Obstacle Detection for Agricultural Robot Based on Vector Field Histogram

Authors

  • Bijay Rai, Dr. Amrendra Mahtsa, Dr. Asim Datta

DOI:

https://doi.org/10.17762/msea.v71i4.623

Abstract

The deployment of autonomous robots has increased in the agricultural industry to replace human labour and increase production yields. A self-sufficient robot is designed to perform certain tasks in various places of the working field area; hence, a cost-effective and efficient navigation system for differential wheeled mobile robots is of the utmost necessity. In this research, an autonomous navigation system for a mobile agricultural robot is suggested utilizing the pure pursuit algorithm (PPA) and vector field histogram (VFH). The PPA algorithm steers autonomously toward waypoints, while the VFH algorithm helps the car avoid obstacles. The VFH method uses 2-dimensional light detection and ranging (LiDAR) sensors for monitoring. PPA specifies a minimum amount of waypoints for map setup simplicity. Using the variable settings of the PPA algorithm, a variety of indicators, including as the distance travelled by the robot, the number of iterations necessary to complete the journey, etc., are examined. The examination of the results indicates that agricultural mobile robots can travel at speeds upto 2.5 km/hr while avoiding obstacles.

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Published

2022-08-29

How to Cite

Bijay Rai, Dr. Amrendra Mahtsa, Dr. Asim Datta. (2022). Obstacle Detection for Agricultural Robot Based on Vector Field Histogram. Mathematical Statistician and Engineering Applications, 71(4), 1304–1311. https://doi.org/10.17762/msea.v71i4.623

Issue

Section

Articles