Localization Based on Natural Features Detector for Steep Slope Vineyards

Abstract

Placing ground robots to work in steep slope vineyards is a complex challenge. The Global Positioning System (GPS) signal is not always available and accurate. A reliable localization approach to detect natural features for this environment is required. This paper presents an improved version of a visual detector for Vineyards Trunks and Masts (ViTruDe) and, a robot able to cope pruning actions in steep slope vineyards (AgRob V16). In addition, it presents an augmented data-set for other localization and mapping algorithm benchmarks. ViTruDe accuracy is higher than 95% under our experiments. Under a simulated runtime test, the accuracy lies between 27% - 96% depending on ViTrude parametrization. This approach can feed a localization system to solve a GPS signal absence. The ViTruDe detector also considers economic constraints and allows to develop cost-effective robots. The augmented training and datasets are publicly available for future research work.

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