  There is a dramatic shortage of skilled labor for modern vineyards. The Vinum
project is developing a mobile robotic solution to autonomously navigate
through vineyards for winter grapevine pruning. This necessitates an autonomous
navigation stack for the robot pruning a vineyard. The Vinum project is using
the quadruped robot HyQReal. This paper introduces an architecture for a
quadruped robot to autonomously move through a vineyard by identifying and
approaching grapevines for pruning. The higher level control is a state machine
switching between searching for destination positions, autonomously navigating
towards those locations, and stopping for the robot to complete a task. The
destination points are determined by identifying grapevine trunks using
instance segmentation from a Mask Region-Based Convolutional Neural Network
(Mask-RCNN). These detections are sent through a filter to avoid redundancy and
remove noisy detections. The combination of these features is the basis for the
proposed architecture.
