles Based on an Adaptive Hybrid Dynamic Stepsize and Target Attractive Force-RRT Algorithm

2019 ◽  
Vol 7 (5) ◽  
pp. 132 ◽  
Author(s):  
Zhen Zhang ◽  
Defeng Wu ◽  
Jiadong Gu ◽  
Fusheng Li
Keyword(s):  
Path Planning ◽  
High Speed ◽  
Attractive Force ◽  
Simulation Experiments ◽  
Planning Strategy ◽  
Unmanned Surface Vehicles ◽  
Planning Algorithm ◽  
Pass Through ◽  
Path Planning Algorithm ◽  
Narrow Area

It is well known that path planning has always been an important study area for intelligent ships, especially for unmanned surface vehicles (USVs). Therefore, it is necessary to study the path-planning algorithm for USVs. As one of the basic algorithms for USV path planning, the rapidly-exploring random tree (RRT) is popular due to its simple structure, high speed and ease of modification. However, it also has some obvious drawbacks and problems. Designed to perfect defects of the basic RRT and improve the performance of USVs, an enhanced algorithm of path planning is proposed in this study, called the adaptive hybrid dynamic stepsize and target attractive force-RRT(AHDSTAF-RRT). The ability to pass through a narrow area and the forward speed in open areas of USVs are improved by adopting the AHDSTAF-RRT in comparison to the basic RRT algorithm. The improved algorithm is also applied to an actual gulf map for simulation experiments, and the experimental data is collected and organized. Simulation experiments show that the proposed AHDSTAF-RRT in this paper outperforms several existing RRT algorithms, both in terms of path length and calculating speed.

A novel potential-based path planning of 3-D articulated robots with moving bases

Robotica ◽  
2004 ◽  
Vol 22 (4) ◽  
pp. 359-367 ◽  
Author(s):  
Chien-Chou Lin ◽  
Chi-Chun Pan ◽  
Jen-Hui Chuang
Keyword(s):  
Path Planning ◽  
Planning Strategy ◽  
Computation Efficiency ◽  
Planning Algorithm ◽  
Minimum Potential ◽  
Potential Gradients ◽  
Robot Configuration ◽  
Articulated Robots ◽  
Repulsive Forces ◽  
Path Planning Algorithm

This paper proposes a novel path planning algorithm of 3-D articulated robots with moving bases based on a generalized potential field model. The approach computes, similar to that done in electrostatics, repulsive forces and torques between charged objects. A collision-free path can be obtained by locally adjusting the robot configuration to search for minimum potential configurations using these forces and torques. The proposed approach is efficient since these potential gradients are analytically tractable. In order to speedup the computation, a sequential planning strategy is adopted. Simulation results show that the proposed algorithm works well, in terms of collision avoidance and computation efficiency.

scholarly journals An Efficient Energy Constraint Based UAV Path Planning for Search and Coverage

2017 ◽  
Vol 2017 ◽  
pp. 1-13 ◽  
Author(s):  
German Gramajo ◽  
Praveen Shankar
Keyword(s):  
Path Planning ◽  
Planning Strategy ◽  
Mission Duration ◽  
Terminal Constraints ◽  
Spatial Coverage ◽  
Small Uav ◽  
Optimization Parameters ◽  
Planning Algorithm ◽  
High Level ◽  
Path Planning Algorithm

A path planning strategy for a search and coverage mission for a small UAV that maximizes the area covered based on stored energy and maneuverability constraints is presented. The proposed formulation has a high level of autonomy, without requiring an exact choice of optimization parameters, and is appropriate for real-time implementation. The computed trajectory maximizes spatial coverage while closely satisfying terminal constraints on the position of the vehicle and minimizing the time of flight. Comparisons of this formulation to a path planning algorithm based on those with time constraint show equivalent coverage performance but improvement in prediction of overall mission duration and accuracy of the terminal position of the vehicle.

Motion and path planning of a novel multi-mode mobile parallel robot based on chessboard-shaped grid division

2018 ◽  
Vol 45 (3) ◽  
pp. 390-400 ◽  
Author(s):  
Zhaotian Wang ◽  
Yezhuo Li ◽  
Yan-An Yao
Keyword(s):  
Path Planning ◽  
Parallel Robot ◽  
Content Type ◽  
Planning Strategy ◽  
Planning Algorithm ◽  
Rolling Mode ◽  
Path Planning Algorithm ◽  
Grid Division ◽  
Multi Mode ◽  
Motion Strategy

Purpose The purpose of this paper is to put forward a rolling assistant robot with two rolling modes, and the multi-mode rolling motion strategy with path planning algorithm, which is suitable to this multi-mode mobile robot, is proposed based on chessboard-shaped grid division (CGD). Design/methodology/approach Based on the kinematic analysis and motion properties of the mobile parallel robot, the motion strategy based on CGD path planning algorithm of a mobile robot with two rolling modes moving to a target position is divided into two parts, which are local self-motion planning and global path planning. In the first part, the mobile parallel robot can move by switching and combining the two rolling modes; and in the second part, the specific algorithm of the global path planning is proposed according to the CGD of the moving ground. Findings The assistant robot, which is a novel 4-RSR mobile parallel robot (where R denotes a revolute joint and S denotes a spherical joint) integrating operation and rolling locomotion (Watt linkage rolling mode and 6R linkage rolling mode), can work as a moving spotlight or worktable. A series of simulation and prototype experiment results are presented to verify the CGD path planning strategy of the robot, and the performance of the path planning experiments in simulations and practices shows the validation of the path planning analysis. Originality/value The work presented in this paper is a further exploration to apply parallel mechanisms with two rolling modes to the field of assistant rolling robots by proposing the CGD path planning strategy. It is also a new attempt to use the specific path planning algorithm in the field of mobile robots for operating tasks.

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