Neural network-based method for swarm robots to realize cooperative foraging through using pheromone-based communication

A neural network, swarm robot technology, applied in the direction of instruments, general control systems, comprehensive factory control, etc., can solve the problem that multi-robot behavior learning is not well solved, to promote local communication, accelerate the emergence process, and automatically optimize. Effects of paths and actions

Active Publication Date: 2019-01-25
SHANDONG UNIV
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Problems solved by technology

[0007] Although researchers have achieved a lot of fruitful research results in swarm intelligent robotics, some problems of multi-robot behavior learning have not been well solved in theory. As a research field, the theoretical framework of swarm intelligent robotics and implementation methods need to be further improved

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  • Neural network-based method for swarm robots to realize cooperative foraging through using pheromone-based communication
  • Neural network-based method for swarm robots to realize cooperative foraging through using pheromone-based communication
  • Neural network-based method for swarm robots to realize cooperative foraging through using pheromone-based communication

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Embodiment

[0112] Example: Simulation experiment of swarm robot collaborative foraging

[0113] In order to illustrate the realization method of pheromone communication among swarm robots based on neural network, a simulation experiment was carried out on the mobile robot environment modeling and exploration software platform established in the laboratory. The nest of the foraging robot is located in the lower left corner of the working space. The robot starts to search for food sources from the nest. The food source is located in the upper right corner of the working environment. As shown in Figure 4(a), the gray rectangle is movable obstacle. The repulsive pheromone P released by the search robot (circle) according to equation (1) "discrete-time dynamic equation of the i-th neuron" o and P e Gradually attenuates and propagates to the entire workspace, as shown in Figure 4(b), the repelling pheromone P o and P e The area of ​​is the area that the robot has already searched, and the ...

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Abstract

The invention relates to a neural network-based method for swarm robots to realize cooperative foraging through using pheromone-based communication. The method includes the following steps that: a neural network model is established; a pheromone volatilization model is designed; and a system overall behavior framework model is established. According to the method of the invention, the pheromone volatilization model of swarm robot cooperative foraging behaviors is put forward and is defined as Ii(t), that is, the external input of an i-th neuron at a time t, and in the formula, an attracting pheromone Pa has a large positive value, a repulsion pheromone Po and a repulsion pheromone Pe have small negative values; when a foraging robot finds food and transports the food back to a nest, the foraging robot releases the attracting pheromone Pa; when the robot avoids an obstacle, the robot releases the repulsion pheromone Po; when the robot searches for food randomly in a working environment,the robot releases the repulsion pheromone Pe; the neural network updates output at any time according to the change of the Ii(t); and the evolution of the neural network enables the swarm robots tocommunicate locally, and witness self-organized group behaviors during an interaction process.

Description

technical field [0001] The invention relates to a method for the emergence of self-organizing behaviors of swarm intelligent robots. A neural network is used to establish a pheromone model. Robots emerge swarm intelligent behaviors through local interaction. A method of communication enabling collaborative foraging. Background technique [0002] The research on multi-robot systems began in the late 1970s. Researchers applied the multi-agent theory in artificial intelligence to multi-robot systems, and began the research on multi-robot technology in the field of robotics. The initial research mainly focused on system architecture, multi-robot motion planning, and system reconfigurability. With the introduction of theories and methods in research fields such as distributed artificial intelligence, complex systems, sociology, and biology, many The research on robotic systems began to explore key theoretical and technical issues such as system organization, information interact...

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Application Information

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IPC IPC(8): G05B19/418
CPCG05B19/41885Y02P90/02
Inventor 宋勇李贻斌方兴李彩虹刘海
Owner SHANDONG UNIV
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