TY - GEN
T1 - An autonomous navigation system for an unmanned surface vehicle for plastic waste collection
AU - Figueroa, Piero
AU - Marsano, Luis
AU - Vinces, Leonardo
AU - Vargas, Dante
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - This article proposes the design of an autonomous navigation system intended for Unmanned Surface Vehicles (USVs) in the form of catamarans with differential propulsion, whose primary function is the collection of plastic waste in aquatic environments such as seas and lakes. The fundamental goal of this system is to optimize the operational capabilities of the USVs by increasing their navigational autonomy, consequently reducing the costs associated with their operation and production. In this context, the vehicle has been mathematically modeled, and a navigation system composed of four essential components has been established. The first component involves heading control, which utilizes GPS and IMU to estimate the orientation of the USV. The second component is the obstacle avoidance system, which employs a lidar sensor. The third component is a collection system that relies on a computer vision model with convolutional neural networks to detect different types of plastics and manage the collection process. Finally, an architecture has been designed to facilitate the interconnection of all the aforementioned control systems.
AB - This article proposes the design of an autonomous navigation system intended for Unmanned Surface Vehicles (USVs) in the form of catamarans with differential propulsion, whose primary function is the collection of plastic waste in aquatic environments such as seas and lakes. The fundamental goal of this system is to optimize the operational capabilities of the USVs by increasing their navigational autonomy, consequently reducing the costs associated with their operation and production. In this context, the vehicle has been mathematically modeled, and a navigation system composed of four essential components has been established. The first component involves heading control, which utilizes GPS and IMU to estimate the orientation of the USV. The second component is the obstacle avoidance system, which employs a lidar sensor. The third component is a collection system that relies on a computer vision model with convolutional neural networks to detect different types of plastics and manage the collection process. Finally, an architecture has been designed to facilitate the interconnection of all the aforementioned control systems.
KW - Artificial Intelligence
KW - Autonomous Robot
KW - Computer Vision
KW - Navigation System
KW - Plastic Contamination
KW - Unmanned Surface Vehicle
UR - https://www.scopus.com/pages/publications/85179893200
U2 - 10.1109/INTERCON59652.2023.10326047
DO - 10.1109/INTERCON59652.2023.10326047
M3 - Contribución a la conferencia
AN - SCOPUS:85179893200
T3 - Proceedings of the 2023 IEEE 30th International Conference on Electronics, Electrical Engineering and Computing, INTERCON 2023
BT - Proceedings of the 2023 IEEE 30th International Conference on Electronics, Electrical Engineering and Computing, INTERCON 2023
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 30th IEEE International Conference on Electronics, Electrical Engineering and Computing, INTERCON 2023
Y2 - 2 November 2023 through 4 November 2023
ER -