A path planning approach based on multi-direction A* algorithm for ships navigating within wind farm waters
TL;DR: Simulation results indicate that the trajectory from 20-direction A* algorithm has similar path length with real cases while enhancing navigation safety to a large degree and making a trade-off between computation complexity and efficiency.
About: This article is published in Ocean Engineering.The article was published on 2019-07-15. It has received 69 citations till now. The article focuses on the topics: Offshore wind power & Wind power.
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TL;DR: In this paper, a path planning method based on the geometric A-star algorithm is introduced to avoid the problems of many nodes, long-distance and large turning angle, and these problems usually exist in the sawtooth and cross paths produced by the traditional A-Star algorithm.
Abstract: This research introduces a path planning method based on the geometric A-star algorithm. The whole approach is applied to an Automated Guided Vehicle (AGV) in order to avoid the problems of many nodes, long-distance and large turning angle, and these problems usually exist in the sawtooth and cross paths produced by the traditional A-star algorithm. First, a grid method models a port environment. Second, the nodes in the close-list are filtered by the functions $P\left ({{x,y} }\right)$ and $W\left ({{x,y} }\right)$ and the nodes that do not meet the requirements are removed to avoid the generation of irregular paths. Simultaneously, to enhance the stability of the AGV regarding turning paths, the polyline at the turning path is replaced by a cubic B-spline curve. The path planning experimental results applied to different scenarios and different specifications showed that compared with other seven different algorithms, the geometric A-star algorithm reduces the number of nodes by 10% ~ 40%, while the number of turns is reduced by 25%, the turning angle is reduced by 33.3%, and the total distance is reduced by 25.5%. Overall, the simulation results of the path planning confirmed the effectiveness of the geometric A-star algorithm.
102 citations
TL;DR: The research progress of path planning based on the multi-modality constraint is introduced and the research methods and classical algorithms, especially those applied to the Unmanned Surface Vehicle in every stage are reviewed.
59 citations
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TL;DR: In this article, the authors introduce the research progress of path planning based on the multi-modality constraint and point out some existing problems in every stage and suggest for future research, especially those applied to the Unmanned Surface Vehicle (USV).
Abstract: The essence of the path planning problems is multi-modality constraint. However, most of the current literature has not mentioned this issue. This paper introduces the research progress of path planning based on the multi-modality constraint. The path planning of multi-modality constraint research can be classified into three stages in terms of its basic ingredients (such as shape, kinematics and dynamics et al.): Route Planning, Trajectory Planning and Motion Planning. It then reviews the research methods and classical algorithms, especially those applied to the Unmanned Surface Vehicle (USV) in every stage. Finally, the paper points out some existing problems in every stage and suggestions for future research.
58 citations
TL;DR: In this article, the improved ant colony optimization-artificial potential field (ACO-APF) algorithm is proposed to improve path planning of USVs in dynamic environments, which is based on a grid map for both local and global path planning.
Abstract: Path planning is important to the efficiency and navigation safety of USV autonomous operation offshore. To improve path planning, this study proposes the improved ant colony optimization-artificial potential field (ACO-APF) algorithm, which is based on a grid map for both local and global path planning of USVs in dynamic environments. The improved ant colony optimization (ACO) mechanism is utilized to search for a globally optimal path from the starting point to the endpoint for a USV in a grid environment, and the improved artificial potential field (APF) algorithm is subsequently employed to avoid unknown obstacles during USV navigation. The primary contributions of this article are as follows: (1) this article proposes a new heuristic function, pheromone update rule, and dynamic pheromone volatilization factor to improve convergence and mitigate finding local optima with the traditional ant colony algorithm; (2) we propose an equipotential line outer tangent circle and redefine potential functions to eliminate goals unreachable by nearby obstacles (GNRONs) and local minimum problems, respectively; (3) to adapt the USV to a complex environment, this article proposes a dynamic early-warning step-size adjustment strategy in which the moving distance and safe obstacle avoidance range in each step are adjusted based on the complexity of the surrounding environment; (4) the improved ant colony optimization algorithm and artificial potential field algorithm are effectively combined to form the algorithm proposed in this article, which is verified as an effective solution for USV local and global path planning using a series of simulations. Finally, in contrast to most papers, we successfully perform field experiments to verify the feasibility and effectiveness of the proposed algorithm.
57 citations
TL;DR: In this article, an improved concept of the CADCA (Collision Avoidance Dynamic Critical Area) is introduced for the case of ship allision, which can be used to appoint a position of no-return in a close-quarters situation, so as to determine the time and distance of the last-minute maneuver.
40 citations
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TL;DR: How heuristic information from the problem domain can be incorporated into a formal mathematical theory of graph searching is described and an optimality property of a class of search strategies is demonstrated.
Abstract: Although the problem of determining the minimum cost path through a graph arises naturally in a number of interesting applications, there has been no underlying theory to guide the development of efficient search procedures. Moreover, there is no adequate conceptual framework within which the various ad hoc search strategies proposed to date can be compared. This paper describes how heuristic information from the problem domain can be incorporated into a formal mathematical theory of graph searching and demonstrates an optimality property of a class of search strategies.
10,366 citations
TL;DR: This paper reformulated the manipulator con trol problem as direct control of manipulator motion in operational space—the space in which the task is originally described—rather than as control of the task's corresponding joint space motion obtained only after geometric and geometric transformation.
Abstract: This paper presents a unique real-time obstacle avoidance approach for manipulators and mobile robots based on the artificial potential field concept. Collision avoidance, tradi tionally considered a high level planning problem, can be effectively distributed between different levels of control, al lowing real-time robot operations in a complex environment. This method has been extended to moving obstacles by using a time-varying artificial patential field. We have applied this obstacle avoidance scheme to robot arm mechanisms and have used a new approach to the general problem of real-time manipulator control. We reformulated the manipulator con trol problem as direct control of manipulator motion in oper ational space—the space in which the task is originally described—rather than as control of the task's corresponding joint space motion obtained only after geometric and kine matic transformation. Outside the obstacles' regions of influ ence, we caused the end effector to move in a straight line with an...
6,515 citations
01 Oct 1992
TL;DR: A methodology for exact robot motion planning and control that unifies the purely kinematic path planning problem with the lower level feedback controller design is presented.
Abstract: A methodology for exact robot motion planning and control that unifies the purely kinematic path planning problem with the lower level feedback controller design is presented. Complete information about a freespace and goal is encoded in the form of a special artificial potential function, called a navigation function, that connects the kinematic planning problem with the dynamic execution problem in a provably correct fashion. The navigation function automatically gives rise to a bounded-torque feedback controller for the robot's actuators that guarantees collision-free motion and convergence to the destination from almost all initial free configurations. A formula for navigation functions that guide a point-mass robot in a generalized sphere world is developed. The simplest member of this family is a space obtained by puncturing a disk by an arbitrary number of smaller disjoint disks representing obstacles. The other spaces are obtained from this model by a suitable coordinate transformation. Simulation results for planar scenarios are provided. >
1,912 citations
TL;DR: A new potential field method for motion planning of mobile robots in a dynamic environment where the target and the obstacles are moving is proposed and the problem of local minima is discussed.
Abstract: The potential field method is widely used for autonomous mobile robot path planning due to its elegant mathematical analysis and simplicity. However, most researches have been focused on solving the motion planning problem in a stationary environment where both targets and obstacles are stationary. This paper proposes a new potential field method for motion planning of mobile robots in a dynamic environment where the target and the obstacles are moving. Firstly, the new potential function and the corresponding virtual force are defined. Then, the problem of local minima is discussed. Finally, extensive computer simulations and hardware experiments are carried out to demonstrate the effectiveness of the dynamic motion planning schemes based on the new potential field method.
808 citations
TL;DR: This survey concentrates on heuristic-based algorithms in robot path planning which are comprised of neural network, fuzzy logic, nature inspired algorithms and hybrid algorithms.
450 citations