Modelling and analysis of information-based target searching using mobile sensors

Hazra, Tanmoy; Nene, Manisha J.; Kumar, Suthikshn

doi:10.1504/ijscc.2018.088336

Cited by 3 publications

(1 citation statement)

References 26 publications

(28 reference statements)

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“…Negotiation and calculation are common methods for resolving target hunting but can lead to delays in robotic action. [8][9][10] When the environments change, robot spends more time replanning the path, so these methods are not suitable for target hunting in a dynamic environments. Yamaguchi 11 studied the target hunting in dynamic environments based on Hilare-type mobile robot and solved the hunting problem using smooth time-varying feedback control method.…”

Section: Introductionmentioning

confidence: 99%

A leader–follower formation control approach for target hunting by multiple autonomous underwater vehicle in three-dimensional underwater environments

Cao

2019

International Journal of Advanced Robotic Systems

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As one of the challenging tasks of multiple autonomous underwater vehicles systems, the realization of target hunting is the great significance. The multiple autonomous underwater vehicle target hunting is studied in this article. In some research, because the hunting members cannot reach the hunting point at the same time, the hunting time is long or the target escapes. To improve the efficiency of the target hunting, the leader–follower formation algorithm is introduced. Firstly, the task is assigned based on the distance between the autonomous underwater vehicle and the target. Then, the autonomous underwater vehicles with the same task are formed based on leader–follower mode, and the formation is kept to track the target. In the final capture phase, multiple autonomous underwater vehicle system use angle matching algorithm to round up target. The simulation results show that the proposed algorithm can effectively accomplish the target hunting task, save the hunting time, and avoid the target escape. Compared with the bioinspired neural network algorithm, the proposed algorithm shows better performance.

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Section: Introductionmentioning

confidence: 99%

A leader–follower formation control approach for target hunting by multiple autonomous underwater vehicle in three-dimensional underwater environments

Cao

2019

International Journal of Advanced Robotic Systems

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Target Search Control of AUV in Underwater Environment With Deep Reinforcement Learning

Cao¹,

Sun²,

Yan³

2019

IEEE Access

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The autonomous underwater vehicle (AUV) is widely used to search for unknown targets in the complex underwater environment. Due to the unpredictability of the underwater environment, this paper combines the traditional frontier exploration method with deep reinforcement learning (DRL) to enable the AUV to explore the unknown underwater environment autonomously. In this paper, a grid map of the search environment is built by the grid method. The designed asynchronous advantage actor-critic (A3C) network structure is used in the traditional frontier exploration method for target search tasks. This network structure enables the AUV to learn from its own experience and generate search strategies for the various unknown environment. At the same time, DRL and dual-stream Q-learning algorithms are used for AUV navigation to further optimize the search path. The simulations and experiments in an unknown underwater environment with different layouts show that the proposed algorithm can accomplish target search tasks with a high success rate, and it can adapt to different environments. In addition, compared to other search methods, the frontier exploration algorithm based on DRL can search a wider environment faster, which results in a higher search efficiency and reduced search time.INDEX TERMS Target search, frontier exploration, deep learning, reinforcement learning.

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The object detection by autonomous apparatus as a solution of the Buffon needle problem

Гузев

Tsitsiashvili

Osipova

2019

Math. Mech. Compl. Sys.

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The problem of object detection by autonomous apparatus is considered. The probabilistic formulation of the problem is proposed by means of a reduction to the classical Buffon problem. The latter naturally arises when the problem is formulated in the coordinate system associated with the apparatus. The problem of detection is considered for devices moving in the open space along a circle around one body, for vehicles patrolling along the linear boundary protecting the bodies, and for devices protecting the system of bodies. The problem of object detection was shown to admit an analysis in the presence of an asymptotic parameter determined by the ratio of the local size of the apparatus scanning area to the global size of the problem under consideration. For all problems, the minimum number of apparatuses that could detect a penetrating object with probability one was calculated.

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Modelling and analysis of information-based target searching using mobile sensors

Cited by 3 publications

References 26 publications

A leader–follower formation control approach for target hunting by multiple autonomous underwater vehicle in three-dimensional underwater environments

A leader–follower formation control approach for target hunting by multiple autonomous underwater vehicle in three-dimensional underwater environments

Target Search Control of AUV in Underwater Environment With Deep Reinforcement Learning

The object detection by autonomous apparatus as a solution of the Buffon needle problem

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