Optimizing Task Allocation in Nuclear Accidents Rescue Response Using Particle Swarm Optimization

2023 42nd Chinese Control Conference (CCC)（2023）

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Abstract

The environment after the nuclear power accident is complex, and it is difficult for rescue workers to enter the accident area safely and effectively rescue the survivors. The robot can replace the rescue workers to complete the rescue work efficiently. On this basis, a task allocation method for emergency multi-robot after nuclear power accident is proposed. First, according to the position and time window constraints of the task, a task sequencing method is proposed, and the inferior solution is eliminated according to the robot's ability constraints when generating the initial solution, so as to reduce the computational complexity. Then, considering that the task and robot number are nominal variables and discrete, a particle swarm optimization iteration method based on roulette wheel is used to solve the task assignment problem based on grouping. The experimental results show that this method can effectively shorten the rescue path and speed up the generation of task assignment scheme.

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Key words

task allocation,rescue,particle swarm optimization,roulette wheel selection

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We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
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