Since their introduction in the 1950s, industrial Automated Guided Vehicles (AGV) have gone from automatic machinery limited by hardware to complex robots limited by software, called Autonomous Mobile Robots. Small and medium businesses need to be able to utilize cutting-edge technology. Therefore, this research focuses on deploying mapless AMRs on cheap open source AMRs in dynamic industrial environments. The study implements Dijkstra’s and A-STAR algorithms on a simulated Turtlebot3 model deployed in a Gazebo rendering of an industrial warehouse with moving objects added. The Turtlebot3 model traverses the environment where time and distance results are observed. The results shown in the research indicate that Dijkstra’s algorithm is barely affected by the change of the initial map state, while the A-STAR algorithm performed worse on average. Future work should focus on minimizing the sensors needed and continue testing with more algorithms, but early tests show promising results.
Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:his-22710 |
Date | January 2023 |
Creators | Aspholm, Linus, Rolén, Michael |
Publisher | Högskolan i Skövde, Institutionen för informationsteknologi |
Source Sets | DiVA Archive at Upsalla University |
Language | English |
Detected Language | English |
Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
Format | application/pdf |
Rights | info:eu-repo/semantics/openAccess |
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