Agricultural robots for field operations: Concepts and components

Agricultural robots for field operations. Part 2: Operations and systems

Modern agriculture is related to a revolution that occurred in a large group of technologies (e.g., informatics, sensors, navigation) within the last decades. In crop production systems, there are field operations that are quite labour-intensive either due to their complexity or because of the fact that they are connected to sensitive plants/edible product interaction, or because of the repetitiveness they require throughout a crop production cycle. These are the key factors for the development of agricultural robots. In this paper, a systematic review of the literature has been conducted on research and commercial agricultural robotics used in crop field operations. This study underlined that the most explored robotic systems were related to harvesting and weeding, while the less studied were the disease detection and seeding robots. The optimization and further development of agricultural robotics are vital, and should be evolved by producing faster processing algorithms, better communication between the robotic platforms and the implements, and advanced sensing systems.

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Agricultural Robotics for Field Operations.

Plant breeding programs and a wide range of plant science applications would greatly benefit from the development of in-field high throughput phenotyping technologies. In this study, a terrestrial LiDAR-based high throughput phenotyping system was developed. A 2D LiDAR was applied to scan plants from overhead in the field, and an RTK-GPS was used to provide spatial coordinates. Precise 3D models of scanned plants were reconstructed based on the LiDAR and RTK-GPS data. The ground plane of the 3D model was separated by RANSAC algorithm and a Euclidean clustering algorithm was applied to remove noise generated by weeds. After that, clean 3D surface models of cotton plants were obtained, from which three plot-level morphologic traits including canopy height, projected canopy area, and plant volume were derived. Canopy height ranging from 85th percentile to the maximum height were computed based on the histogram of the z coordinate for all measured points; projected canopy area was derived by projecting all points on a ground plane; and a Trapezoidal rule based algorithm was proposed to estimate plant volume. Results of validation experiments showed good agreement between LiDAR measurements and manual measurements for maximum canopy height, projected canopy area, and plant volume, with R2-values of 0.97, 0.97, and 0.98, respectively. The developed system was used to scan the whole field repeatedly over the period from 43 to 109 days after planting. Growth trends and growth rate curves for all three derived morphologic traits were established over the monitoring period for each cultivar. Overall, four different cultivars showed similar growth trends and growth rate patterns. Each cultivar continued to grow until ~88 days after planting, and from then on varied little. However, the actual values were cultivar specific. Correlation analysis between morphologic traits and final yield was conducted over the monitoring period. When considering each cultivar individually, the three traits showed the best correlations with final yield during the period between around 67 and 109 days after planting, with maximum R2-values of up to 0.84, 0.88, and 0.85, respectively. The developed system demonstrated relatively high throughput data collection and analysis.

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In-field High Throughput Phenotyping and Cotton Plant Growth Analysis Using LiDAR.

Far from being exclusively related to economic considerations, the advantages of Industry 4.0 applications also include environmental and social concerns. An increasing amount of scientific publications relate the implementation of the fourth industrial revolution paradigm to sustainability. Several studies reported opportunities of Industry 4.0 implementation particularly to the environmental dimension of sustainability, e.g., through improved logistics streams and lowered waste from production. The present research aims at providing evidence on whether manufacturing companies consider Industry 4.0 implementation as an advantage contributing to environmental and social sustainability in terms of lower environmental impact of production, as well as higher physical relief for workers and flexibility of work organisation. The results were an attempt to study such relations with company sizes, industry sectors, turnover and self-assessed levels of digitalization varying. The sample encompasses 65 companies located in the Marche region (Italy). The results show that overall the perception of economic opportunities prevail, while the association of a beneficial impact of Industry 4.0 on environmental sustainability is rather low across companies, regardless of their size, turnover and digital level. As for the statistically significant variables, the results suggest a strong association of the size and the digital level to specific Industry 4.0 related advantages, referring to the social and economic dimension of sustainability, respectively.

https://www.mdpi.com/2071-1050/12/9/3647/pdf

The Advantages of Industry 4.0 Applications for Sustainability: Results from a Sample of Manufacturing Companies

https://www.mdpi.com/2218-6581/6/4/39/pdf

A Review on Energy-Saving Optimization Methods for Robotic and Automatic Systems

Evaluation of a LiDAR-based 3D-stereoscopic vision system for crop-monitoring applications

Planetary gearboxes are extensively used in mechatronic applications due to their compactness and high reduction ratios. The complex kinematic of such systems and the requirement of low-vibration-gears suggest studying these gearboxes with appropriate dynamic models. To this purpose, a planar lumped parameter model with 18 degrees of freedom was implemented. Model parameters such as the stiffness of the bearings and the gear meshes were calculated using dedicated FEM simulations. Two different gearbox configurations were simulated and experimentally tested. The compared results showed a good agreement. The main goal of the research was to assess the validity of such methodology for the prediction of the system eigenfrequencies. Additionally, from a kinematic analysis of the gearbox it was possible to individuate the self-excitation frequencies. The overlapping of these self-excited frequencies with the eigenfrequencies of the system was individuated as the major cause of the gearbox noise.

A mixed FEM and lumped-parameter dynamic model for evaluating the modal properties of planetary gearboxes

/pdf/byelab-an-agricultural-mobile-robot-prototype-for-proximal-4wsg35jhgq.pdf

ByeLab: An Agricultural Mobile Robot Prototype for Proximal Sensing and Precision Farming

In this paper a novel approach for sustainable 3D printing with a Linear Delta Robot equipped with elastic elements is presented and experimentally validated. Energy saving is achieved thanks to the introduction and optimization of linear springs that are mounted on the robot with different configurations: in parallel to the prismatic joints, or directly connecting the end-effector to the fixed frame. The elastic elements allow for a conversion between potential and kinetic energy during a cyclic motion, as for instance the printing of a material layer in additive manufacturing, resulting in actuators energy saving. To reduce the energy consumption, the spring parameters are optimized for the different scenarios by considering the kinematic, dynamic and electro-mechanical models of the parallel robot performing a 3D printing trajectory. The proposed approach is experimentally validated, showing an energy reduction up to almost 50% with respect to the nominal case without springs. The method is general and can be applied for energy efficiency and sustainability in several fields of robotics and computer-integrated manufacturing.

Giovanni Carabin

Papers

A Review on Energy-Saving Optimization Methods for Robotic and Automatic Systems

Evaluation of a LiDAR-based 3D-stereoscopic vision system for crop-monitoring applications

A mixed FEM and lumped-parameter dynamic model for evaluating the modal properties of planetary gearboxes

ByeLab: An Agricultural Mobile Robot Prototype for Proximal Sensing and Precision Farming

An energy-efficient approach for 3D printing with a Linear Delta Robot equipped with optimal springs