Task Allocation of Rescue Robots based on Path optimization in Chemical Disaster Environment
| Autor: | Yingqiu Xu, Ziyan Lin, Yingzi Tan |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
Rescue robot
Computer science Distributed computing Ant colony optimization algorithms 020208 electrical & electronic engineering 010401 analytical chemistry 02 engineering and technology 01 natural sciences 0104 chemical sciences Task (project management) Genetic algorithm Shortest path problem Path (graph theory) 0202 electrical engineering electronic engineering information engineering Robot Motion planning |
| Zdroj: | 2020 IEEE International Conference on Mechatronics and Automation (ICMA). |
| DOI: | 10.1109/icma49215.2020.9233645 |
| Popis: | Chemical disaster events are characterized by suddenness, danger and variability, while robots are inefficient and unsafe in path planning and task allocation under special and blocked chemical environment. In order to improve rescue speed and safety, combining the characteristics of the environment, a task framework for rescue robots is proposed in the paper. The improved ant colony algorithm is used to obtain the shortest path plan. The result of the shortest path is used in the task allocation process. A task allocation model with the goal of minimum time is proposed and solved by genetic algorithm with elite strategy (EGA). The simulation results show that the method proposed in this paper can be well adapted to the chemical disaster environment, and provides a better or sub-optimal solution for the task allocation problem of rescue robots. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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