scholarly journals A random sampling based algorithm for ship path planning with obstacles

Author(s):  
R Zaccone ◽  
M Martelli

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. 

Robotica ◽  
2021 ◽  
pp. 1-30
Author(s):  
Ümit Yerlikaya ◽  
R.Tuna Balkan

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.


2021 ◽  
Vol 2113 (1) ◽  
pp. 012002
Author(s):  
Zhuokai Wu

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.


Author(s):  
Letian Lin ◽  
J. Jim Zhu

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.


Mathematics ◽  
2018 ◽  
Vol 6 (10) ◽  
pp. 175 ◽  
Author(s):  
Yongtao Li ◽  
Yu Wu ◽  
Xichao Su ◽  
Jingyu Song

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.


Author(s):  
Hongying Shan ◽  
Chuang Wang ◽  
Cungang Zou ◽  
Mengyao Qin

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.


Robotica ◽  
1997 ◽  
Vol 15 (2) ◽  
pp. 213-224 ◽  
Author(s):  
Andreas C. Nearchou ◽  
Nikos A. Aspragathos

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.


Author(s):  
Nurul Saliha Amani Ibrahim ◽  
Faiz Asraf Saparudin

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.


Author(s):  
Yu Wu ◽  
Shaobo Wu ◽  
Xinting Hu

AbstractDifferent from the usual surveillance task in which the goal is to achieve complete coverage of the specified area, the cooperative path planning problem of drones for persistent surveillance task is studied in this paper considering multiple constraints of the covered area. The goal is to maximize the combinational coverage area of drones while giving preference to the area that hasn’t been visited beyond a certain time interval. The influence of shooting resolution and blocking of buildings are considered, and the state information of each grid is defined to record the visit information of the ground area. Considering the characteristic of the established model, the multi-constrained cooperative path planning (MCCPP) algorithm is developed. The grids which have not been visited for a long time are received special attentions, and the drone is led to reducing the flight height to cover the gird which has a special requirement on the shooting resolution. The cooperation mechanism among drones is also set to ensure that all the drones can determine the next path point synchronously. An emergency path planning algorithm with the continuous checking strategy is designed for a drone to fly to the specified area and finish a complete coverage of it.


Author(s):  
Yu Wu ◽  
Haixu Li ◽  
Xichao Su

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.


Author(s):  
Arturo De Marinis ◽  
Felice Iavernaro ◽  
Francesca Mazzia

AbstractIn this article, we present a new strategy to determine an unmanned aerial vehicle trajectory that minimizes its flight time in presence of avoidance areas and obstacles. The method combines classical results from optimal control theory, i.e. the Euler-Lagrange Theorem and the Pontryagin Minimum Principle, with a continuation technique that dynamically adapts the solution curve to the presence of obstacles. We initially consider the two-dimensional path planning problem and then move to the three-dimensional one, and include numerical illustrations for both cases to show the efficiency of our approach.


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