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2023
DOI: 10.18196/jrc.v4i3.18489
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Application of Odometry and Dijkstra Algorithm as Navigation and Shortest Path Determination System of Warehouse Mobile Robot

Achmad Ubaidillah,
Hanifudin Sukri

Abstract: One of the technologies in the industrial world that utilizes robots is the delivery of goods in warehouses, especially in the goods distribution process. This is very useful, especially in terms of resource efficiency and reducing human error. The existing system in this process usually uses the line follower concept on the robot's path with a camera sensor to determine the destination location. If the line and destination are not detected by the sensor or camera, the robot's navigation system will experience… Show more

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Cited by 3 publications
(3 citation statements)
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“…In [ 122 ], a search and rescue is presented in a maze-like environment with ant and Dijkstra algorithms. The work in [ 123 ] describes the application of odometry and Dijkstra’s algorithm to warehouse mobile robot navigation and shortest path determination.…”
Section: Heuristic Approachmentioning
confidence: 99%
“…In [ 122 ], a search and rescue is presented in a maze-like environment with ant and Dijkstra algorithms. The work in [ 123 ] describes the application of odometry and Dijkstra’s algorithm to warehouse mobile robot navigation and shortest path determination.…”
Section: Heuristic Approachmentioning
confidence: 99%
“…This test ensures that the voicebased navigation feature functions effectively, accommodating various languages and facilitating user-friendly control of the wheelchair. Many researchers have done much research work related to robot navigation with different algorithms [69], [70], [71], [72]. Open the app.…”
Section: ) Bluetooth Control: Thismentioning
confidence: 99%
“…There are two path planning methods, the first is searching based method, such as algorithm A* [4] [6], algorithm D* [7] and algorithm Djiakstra [8]. The second is sampling based method, including algorithm RRT [9,10,11], algorithm RRT-Connect and similarly [12] [13], algorithm RRT* [14] [15].…”
Section: Introductionmentioning
confidence: 99%