A path planning model of a tiltrotor for approaching an aircraft carrier during landing

2021 ◽  
pp. 095441002199649
Author(s):  
Yu Wu ◽  
Haixu Li ◽  
Xichao Su
Keyword(s):  
Path Planning ◽  
Target Point ◽  
Planning Problem ◽  
Planning Model ◽  
State Variables ◽  
Aircraft Carrier ◽  
Control Variables ◽  
Planning Algorithm ◽  
Path Search ◽  
Path Planning Algorithm

A path planning model concerning a tiltrotor approaching an aircraft carrier is established in this study. In the model, the characteristic of the tiltrotor, the landing task, and the environment of the carrier are taken into account. First, the motion equations and the maneuverability of the tiltrotor in each flight mode are presented, and the constraints of control variables and flight envelope are given. The returning flight of the tiltrotor is divided into three phases corresponding to the three flight modes of the tiltrotor, and the constraints in each phase and the goal are set. Considering the flight safety of the tiltrotor, the environment of the carrier is described as flyable space and no-fly zones, and the no-fly zones are set taking the influences of turbulence and wind field induced by the moving aircraft carrier into account. The path planning issue is formulated into an optimization problem under the constraints of control variables and state variables. According to the characteristic of the established model, a pigeon inspired optimization (PIO)-based path planning algorithm is developed integrating the “step-by-step” and “one effort” path search strategies. Simulation results demonstrate that the tiltrotor can reach the target point with a reasonable landing path. Comparison among different algorithms is also conducted to verify that the PIO algorithm is capable of solving this online path planning problem.

scholarly journals Path Planning for Aircraft Fleet Launching on the Flight Deck of Carriers

Mathematics ◽  
2018 ◽  
Vol 6 (10) ◽  
pp. 175 ◽  
Author(s):  
Yongtao Li ◽  
Yu Wu ◽  
Xichao Su ◽  
Jingyu Song
Keyword(s):  
Path Planning ◽  
Collision Detection ◽  
Planning Problem ◽  
Aircraft Carrier ◽  
Planning Algorithm ◽  
Rolling Optimization ◽  
Path Planner ◽  
Path Planning Algorithm ◽  
Flight Deck ◽  
Path Planning Problem

This paper studies the path planning problem for aircraft fleet taxiing on the flight deck of carriers, which is of great significance for improving the safety and efficiency level of launching. As there are various defects of manual command in the flight deck operation of carriers, the establishment of an automatic path planner for aircraft fleets is imperative. The requirements of launching, the particularities of the flight deck environment, the way of launch, and the work mode of catapult were analyzed. On this basis, a mathematical model was established which contains the constraints of maneuverability and the work mode of catapults; the ground motion and collision detection of aircraft are also taken into account. In the design of path planning algorithm, path tracking was combined with path planning, and the strategy of rolling optimization was applied to get the actual taxi path of each aircraft. Taking the Nimitz-class aircraft carrier as an example, the taxi paths of aircraft fleet launching was planned with the proposed method. This research can guarantee that the aircraft fleet complete launching missions safely with reasonable taxi paths.

scholarly journals A 2D Optimal Path Planning Algorithm for Autonomous Underwater Vehicle Driving in Unknown Underwater Canyons

2021 ◽  
Vol 9 (3) ◽  
pp. 252
Author(s):  
Yushan Sun ◽  
Xiaokun Luo ◽  
Xiangrui Ran ◽  
Guocheng Zhang
Keyword(s):  
Path Planning ◽  
Obstacle Avoidance ◽  
Autonomous Underwater Vehicles ◽  
Optimal Path ◽  
Small Scale ◽  
Target Point ◽  
Safe Driving ◽  
Policy Gradient ◽  
Planning Algorithm ◽  
Path Planning Algorithm

This research aims to solve the safe navigation problem of autonomous underwater vehicles (AUVs) in deep ocean, which is a complex and changeable environment with various mountains. When an AUV reaches the deep sea navigation, it encounters many underwater canyons, and the hard valley walls threaten its safety seriously. To solve the problem on the safe driving of AUV in underwater canyons and address the potential of AUV autonomous obstacle avoidance in uncertain environments, an improved AUV path planning algorithm based on the deep deterministic policy gradient (DDPG) algorithm is proposed in this work. This method refers to an end-to-end path planning algorithm that optimizes the strategy directly. It takes sensor information as input and driving speed and yaw angle as outputs. The path planning algorithm can reach the predetermined target point while avoiding large-scale static obstacles, such as valley walls in the simulated underwater canyon environment, as well as sudden small-scale dynamic obstacles, such as marine life and other vehicles. In addition, this research aims at the multi-objective structure of the obstacle avoidance of path planning, modularized reward function design, and combined artificial potential field method to set continuous rewards. This research also proposes a new algorithm called deep SumTree-deterministic policy gradient algorithm (SumTree-DDPG), which improves the random storage and extraction strategy of DDPG algorithm experience samples. According to the importance of the experience samples, the samples are classified and stored in combination with the SumTree structure, high-quality samples are extracted continuously, and SumTree-DDPG algorithm finally improves the speed of the convergence model. Finally, this research uses Python language to write an underwater canyon simulation environment and builds a deep reinforcement learning simulation platform on a high-performance computer to conduct simulation learning training for AUV. Data simulation verified that the proposed path planning method can guide the under-actuated underwater robot to navigate to the target without colliding with any obstacles. In comparison with the DDPG algorithm, the stability, training’s total reward, and robustness of the improved Sumtree-DDPG algorithm planner in this study are better.

Research on pull-type multi-AGV system dynamic path optimization based on time window

2021 ◽  
pp. 095440702098271
Author(s):  
Hongying Shan ◽  
Chuang Wang ◽  
Cungang Zou ◽  
Mengyao Qin
Keyword(s):  
Path Planning ◽  
Time Window ◽  
Planning Problem ◽  
Dijkstra Algorithm ◽  
Before And After ◽  
Common Planning ◽  
Planning Algorithm ◽  
Dynamic Path ◽  
Set Up ◽  
Path Planning Algorithm

This paper is a study of the dynamic path planning problem of the pull-type multiple Automated Guided Vehicle (multi-AGV) complex system. First, based on research status at home and abroad, the conflict types, common planning algorithms, and task scheduling methods of different AGV complex systems are compared and analyzed. After comparing the different algorithms, the Dijkstra algorithm was selected as the path planning algorithm. Secondly, a mathematical model is set up for the shortest path of the total driving path, and a general algorithm for multi-AGV collision-free path planning based on a time window is proposed. After a thorough study of the shortcomings of traditional single-car planning and conflict resolution algorithms, a time window improvement algorithm for the planning path and the solution of the path conflict covariance is established. Experiments on VC++ software showed that the improved algorithm reduces the time of path planning and improves the punctual delivery rate of tasks. Finally, the algorithm is applied to material distribution in the OSIS workshop of a C enterprise company. It can be determined that the method is feasible in the actual production and has a certain application value by the improvement of the data before and after the comparison.

Collision-Free Motion Planning for an Aligned Multiple-turret System Operating in Extreme Environment

Robotica ◽  
2021 ◽  
pp. 1-30
Author(s):  
Ümit Yerlikaya ◽  
R.Tuna Balkan
Keyword(s):  
Path Planning ◽  
Extreme Environment ◽  
Configuration Spaces ◽  
Planning Problem ◽  
Different Types ◽  
Planning Algorithm ◽  
Line Path ◽  
Path Planning Algorithm ◽  
Path Planning Problem ◽  
System Operating

Abstract Instead of using the tedious process of manual positioning, an off-line path planning algorithm has been developed for military turrets to improve their accuracy and efficiency. In the scope of this research, an algorithm is proposed to search a path in three different types of configuration spaces which are rectangular-, circular-, and torus-shaped by providing three converging options named as fast, medium, and optimum depending on the application. With the help of the proposed algorithm, 4-dimensional (D) path planning problem was realized as 2-D + 2-D by using six sequences and their options. The results obtained were simulated and no collision was observed between any bodies in these three options.

scholarly journals Path planning for automatic guided vehicle with multiple target points in dynamic environment

2018 ◽  
Vol 159 ◽  
pp. 02029 ◽  
Author(s):  
Chang Kyu Kim ◽  
Huy Hung Nguyen ◽  
Dae Hwan Kim ◽  
Hak Kyeong Kim ◽  
Sang Bong Kim
Keyword(s):  
Path Planning ◽  
Shortest Paths ◽  
Initial Point ◽  
Target Point ◽  
Laser Sensor ◽  
Multiple Target ◽  
Hamilton Path ◽  
Automatic Guided Vehicle ◽  
Planning Algorithm ◽  
Path Planning Algorithm

In path planning field, Automatic guided vehicle (AGV) has to move from an initial point towards a target point with capability to avoid obstacles. There are A*, D* and D* lite path planning algorithms in the path planning algorithm. This paper proposes a modified D* lite path planning algorithm using the most efficient D* lite among these algorithms. The modified D* lite path planning algorithm is to improve these D* lite path planning algorithm’s weaknesses such as traversing across obstacles sharp corners, or traversing between two obstacles. To do this task, the followings are done. First, a work space is divided into square cells. Second, cost of each edge connecting current node to neighbor nodes is calculated. Third, the shortest paths from the initial point to all multiple target points are computed and the shortest paths from any target point to remaining target points including the goal point are computed by using Hamilton path. Fourth, a cost-minimal path is re-calculated as soon as the laser sensor detects an obstacle and make an updated list of target points. Finally, the validity of the proposed modified D* lite path planning algorithm is verified through simulation and experimental results.

A smooth local path planning algorithm based on modified visibility graph

2017 ◽  
Vol 31 (19-21) ◽  
pp. 1740091 ◽  
Author(s):  
Taizhi Lv ◽  
Maoyan Feng
Keyword(s):  
Path Planning ◽  
Simulation Experiment ◽  
Visibility Graph ◽  
Local Path Planning ◽  
Spline Curves ◽  
Smooth Path ◽  
Planning Algorithm ◽  
Path Search ◽  
Local Path ◽  
Path Planning Algorithm

Path planning is an essential and inevitable problem in robotics. Trapping in local minima and discontinuities often exist in local path planning. To overcome these drawbacks, this paper presents a smooth path planning algorithm based on modified visibility graph. This algorithm consists of three steps: (1) polygons are generated from detected obstacles; (2) a collision-free path is found by simultaneous visibility graph construction and path search by A[Formula: see text] (SVGA); (3) the path is smoothed by B-spline curves and particle swarm optimization (PSO). Simulation experiment results show the effectiveness of this algorithm, and a smooth path can be found fleetly.

scholarly journals NPQ-RRT ∗ : An Improved RRT ∗ Approach to Hybrid Path Planning

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Zihan Yu ◽  
Linying Xiang
Keyword(s):  
Path Planning ◽  
Optimal Path ◽  
Research Direction ◽  
Random Trees ◽  
Target Point ◽  
Evaluation Function ◽  
Local Planning ◽  
Planning Algorithm ◽  
Window Approach ◽  
Path Planning Algorithm

In recent years, the path planning of robot has been a hot research direction, and multirobot formation has practical application prospect in our life. This article proposes a hybrid path planning algorithm applied to robot formation. The improved Rapidly Exploring Random Trees algorithm PQ-RRT ∗ with new distance evaluation function is used as a global planning algorithm to generate the initial global path. The determined parent nodes and child nodes are used as the starting points and target points of the local planning algorithm, respectively. The dynamic window approach is used as the local planning algorithm to avoid dynamic obstacles. At the same time, the algorithm restricts the movement of robots inside the formation to avoid internal collisions. The local optimal path is selected by the evaluation function containing the possibility of formation collision. Therefore, multiple mobile robots can quickly and safely reach the global target point in a complex environment with dynamic and static obstacles through the hybrid path planning algorithm. Numerical simulations are given to verify the effectiveness and superiority of the proposed hybrid path planning algorithm.

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.

A genetic path planning algorithm for redundant articulated robots

Robotica ◽  
1997 ◽  
Vol 15 (2) ◽  
pp. 213-224 ◽  
Author(s):  
Andreas C. Nearchou ◽  
Nikos A. Aspragathos
Keyword(s):  
Path Planning ◽  
Degrees Of Freedom ◽  
Target Location ◽  
Planning Problem ◽  
Worst Case ◽  
Pick And Place ◽  
Planning Algorithm ◽  
A New Technique ◽  
Articulated Robots ◽  
Path Planning Algorithm

In some daily tasks, such as pick and place, the robot is requested to reach with its hand tip a desired target location while it is operating in its environment. Such tasks become more complex in environments cluttered with obstacles, since the constraint for collision-free movement must be also taken into account. This paper presents a new technique based on genetic algorithms (GAs) to solve the path planning problem of articulated redundant robot manipulators. The efficiency of the proposed GA is demonstrated through multiple experiments carried out on several robots with redundant degrees-of-freedom. Finally, the computational complexity of the proposed solution is estimated, in the worst case.

scholarly journals Efficient robotic path planning algorithm based on artificial potential field

2021 ◽  
Vol 11 (6) ◽  
pp. 4840
Author(s):  
Elia Nadira Sabudin ◽  
Rosli Omar ◽  
Sanjoy Kumar Debnath ◽  
Muhammad Suhaimi Sulong
Keyword(s):  
Computational Complexity ◽  
Path Planning ◽  
Potential Field ◽  
Path Length ◽  
Computation Time ◽  
Cell Decomposition ◽  
Target Point ◽  
Planning Methods ◽  
Planning Algorithm ◽  
Path Planning Algorithm

<span lang="EN-US">Path planning is crucial for a robot to be able to reach a target point safely to accomplish a given mission. In path planning, three essential criteria have to be considered namely path length, computational complexity and completeness. Among established path planning methods are voronoi diagram (VD), cell decomposition (CD), probability roadmap (PRM), visibility graph (VG) and potential field (PF). The above-mentioned methods could not fulfill all three criteria simultaneously which limits their application in optimal and real-time path planning. This paper proposes a path PF-based planning algorithm called dynamic artificial PF (DAPF). The proposed algorithm is capable of eliminating the local minima that frequently occurs in the conventional PF while fulfilling the criterion of path planning. DAPF also integrates path pruning to shorten the planned path. In order to evaluate its performance, DAPF has been simulated and compared with VG in terms of path length and computational complexity. It is found that DAPF is consistent in generating paths with low computation time in obstacle-rich environments compared to VG. The paths produced also are nearly optimal with respect to VG.</span>

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