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Journal ArticleDOI

Path planning algorithm for unmanned surface vehicle formations in a practical maritime environment

15 Mar 2015-Ocean Engineering (Pergamon)-Vol. 97, pp 126-144
TL;DR: A novel computer based algorithm that solves the problem of USV formation path planning using the fast marching (FM) method and has been specifically designed for operation in dynamic environments using the novel constrained FM method.
About: This article is published in Ocean Engineering.The article was published on 2015-03-15 and is currently open access. It has received 196 citations till now. The article focuses on the topics: Payload & Motion planning.

Summary (2 min read)

1. Introduction

  • Section 2 reviews related work in terms of formation path planning.
  • Sections 3 and 4 describe fundamentals of the method used in this paper as well as the algorithm which models static and dynamic obstacles.
  • Section 5 introduces the USV formation path planning algorithm.
  • Proposed algorithm and methods are verified by simulations in section 6.
  • Section 7 concludes the paper and discusses the future work.

2. Literature review

  • Due to limited resources studying USV formation path planning, and also in order to give a more thorough review of the current research situation; literature from not only USV, but also UAV, UGV and unmanned underwater vehicle (UUV) have been reviewed in this section.
  • For simplicity, the authors have named all kinds of autonomous vehicle as 'unmanned vehicle' in following section.

2.1. Formation control structure

  • For unmanned vehicle formations, maintenance of the formation shape is of great importance.
  • To maintain the shape, several control structures including leaderfollower, virtual structure and behaviour based approaches have been proposed by a number of researchers.
  • Both of these approaches adopt a centralised control topology, where all the important control decisions are made within at the centre of the system.
  • It breaks down the formation tasks into several sub tasks according to different behaviours.

2.2. Multiple vehicles formation path planning

  • The authors improve upon the work of Gomez et al. (2013) and developing its application specifically for USV formation with emphasis on path planning in a dynamic environment.
  • A new constrained FM method is proposed to model the dynamic behaviour of moving ships for collision avoidance.
  • In addition, path replanning capability is incorporated to improve the completeness of the algorithm.

4. Planning space representation

  • In path planning problems, safety always holds priority no matter what application.
  • It is espe-cially important for USV navigation environments, which include a great deal of maritime uncertainties.
  • Sufficient safe distance should always be maintained between USV and obstacles (both static and dynamic).
  • The FM based map representation method for both static environment and moving obstacles is described.

4.1. Static obstacles representation

  • USV's mission start point is now the algorithm's start point.
  • Since M s is used as a speed matrix in this step, which gives nonconstant speed over the space, the interface now tends to remain in places with high propagating speed.
  • The generated potential field should follow the trace of the interface, which is shown in Fig. 7b .
  • Potential of nearby obstacles is always higher than at other places', which act as a protecting layer to prevent the path passing too close to obstacles.

4.2. Dynamic obstacles representation

  • When two USVs are moving too close to each other from any direction, a repulsive force is needed to maintain safety.
  • Therefore, constrained FM method is still used here but with a circular shape to model formation USVs.

5. USV formation path planning

  • Once the leader's path is determined, the algorithm starts to iterate to compute paths for followers.
  • Similar procedures are followed; however, since follower's target points are re-planned during each time step, it is possible that the target point is located within the obstacle (see Fig. 12a ) such that the algorithm fails to find the path.

6. Simulations

  • In the simulations, the authors assume that identical USVs are used in formation.
  • Followers, however, can vary their speeds according to their positions in formation.
  • Follower USV needs to remain at the same velocity as leader's when it is moving at desired formation position.

6.1. Simulation in dynamic environment with one moving obstacle

  • Evaluations of the algorithm performance and USV formation behaviour are given in Fig. 15 .
  • Fig. 15a shows the overall trajectories for the formation, and all of them remain a safe distance away from static obstacles, which proves that the algorithm is able to generate acceptable safe paths in a complex environment.
  • Furthermore, in Fig. 15b , distances between TS and each USV are recorded.
  • It is noted that the closest distances for leader and two followers are approximately 21 pixels, 17 pixels and 25 pixels, which demonstrates that formation can effectively avoid moving obstacle.
  • It may be concluded that during initial time steps, large errors occur since two followers are not located at their desired positions.

6.2. Simulation in dynamic environment with multiple moving obstacles

  • Smallest distance occurs at time step 61 with the value of 11 pixels (55 m) between TS2 and follower1, which means that the formation does not collide with any target ships.
  • In terms of formation behaviour, Fig. 18c records the distance error values.
  • Except the initial formation generation stages, the values remain close to zero for most of simulation time, which means that the formation shape is well maintained.

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Citations
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Additional excerpts

  • ...Liu and Bucknall [14] suggested a constrained fast marching method to solve the problem of USV formation path planning in dynamic environments....

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  • ...Liu and Bucknall [14] suggested a constrained...

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References
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Journal ArticleDOI
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


"Path planning algorithm for unmanne..." refers methods in this paper

  • ...Based on the124 potential field, the vehicle can then be guided by following total field gradient.125 Detailed explanation of this can be referred to Khatib (1986) and Ge and Cui126 (2002).127 In terms of implementation of APF in formation path planning, besides potential128 fields around target…...

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Journal ArticleDOI
01 Dec 1998
TL;DR: New reactive behaviors that implement formations in multirobot teams are presented and evaluated and demonstrate the value of various types of formations in autonomous, human-led and communications-restricted applications, and their appropriateness in different types of task environments.
Abstract: New reactive behaviors that implement formations in multirobot teams are presented and evaluated. The formation behaviors are integrated with other navigational behaviors to enable a robotic team to reach navigational goals, avoid hazards and simultaneously remain in formation. The behaviors are implemented in simulation, on robots in the laboratory and aboard DARPA's HMMWV-based unmanned ground vehicles. The technique has been integrated with the autonomous robot architecture (AuRA) and the UGV Demo II architecture. The results demonstrate the value of various types of formations in autonomous, human-led and communications-restricted applications, and their appropriateness in different types of task environments.

3,008 citations


"Path planning algorithm for unmanne..." refers background in this paper

  • ...In 80 the work of Balch and Arkin (1998), formation maintenance is integrated with 81 other missions such as goal keeping and collision avoidance and the control of 82 each vehicle is the result of a weighted function of these missions....

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  • ...In80 the work of Balch and Arkin (1998), formation maintenance is integrated with81 other missions such as goal keeping and collision avoidance and the control of82 each vehicle is the result of a weighted function of these missions.83 2.2....

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Journal ArticleDOI
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


"Path planning algorithm for unmanne..." refers background or methods in this paper

  • ...125 Detailed explanation of this can be referred to Khatib (1986) and Ge and Cui 126 (2002). 127 In terms of implementation of APF in formation path planning, besides potential 128 fields around target point and obstacles, new fields need to be constructed to 129 keep formation distances as well as avoid collision between vehicles within the 130 formation. Wang et al. (2008) first constructed such potential fields by referring 131 to the concepts of electric field. Each vehicle was treated as point in the electric 132 field with varying electrical polarity. If the distance between vehicles was larger 133 than the expected value, opposite charges were used to attract them to move 134 towards each other; otherwise, like polarities were used to prevent them from 135 colliding when two vehicles were moving within close proximity. 136 Paul et al. (2008) also applied APF method to solve the problem of UAV forma137 tion path planning. Attractive fields between leader-follower as well as follower138 follower were built to keep formation shape, and repulsive fields were used to 139 prevent internal collision as well as collision with obstacles. To increase control 140 accuracy as well as to better address the formation shape maintenance prob141 lem, attractive potential field was a function of the error value between desired 142 distance and actual leader-follower or follower-follower distance such that any 143 deflection from the desired position can be quickly modified and corrected. 144 Yang et al. (2011) published work on motion planning for UUV formation in 145 an environment with obstacles based on APF....

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  • ...104 (2006), Kala (2012), Qu et al. (2013)), particle swarm optimisation (Duan et al....

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  • ...125 Detailed explanation of this can be referred to Khatib (1986) and Ge and Cui 126 (2002). 127 In terms of implementation of APF in formation path planning, besides potential 128 fields around target point and obstacles, new fields need to be constructed to 129 keep formation distances as well as avoid collision between vehicles within the 130 formation. Wang et al. (2008) first constructed such potential fields by referring 131 to the concepts of electric field....

    [...]

  • ...125 Detailed explanation of this can be referred to Khatib (1986) and Ge and Cui 126 (2002). 127 In terms of implementation of APF in formation path planning, besides potential 128 fields around target point and obstacles, new fields need to be constructed to 129 keep formation distances as well as avoid collision between vehicles within the 130 formation. Wang et al. (2008) first constructed such potential fields by referring 131 to the concepts of electric field. Each vehicle was treated as point in the electric 132 field with varying electrical polarity. If the distance between vehicles was larger 133 than the expected value, opposite charges were used to attract them to move 134 towards each other; otherwise, like polarities were used to prevent them from 135 colliding when two vehicles were moving within close proximity. 136 Paul et al. (2008) also applied APF method to solve the problem of UAV forma137 tion path planning....

    [...]

  • ...125 Detailed explanation of this can be referred to Khatib (1986) and Ge and Cui 126 (2002). 127 In terms of implementation of APF in formation path planning, besides potential 128 fields around target point and obstacles, new fields need to be constructed to 129 keep formation distances as well as avoid collision between vehicles within the 130 formation....

    [...]

Journal ArticleDOI
TL;DR: In this article, a leader-follower formation control of multiple underactuated autonomous underwater vehicles (AUVs) is proposed, where the follower tracks a reference trajectory based on the leader position and predetermined formation without the need for leader's velocity and dynamics.

566 citations

Journal ArticleDOI
TL;DR: In this article, the authors review the development of collision avoidance techniques and path planning for ships, particularly when engaged in close range encounters, and identify the'state of the art' and issues in close-range marine navigation.
Abstract: Efficient marine navigation through obstructions is still one of the many problems faced by the mariner. Many accidents can be traced to human error, recently increased traffic densities and the average cruise speed of ships impedes the collision avoidance decision making process further in the sense that decisions have to be made in reduced time. It seems logical that the decision making process be computerised and automated as a step forward to reduced the risk of collision. This article reviews the development of collision avoidance techniques and path planning for ships, particularly when engaged in close range encounters. In addition, previously published works have been categorised and their shortcomings highlighted in order to identify the 'state of the art' and issues in close range marine navigation.

221 citations


"Path planning algorithm for unmanne..." refers background in this paper

  • ...…defined steps to search98 for the solution whereas heuristic approach only searches inside a subspace of99 the search space without following rigorous procedures (Tam et al. (2009)) .100 Heuristic approach is designed to provide solutions when classic search methods101 fail to find exact solutions....

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Q1. What contributions have the authors mentioned in the paper "Path planning algorithm for unmanned surface vehicle formations in a practical maritime environment" ?

This paper presents a novel computer based algorithm that solves the problem of USV formation path planning.