Dynamic path planning of mobile robots with improved genetic algorithm

By Adem Tuncer, Mehmet Yildirim. Computers & electrical engineering, 2012

322 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computer Vision and Pattern Recognition, Control and Systems Engineering

View Paper: https://www.semanticscholar.org/paper/b52f6db5e63c4fde291ddb8be16c2ceef7f22a33

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Alfonso J. García-Cerezo
2. Carlos Jesús Pérez-del-Pulgar
3. J. Sánchez-Ibáñez
4. George K. Karagiannidis
5. Mohsen Guizani

In Computer Vision and Pattern Recognition

1. Alfonso J. García-Cerezo
2. Carlos Jesús Pérez-del-Pulgar
3. J. Sánchez-Ibáñez
4. Guangjie Han
5. George K. Karagiannidis
6. Mohsen Guizani

In Control and Systems Engineering

1. Alfonso J. García-Cerezo
2. Carlos Jesús Pérez-del-Pulgar
3. J. Sánchez-Ibáñez
4. George K. Karagiannidis
5. Mohsen Guizani

Citations in the corpus

• Path Planning for Autonomous Mobile Robots: A Review (2021, background): “Tuncer and Yildirim [109] presented a modification to the Mutation process.”
• Path Planning for the Mobile Robot: A Review (2018, background): “The algorithm has slow convergence speed, long execution time, and the performance relies on the initial value.”
• A Survey on Mobile Anchor Node Assisted Localization in Wireless Sensor Networks (2016, background): “Recently, researchers’ interest on autonomous vehicles has increased with the development of electronic techniques [75].”