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In this paper, we consider the issue of transporting a certain number of goods by a team of mobile robots. The target is to minimize the total transportation time and keep a low energy consumption of the intelligent agents on assuring security and quality during the transportation process. The pivotal issue needs to be solved is how to assign tasks to individual robots in a more reasonable and efficient way. We present a novel solution by using an empirical-based heuristic planning strategy for the goods transportation by multiple robots. In contrast to previous approaches, this strategy is designed to plan the transportation task for each individual robot by estimating the production rate of goods based on multi-robot coordination. Our approach has been implemented and evaluated in simulation. The experimental results demonstrate that the completion time of the whole transportation mission can be significantly reduced and the energy consumption of robots can be kept at a low level of our heuristic planning strategy compared with the previous approach.
[INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI]
[INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI]
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 12 | |
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| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
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