JACIII Vol.23 No.2 pp. 282-286
doi: 10.20965/jaciii.2019.p0282

Short Paper:

Robot Navigation Algorithm Based on Sensor Technology and Iterative Maximum a Posteriori Estimation

Na Zheng, Yanli Du, and Qinghua Bai

College of Electrical and Information Engineering, Beihua University
No.1 Xinshan Street, Longtan District, Jilin City, Jilin 132021, China

Corresponding author

June 11, 2018
July 31, 2018
March 20, 2019
Sensor technology, iterative maximum a posteriori estimation, robot navigation, received signal strength, Kalman filter

The hybrid sensor network is mainly composed of static and dynamic sensor nodes. The dynamic node is the mobile robot with wireless sensor module installed. This paper proposes a robot navigation algorithm based on sensor technology and iterative maximum a posteriori estimation. It uses Kalman filter and least-squares fitting to improve RSSI measurement accuracy and the mobile robot only needs to use the received signal strength (RSSI) and odometer information to realize autonomous navigation in the sensing area. Moreover, static nodes are randomly deployed in the sensing area without a priori location information. Therefore, this algorithm has the advantages of low cost and ease of deployment. Both simulation and outdoor field experiments show the performance and effectiveness of the algorithm.

Steps vary with the initial distance

Steps vary with the initial distance

Cite this article as:
N. Zheng, Y. Du, and Q. Bai, “Robot Navigation Algorithm Based on Sensor Technology and Iterative Maximum a Posteriori Estimation,” J. Adv. Comput. Intell. Intell. Inform., Vol.23 No.2, pp. 282-286, 2019.
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Last updated on Apr. 22, 2024