Robot plume tracking method based on continuous state behavioral domain intensive learning

A continuous state, reinforcement learning technology, applied in neural learning methods, instruments, manipulators, etc., can solve problems such as high cost, less judgment, and inability to adapt to the environment.

Active Publication Date: 2018-02-23
TSINGHUA UNIV
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Problems solved by technology

First of all, there are few judgments, only to make corresponding actions based on whether the concentration is detected and the time when the signal is lost, without using other available information, such as the size and direction of the flow field, the position of the loss, and its own actions when it is lost, etc., which is not considered comprehensive enough
Secondly, the action of the robot in the plume flow is relatively simple

Method used

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  • Robot plume tracking method based on continuous state behavioral domain intensive learning
  • Robot plume tracking method based on continuous state behavioral domain intensive learning
  • Robot plume tracking method based on continuous state behavioral domain intensive learning

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Embodiment Construction

[0082] The robot plume tracking method based on reinforcement learning in the continuous state behavior domain proposed by the present invention will be further described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0083] The robot plume tracking method based on continuous state behavior domain reinforcement learning proposed by the present invention describes the robot plume tracking process by using sequence decision-making. At the initial moment, the underwater robot will obtain the current deep-sea environmental information, including signals detectable by sensors such as the current velocity in the deep sea and the concentration of hydrothermal plume signals. Combine these signals into the state vector required for single-step path planning, input the state vector into the current decision-making neural network, and the decision-making neural network outputs the direction of the robot at this moment. After the robot runs at a c...

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Abstract

The invention provides a robot plume tracking method based on continuous state behavioral domain intensive learning, which belongs to the field of underwater robot path planning. The robot plume tracking method is used for training an underwater robot in path planning for plume hydrothermal vent searching; the robot generates a state vector in every plume tracking and inputs the state vector intoa current decision-making neural network, the decision-making neural network outputs an advancing direction of the robot at the moment, and the robot updates a state vector at a new moment and judgeswhether the single-time plume tracking satisfies a termination condition after operating at a constant speed for a time period; when the termination condition is satisfied, the single-time plume tracking is finished, and the robot regenerates a new initial position; if the termination condition is not satisfied, the robot advances continuously at a next moment; and during the process, an intensivelearning algorithm is used for updating the decision-making neural network at each moment until the algorithm converges. The robot plume tracking method based on continuous state behavioral domain intensive learning has the advantages of fast learning speed and good convergence, can improve the flexibility of the robot tracking a plume hydrothermal vent, and reduces the searching cost.

Description

technical field [0001] The invention belongs to the field of underwater robot path planning, in particular to a robot plume tracking method based on continuous state behavior domain reinforcement learning. Background technique [0002] Deep-sea hydrothermal activities and their life phenomena are one of the major discoveries in marine science in the 20th century. Since deep-sea hydrothermal vents are closely related to seafloor spreading and polymetallic sulfide mineralization, and involve cutting-edge scientific issues such as the evolution of biological communities in hydrothermal environments, and the impact of hydrothermal activities on global climate change, etc. The study of deep-sea hydrothermal fluids has become a hot topic in ocean research. [0003] In order to further study deep-sea hydrothermal fluids, it is necessary to explore the location of unknown hydrothermal vents in the deep sea. Researchers have found that deep-sea hydrothermal vents will emit hydrothe...

Claims

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Application Information

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IPC IPC(8): G06K9/66G06N3/08B25J9/16
CPCG06N3/08B25J9/1664G06V30/194
Inventor 宋世吉牛绿茵
Owner TSINGHUA UNIV
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