Recent Trends in Mobile Robotics for 3D Mapping in Agriculture

Fasiolo, Diego Tiozzo; Scalera, Lorenzo; Maset, Eleonora; Gasparetto, Alessandro

doi:10.1007/978-3-031-04870-8_50

Cited by 4 publications

(2 citation statements)

References 31 publications

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“…We can observe that a substantial amount of work is devoted to applications in agricultural robots, and not forestry per se. Indeed, agricultural robots have received significant attention from the research community; see, for example, [104][105][106]. However, the fundamental research on locomotion, perception, and decision-making should still be largely applicable, as both applications share many of the same challenges: irregular terrains, perception issues introduced by natural conditions, etc.…”

Section: Research and Development Throughout The Rest Of The Worldmentioning

confidence: 99%

Sensing and Artificial Perception for Robots in Precision Forestry: A Survey

Ferreira,

Portugal,

Andrada

et al. 2023

Robotics

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Artificial perception for robots operating in outdoor natural environments, including forest scenarios, has been the object of a substantial amount of research for decades. Regardless, this has proven to be one of the most difficult research areas in robotics and has yet to be robustly solved. This happens namely due to difficulties in dealing with environmental conditions (trees and relief, weather conditions, dust, smoke, etc.), the visual homogeneity of natural landscapes as opposed to the diversity of natural obstacles to be avoided, and the effect of vibrations or external forces such as wind, among other technical challenges. Consequently, we propose a new survey, describing the current state of the art in artificial perception and sensing for robots in precision forestry. Our goal is to provide a detailed literature review of the past few decades of active research in this field. With this review, we attempted to provide valuable insights into the current scientific outlook and identify necessary advancements in the area. We have found that the introduction of robotics in precision forestry imposes very significant scientific and technological problems in artificial sensing and perception, making this a particularly challenging field with an impact on economics, society, technology, and standards. Based on this analysis, we put forward a roadmap to address the outstanding challenges in its respective scientific and technological landscape, namely the lack of training data for perception models, open software frameworks, robust solutions for multi-robot teams, end-user involvement, use case scenarios, computational resource planning, management solutions to satisfy real-time operation constraints, and systematic field testing. We argue that following this roadmap will allow for robotics in precision forestry to fulfil its considerable potential.

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Section: Research and Development Throughout The Rest Of The Worldmentioning

confidence: 99%

Sensing and Artificial Perception for Robots in Precision Forestry: A Survey

Ferreira,

Portugal,

Andrada

et al. 2023

Robotics

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“…In addition to backpack, trolley, and handheld MMSs, which still require a surveyor to operate, sensorized robotic platforms leveraging on SLAM algorithms will become widespread in the near future, opening up the possibility for automated mapping (Maset et al, 2022a). Mobile robots equipped with laser scanners, RGB cameras and multispectral sensors are increasingly used in the field of precision agriculture (Tiozzo Fasiolo et al, 2022b), but the employment of autonomous systems is also spreading for the digitization of buildings, as reviewed in (Adán et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

Feasibility and Accuracy of as-Built Modelling From Slam-Based Point Clouds: Preliminary Results

Matellon,

Maset,

Visintini

et al. 2023

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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Abstract. Nowadays, portable Mobile Mapping Systems (MMSs) and robotic mapping platforms leveraging on Simultaneous Localization and Mapping (SLAM) methods are gaining increasing attention for architectural and construction surveying, representing an efficient solution for geometric data acquisition for scan-to-BIM purposes. However, the applicability of standard modelling workflows and the accuracy of Building Information Models (BIM) that can be obtained from SLAM-based point clouds is still an open question. In this paper, we propose a preliminary evaluation on the feasibility of extracting as-built BIM from (i) a point cloud acquired with a commercial portable MMS, and (ii) a point cloud obtained through an open-source SLAM algorithm, surveying the environment with an autonomous mobile robotic platform. In both cases, the main structural elements of the test site are accurately generated, thus showing promising results. On the other hand, the experiment highlights also the need for SLAM systems capable of providing less noisy point clouds, in order to capture and model architectural details.

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