Abstract

Abstract
The Phenobot platform is comprised by an autonomous robot, instrumentation, artificial intelligence, and digital twin diagnosis at the molecular level, marking the transition from pure data-driven to knowledge-driven agriculture 4.0, towards a physiology-based approach to precision viticulture. Such is achieved by measuring the plant metabolome 'in vivo' and 'in situ', using spectroscopy and artificial intelligence for quantifying metabolites, e.g.: i. grapes: chlorophylls a and b, pheophytins a and b, anthocyanins, carotenoids, malic and tartaric acids, glucose and fructose; ii. foliage: chlorophylls a and b, pheophytins a and b, anthocyanins, carotenoids, nitrogen, phosphorous, potassium, sugars, and leaf water potential; and iii. soil nutrients (NPK). The geo-referenced metabolic information of each plant (organs and tissues) is the basis of multi-scaled analysis: i. geo-referenced metabolic maps of vineyards at the macroscopic field level, and ii. genome-scale 'in-silico' digital twin model for inferential physiology (phenotype state) and omics diagnosis at the molecular and cellular levels (transcription, enzyme efficiency, and metabolic fluxes). Genome-scale 'in-silico' Vitis vinifera numerical network relationships and fluxes comprise the scientific knowledge about the plant's physiological response to external stimuli, being the comparable mechanisms between laboratory and field experimentation - providing a causal and interpretable relationship to a complex system subjected to external spurious interactions (e.g., soil, climate, and ecosystem) scrambling pure data-driven approaches. This new approach identifies the molecular and cellular targets for managing plant physiology under different stress conditions, enabling new sustainable agricultural practices and bridging agriculture with plant biotechnology, towards faster innovations (e.g. biostimulants, anti-microbial compounds/mechanisms, nutrition, and water management). Phenobot is a project under the Portuguese emblematic initiative in Agriculture 4.0, part of the Recovery and Resilience Plan (Ref. PRR: 190 Ref. 09/C05-i03/2021 - PRR-C05-i03-I-000134). © The Authors, published by EDP Sciences. This is an open access article distributed under the terms of the Creative Commons Attribution License 4.0 (https://creativecommons.org/licenses/by/4.0/).

Abstract

Abstract

Abstract

Abstract
Quadruped robots have gained significant attention in the robotics world due to their capability to traverse unstructured terrains, making them advantageous in search and rescue and surveillance operations. However, their utility is substantially restricted in situations where object manipulation is necessary. A potential solution is to integrate a robotic arm, although this can be challenging since the arm's addition may unbalance the whole system, affecting the quadruped locomotion. To address this issue, the robotic arm must be adapted to the quadruped robot, which is not viable with commercially available products. This paper details the design and development of a robotic arm that has been specifically built to integrate with a quadruped robot to use in a variety of agricultural and industrial applications. The design of the arm, including its physical model and kinematic configuration, is presented. To assess the effectiveness of the prototype, a simulation was conducted with a motion-planning algorithm based on the arm's inverse kinematics. The simulation results confirm the system's stability and the functionality of the robotic arm's movement.