scholarly journals Path Planning for Autonomous Landing of Helicopter on the Aircraft Carrier

Mathematics ◽  
2018 ◽  
Vol 6 (10) ◽  
pp. 178 ◽  
Author(s):  
Hanjie Hu ◽  
Yu Wu ◽  
Jinfa Xu ◽  
Qingyun Sun
Keyword(s):  
Path Planning ◽  
Vertical Motion ◽  
Planning Problem ◽  
Aircraft Carrier ◽  
Autonomous Landing ◽  
Planning Algorithm ◽  
Two Phases ◽  
The Impact ◽  
Flight Deck ◽  
Path Planning Problem

Helicopters are introduced on the aircraft carrier to perform the tasks which are beyond the capability of fixed-wing aircraft. Unlike fixed-wing aircraft, the landing path of helicopters is not regulated and can be determined autonomously, and the path planning problem for autonomous landing of helicopters on the carrier is studied in this paper. To solve the problem, the returning flight is divided into two phases, that is, approaching the carrier and landing on the flight deck. The feature of each phase is depicted, and the conceptual model is built on this basis to provide a general frame and idea of solving the problem. In the established mathematical model, the path planning problem is formulated into an optimization problem, and the constraints are classified by the characteristics of the helicopter and the task requirements. The goal is to reduce the terminal position error and the impact between the helicopter and the flight deck. To obtain a reasonable landing path, a multiphase path planning algorithm with the pigeon inspired optimization (MPPIO) algorithm is proposed to adapt to the changing environment. Three experiments under different situations, that is, static carrier, only horizontal motion of carrier considered, and 3D motion of carrier considered, are conducted. The results demonstrate that the helicopters can all reach the ideal landing point with the reasonable path in different situations. The small terminal error and relatively vertical motion between the helicopter and the carrier ensure a precise and safe landing.

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.

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.

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 A random sampling based algorithm for ship path planning with obstacles

2018 ◽  
Author(s):  
R Zaccone ◽  
M Martelli
Keyword(s):  
Path Planning ◽  
Time Domain ◽  
Random Sampling ◽  
Ad Hoc ◽  
Scientific Literature ◽  
Planning Problem ◽  
Planning Algorithm ◽  
Potential Benefits ◽  
Path Planning Algorithm ◽  
Path Planning Problem

The paper presents a path planning algorithm for ship guidance in presence of obstacles, based on an ad hoc modified version of the Rapidly-exploring Random Tree (RRT*) algorithm. The proposed approach is designed to be part of a decision support system for the bridge operators, in order to enhance traditional navigation. Focusing on the maritime field, a review of the scientific literature dealing with motion planning is presented, showing potential benefits and weaknesses of the different approaches. Among the several methods, details on RRT and RRT* algorithms are given. The ship path planning problem is introduced and discussed, formulating suitable cost functions and taking into account both topological and kinematic constraints. Eventually, an existing time domain ship simulator is used to test the effectiveness of the proposed algorithm over a number of realistic operation scenarios. The obtained results are presented and critically discussed. 

scholarly journals Decentralized Path Planning for Multi-Objective Robot Swarm System

2021 ◽  
Vol 2113 (1) ◽  
pp. 012002
Author(s):  
Zhuokai Wu
Keyword(s):  
Path Planning ◽  
Obstacle Avoidance ◽  
Heuristic Algorithms ◽  
Optimization Problems ◽  
Planning Problem ◽  
Robot Swarm ◽  
Planning Algorithm ◽  
Path Planning Algorithm ◽  
Path Planning Problem ◽  
Multi Robot

Abstract The multi-robot path planning aims to explore a set of non-colliding paths with the shortest sum of lengths for multiple robots. The most popular approach is to artificially decompose the map into discrete small grids before applying heuristic algorithms. To solve the path planning in continuous environments, we propose a decentralized two-stage algorithm to solve the path-planning problem, where the obstacle and inter-robot collisions are both considered. In the first stage, an obstacle- avoidance path-planning problem is mathematically developed by minimizing the travel length of each robot. Specifically, the obstacle-avoidance trajectories are generated by approximating the obstacles as convex-concave constraints. In the second stage, with the given trajectories, we formulate a quadratic programming (QP) problem for velocity control using the control barrier and Lyapunov function (CBF-CLF). In this way, the multi-robot collision avoidance as well as time efficiency are satisfied by adapting the velocities of robots. In sharp contrast to the conventional heuristic methods, path length, smoothness and safety are fully considered by mathematically formulating the optimization problems in continuous environments. Extensive experiments as well as computer simulations are conducted to validate the effectiveness of the proposed path-planning algorithm.

Path Planning for Autonomous Car Parking

2018 ◽  
Author(s):  
Letian Lin ◽  
J. Jim Zhu
Keyword(s):  
Path Planning ◽  
Target Line ◽  
Planning Problem ◽  
Control Laws ◽  
Computational Costs ◽  
Planning Algorithm ◽  
Path Planner ◽  
Path Planning Algorithm ◽  
Path Planning Problem ◽  
Reverse Path

The path planning problem for autonomous car parking has been widely studied. However, it is challenging to design a path planner that can cope with parking in tight environment for all common parking scenarios. The important practical concerns in design, including low computational costs and little human’s knowledge and intervention, make the problem even more difficult. In this work, a path planner is developed using a novel four-phase algorithm. By using some switching control laws to drive two virtual cars to a target line, a forward path and a reverse path are obtained. Then the two paths are connected along the target line. As illustrated by the simulation results, the proposed path planning algorithm is fast, highly autonomous, sufficiently general and can be used in tight environment.

Path Planning for an Articulated Transporter/Manipulator System

1992 ◽  
Author(s):  
Shih-chien Chiang ◽  
Carl D. Crane ◽  
Joseph Duffy
Keyword(s):  
Path Planning ◽  
Hierarchical Structure ◽  
Planning Process ◽  
Three Dimensional ◽  
Vertical Motion ◽  
Working Environment ◽  
Planning Problem ◽  
Two Dimensional ◽  
Path Planning Problem

Abstract This work addresses the three dimensional path planning for an Articulated Transporter/Manipulator System (ATMS) in a given working environment. A vertical motion capability provides the ATMS a new ability which can be used to advantage in the generation of collision free paths. It also complicates the path planning process, however, by not being constrained to a 2D environment. A hierarchical structure of path planning is developed to decompose the three-dimensional path planning problem into several two-dimensional sub-problems.

scholarly journals Autonomous Vehicle Path Planning using Q-Learning

2021 ◽  
Vol 2128 (1) ◽  
pp. 012018
Author(s):  
Mohammed M S Ibrahim ◽  
Mostafa Rostom Atia ◽  
MW Fakhr
Keyword(s):  
Path Planning ◽  
Autonomous Vehicle ◽  
Optimal Path ◽  
Lookup Table ◽  
Planning Problem ◽  
Training Time ◽  
Q Learning ◽  
Starting Position ◽  
Planning Algorithm ◽  
Path Planning Problem

Abstract Path planning is vital in autonomous vehicle technology, from robots to self-driving cars and driverless trucks, it is impossible to navigate without a proper path planning algorithm, various algorithms exist Q-learning being one of them. Q-learning is used extensively in discrete applications as it is effective in finding solutions to these problems. This research investigates the possibility of using Q-learning for solving the local path planning problem with obstacle avoidance. Q-learning is split into two phases, the first being the training phase, and the second being the application phase. During training, Q-learning requires exponentially increasing training time based on the system’s state space. However, when Q-learning is applied it becomes as simple as a lookup table which allows it to run on even the simplest microcontrollers. Two simulations are conducted with varying environments. One to showcase the ability to learn the optimal path, the other to showcase the ability for learning navigation in variable environments. The first simulation was run on a static environment with one obstacle, with enough training episodes, Q-learning could solve the path planning problem with minimal movement steps. The second simulation focuses on a randomized environment, obstacles and the agent’s starting position are randomly chosen at the start of every episode. During testing, Q-learning was able to find a path to the target when a path did exist, as It was possible in certain configurations for the vehicle to be stuck in between obstacles with no feasible path or solution.

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