Cooperative AUV motion planning using terrain information

Häusler, Andreas J.; Saccon, Alessandro; Pascoal, António; Hauser, John; Aguiar, A. Pedro

doi:10.1109/oceans-bergen.2013.6608137

Cited by 11 publications

(9 citation statements)

References 31 publications

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“…On a complementary line of work, Hausler et al (2013) developed path planning algorithms that along choose a suitable vehicle path that maximizes the amount terrain information. His approach involves on an initial phase an instantiation of an A * algorithm, on which the cost criterion to maximize is related to the integral of the magnitude of the terrain gradient along its trajectory.…”

Section: ∼2000mentioning

confidence: 99%

Survey on advances on terrain based navigation for autonomous underwater vehicles

2017

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The autonomy of robotic underwater vehicles is dependent on the ability to perform long-term and long-range missions without need of human intervention. While current state-of-the-art underwater navigation techniques are able to provide sufficient levels of precision in positioning, they require the use of support vessels or acoustic beacons. This can pose limitations on the size of the survey area, but also on the whole cost of the operations. Terrain Based Navigation is a sensor-based navigation technique that bounds the error growth of deadreckoning using a map with terrain information, provided that there is enough terrain variability. An obvious advantage of Terrain Based Navigation is the fact that no external aiding signals or devices are required. Because of this unique feature, terrain navigation has the potential to dramatically improve the autonomy of Autonomous Underwater Vehicles (AUVs). This paper consists on a comprehensive survey on the recent developments for Terrain Based Navigation methods proposed for AUVs. The survey includes a brief introduction to the original Terrain Based Navigation formulations, as well as a description of the algorithms, and a list of the different implementation alternatives found in the literature. Additionally, and due to the relevance, Bathymetric SLAM techniques will also be discussed.

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Section: ∼2000mentioning

confidence: 99%

Survey on advances on terrain based navigation for autonomous underwater vehicles

2017

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“…We compare the quantitative method proposed in this article with the two commonly used terrain adaptation quantization methods (topographic entropy and topographic standard deviation). 10,18,19 The expressions of topographic entropy and topographic standard deviation are as follows: In the equation, the number of nodes that measure the terrain is m Â n and, ði; jÞ is the index number that represents the measurement of a topographic node.…”

Section: Comparison Of Commonly Quantitative Parametersmentioning

confidence: 99%

“…For example, the waypoints selected are based on the binary-tree search algorithm, 18 and the terrain matching navigation method based on the A*. [19][20][21] It is worth noting that the key to TRN path planning include two prerequisites: (1) suitability quantization and (2) division of suitable area and unsuitable area. Therefore, this study is mainly to solve these two problems.…”

Section: Introductionmentioning

confidence: 99%

Underwater digital elevation map gridding method based on optimal partition of suitable matching area

Wang

et al. 2019

International Journal of Advanced Robotic Systems

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Global positioning system signal does not penetrate into the water volume, and autonomous underwater vehicle have to use the inertial navigation system that will cause an inevitable cumulative error. Terrain reference position can zero out the inertial navigation system error and have been widely used. To improve the positioning accuracy, the planning path of the underwater robot is required to pass through the suitable matching areas in the path planning stage. So, a gridding map is needed to quantify the suitability of the terrain and to partition the suitable matching area and the unsuitable matching area optimally. In this article, we will focus on the quantitative method of terrain suitability and the grid parameter solution method for optimal partition of suitable matching area. Finally, the validity of the algorithm is obtained using the ship borne data. The results show that in the low suitability blocks, the influence of measurement error on terrain reference position accuracy is higher than that in high suitability blocks. And the average of terrain reference position deviation obtained of the path passed through the high suitability area is 53.3% which is lower than that of the path passed through the low suitability area, and the standard deviation of the position deviation is reduced by 21.15%.

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“…Homogeneous fleets consist of a node network of clone vehicles. SWARM relative localisation algorithms (Delight, Ramakrishnan, Zambrano, & MacCready, ; Saska, ), leader–follower algorithms, coordinated path following algorithms (Aguiar & Pascoal, ; Häusler, Saccon, Pascoal, Hauser, & Aguiar, ; Xargay et al, ), and a leapfrogging method (Matsuda, Maki, Sakamaki, & Ura, ) are best suited to the organisation of homogeneous fleets.…”

Section: Cooperation or Collaboration: Nuances In Multirobot Systems mentioning

confidence: 99%

Review of mission planning for autonomous marine vehicle fleets

Thompson

Guihen

2018

Journal of Field Robotics

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The deployment of a fleet of autonomous marine vehicles (AMVs) allows for the parallelisation of missions, intervehicle support for longer deployment times, adaptability and redundancy to in situ mission changes, and effective use of the right vehicle for the right purpose. End users and operators of AMVs face challenges in planning complex missions due to the limitations of their vehicles, dynamic, operationally constrictive, and unstructured environments, and in minimising risks to equipment, the mission, and personnel. Automated mission planning for AMV fleets can be a tool to reduce the complexity of programming vehicle tasking, and to perform validity assessments for end user-specified goals, allowing the operator to focus on risk assessment. We present a critical review of the current advances in automated planning for AMV fleets, investigating the limitations of available state-ofthe-art tools and providing a road map of the goals and challenges based on analysis of field reports and end user initiatives.

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Cooperative AUV motion planning using terrain information

Cited by 11 publications

References 31 publications

Survey on advances on terrain based navigation for autonomous underwater vehicles

Survey on advances on terrain based navigation for autonomous underwater vehicles

Underwater digital elevation map gridding method based on optimal partition of suitable matching area

Review of mission planning for autonomous marine vehicle fleets

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