Reinforcement-Learning-Based Route Generation for Heavy-Traffic Autonomous Mobile Robot Systems
| Autor: | Rok Vrabič, Dominik Kozjek, Andreja Malus |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
autonomous mobile robots
reinforcement learning multi-robot cooperation Relation (database) Computer science Distributed computing Reliability (computer networking) Movement 02 engineering and technology TP1-1185 Space (commercial competition) Biochemistry udc:007.52(045) Article Analytical Chemistry 0203 mechanical engineering 0202 electrical engineering electronic engineering information engineering Reinforcement learning Learning Electrical and Electronic Engineering Instrumentation Throughput (business) Chemical technology intralogistics Reproducibility of Results 020302 automobile design & engineering Mobile robot Robotics Atomic and Molecular Physics and Optics spodbujevalno učenje route planning Robot 020201 artificial intelligence & image processing Route planning avtonomni mobilni roboti Algorithms intralogistika |
| Zdroj: | Sensors (Basel, Switzerland) Sensors, vol. 21, no. 14, 4809, 2021. Sensors, Vol 21, Iss 4809, p 4809 (2021) Sensors Volume 21 Issue 14 |
| ISSN: | 1424-8220 |
| Popis: | Autonomous mobile robots (AMRs) are increasingly used in modern intralogistics systems as complexity and performance requirements become more stringent. One way to increase performance is to improve the operation and cooperation of multiple robots in their shared environment. The paper addresses these problems with a method for off-line route planning and on-line route execution. In the proposed approach, pre-computation of routes for frequent pick-up and drop-off locations limits the movements of AMRs to avoid conflict situations between them. The paper proposes a reinforcement learning approach where an agent builds the routes on a given layout while being rewarded according to different criteria based on the desired characteristics of the system. The results show that the proposed approach performs better in terms of throughput and reliability than the commonly used shortest-path-based approach for a large number of AMRs operating in the system. The use of the proposed approach is recommended when the need for high throughput requires the operation of a relatively large number of AMRs in relation to the size of the space in which the robots operate. |
| Databáze: | OpenAIRE |
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