Autonomous Robot Visual-Only Guidance in Agriculture Using Vanishing Point Estimation

• Type: Article in International Conference Proceedings Book
• Date: 2021

Authors

Sarmento, J (Author) Other; Aguiar, AS (Author) Other; Filipe Neves Santos (Author) FEUP; Armando Jorge Sousa (Author) FEUP

Conference proceedings International

Title: PROGRESS IN ARTIFICIAL INTELLIGENCE (EPIA 2021)

Pages: 3-15

20th EPIA Conference on Artificial Intelligence (EPIA)

ELECTR NETWORK, SEP 07-09, 2021

Indexing

ISI Web of Knowledge - 3 Citations

Scopus - 5 Citations

Other information

Authenticus ID: P-00V-DRQ

DOI: 10.1007/978-3-030-86230-5_1

Abstract (EN): Autonomous navigation in agriculture is very challenging as it usually takes place outdoors where there is rough terrain, uncontrolled natural lighting, constantly changing organic scenarios and sometimes the absence of a Global Navigation Satellite System (GNSS). In this work, a single camera and a Google coral dev Board Edge Tensor Processing Unit (TPU) setup is proposed to navigate among a woody crop, more specifically a vineyard. The guidance is provided by estimating the vanishing point and observing its position with respect to the central frame, and correcting the steering angle accordingly. The vanishing point is estimated by object detection using Deep Learning (DL) based Neural Networks (NN) to obtain the position of the trunks in the image. The NN's were trained using Transfer Learning (TL), which requires a smaller dataset than conventional training methods. For this purpose, a dataset with 4221 images was created considering image collection, annotation and augmentation procedures. Results show that our framework can detect the vanishing point with an average of the absolute error of 0.52. and can be considered for autonomous steering.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 13