College - Author 1

College of Engineering

Department - Author 1

Electrical Engineering Department

Degree Name - Author 1

BS in Electrical Engineering

College - Author 2

College of Engineering

Department - Author 2

Electrical Engineering Department

Degree - Author 2

BS in Electrical Engineering

College - Author 3

College of Engineering

Department - Author 3

Electrical Engineering Department

Degree - Author 3

BS in Electrical Engineering

Date

6-2024

Primary Advisor

Siavash Farzan, College of Engineering, Electrical Engineering Department

Abstract/Summary

As agricultural demands rise and manual labor costs increase, there has become a dire need to automate apple harvesting. However, the precision and speed necessary for cost-efficient apple harvesting pose a significant challenge for robotic automation. To maintain cost-effective production, a harvester must be able to operate fast enough and long enough to compete with human labor. It must also be able to navigate and traverse apple orchards autonomously and pick apples without damaging the fruit or tree. This project presents an apple harvesting robot that uses a Mask R-CNN vision system with an RGB-D camera to detect the location of apples in a small-scale environment. These coordinates are then published to a ROS network from which a mobile robot with an LDS-02 laser scanner navigates through the environment and localizes itself through a combination of SLAM and AMCL algorithms. It then uses a four degree of freedom articulated arm and a custom soft gripping end effector to pluck the apple for the tree. This entire process is fully autonomous and is able to run for approximately 95 minutes before requiring a new battery. The camera used for vision is mounted in a stationary location outside of the environment. This project serves as an integration and application of several burgeoning fields of research in robotics including dead-reckoning mobile robotics, sensor fusion, soft-gripping actuators, control of articulated arms, and neural network vision processing. In sum, the robot is an effective demonstration of the application of robotics within the complex space of apple harvesting tasks.

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