| dc.description.abstract | This research is motivated by the declining number of agricultural workers, particularly
during harvest seasons, as well as the high workload faced by farmers due to the
continued use of manual methods in the transportation of harvested crops. To address
this issue, a series of steps were conducted, including literature review, system design,
hardware and software implementation, and system testing. This study aims to develop
a prototype of a harvest-transporting robot for a simulated avocado plantation path
using an automatic navigation system based on a line follower and Dijkstra's algorithm.
The developed robot utilizes an ESP32 as the main microcontroller, equipped with a
line sensor for navigation, a load cell for detecting the weight of the load, an HX711
module, DC motors, and an LCD to display real-time information. The testing results
show that the robot was able to follow the designated path effectively, with the line
follower sensor achieving an 86.67% success rate across 15 trials at three destination
points. The load cell sensor recorded an average error of only 0.8% across five tests,
indicating high accuracy in weight measurement. In transportation trials on three
different routes, the system achieved an average time efficiency of 93.36% compared
to the fastest time on each route. Furthermore, the comparison between manual
algorithm calculations and program results showed consistency, indicating that the
implementation of Dijkstra's algorithm worked as designed. This development is
expected to support the broader adoption of automation technologies in Indonesia's
agricultural sector. | en_US |
