Edge AI-Based Tree Trunk Detection for Forestry Monitoring Robotics

Santos, Filipe; Filipe, Vítor; Sousa, Armando; Oliveira, P. B. de Moura

doi:10.3390/robotics11060136

Cited by 12 publications

(7 citation statements)

References 56 publications

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“…In recent years, deep learning algorithms have undergone great performance improvements, making considerable progress in applications that include tree trunk detection (da Silva et al, 2022;Wells and Chung, 2023), tree crown detection (Roslan et al, 2020), tree separation/classification (Roslan et al, 2020;Liu et al, 2021), and tree health detection (Yarak et al, 2021;Nguyen et al, 2021). Deep learning is enabling the deployment of computer vision systems on forest machines to achieve real-time complex forestry operations.…”

Section: Literature Review About Computer Vision In Forestrymentioning

confidence: 99%

Exploring the Feasibility of Autonomous Forestry Operations: Results from the First Experimental Unmanned Machine

Hera,

Trejo,

Lindroos

et al. 2023

Preprint

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This article presents a study on the world’s first unmanned machine designed for autonomous forestry operations. In response to the challenges associated with traditional forestry operations, we developed a platform equipped with essential hardware components necessary for performing autonomous forwarding tasks. Through the use of computer vision, autonomous navigation, and manipulator control algorithms, the machine is able to pick up logs from the ground and manoeuvre through a range of forest terrains without the need for human intervention. Our initial results demonstrate the potential for safe and efficient autonomous extraction of logs in the cut-to-length harvesting process. We achieved a high level of accuracy in our computer vision system, and our autonomous navigation system proved to be highly efficient. This research represents a significant milestone in the field of autonomous outdoor robotics, with far-reaching implications for the future of forestry operations. By reducing the need for human labour, autonomous machines have the potential to increase productivity and reduce labour costs, while also minimizing the environmental impact of timber harvesting. The success of our study highlights the potential for further development and optimization of autonomous machines in the forestry industry.

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Section: Literature Review About Computer Vision In Forestrymentioning

confidence: 99%

Exploring the Feasibility of Autonomous Forestry Operations: Results from the First Experimental Unmanned Machine

Hera,

Trejo,

Lindroos

et al. 2023

Preprint

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“…In terms of precision farming in horticulture, a trend is also the use of robotics for tree management including precise monitoring of trunks. For instance, a recent study applied deep learning algorithms to aid a robotic platform equipped with a multisensory device to map and monitor trunks in forest and ornamental settings ( da Silva et al., 2022 ). Robotics can be expected to impact precision horticulture beyond automated fruit collection approaches towards holistic trunk management platforms also in olive cultivation.…”

Section: Precision Arboriculture Using Innovative Application and For...mentioning

confidence: 99%

Innovations towards sustainable olive crop management: a new dawn by precision agriculture including endo-therapy

Grandi,

Oehl,

Lombardi

et al. 2023

Front. Plant Sci.

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Olive trees (Olea europaea L.) are deeply interwoven with the past, present and future of Mediterranean civilizations, both as essential economical as well as cultural valuables. Olive horticulture constitutes one of the primary agroecosystems in the Mediterranean regions of today. Being inhabitant of ecological niches, Olea europaea is prone to a peculiar vulnerability towards climatic and socioeconomical transformations that are briskly reshaping regional and global agroecosystems. Because of climatic changes and the biosafety risks of global agricultural trades, olive plants are highly susceptible to newly emerging diseases and pests, and the traditional olive horticultural crop protection practices are under scrutiny towards reducing their ecological impact. Hence there is an eminent demand for a more nature-positive olive tree crop management. Recent innovations in precision agriculture are raising the prospect for innovative crop protection methods that may provide olive farmers the required agility to respond to present and future agricultural challenges. For instance, endo-therapy, which is the systemic delivery of active ingredients via trunk injection, is a technology that holds promise of a true step-change in sustainable olive crop management. Endo-therapy allows reaching vascular diseases inaccessible to foliar treatments and delivers active ingredients in a precise manner with no risks of off-target drifts. Similarly, progresses in biological precision delivery using controlled release of active ingredients based on innovative formulation technologies are showing an exciting potential for more targeted and sustainable crop protection solutions. This review summarizes the latest innovations on both physical and biological precision deliveries in the realm of olive arboriculture in the Mediterranean regions and gives an outlook how these technologies may help orchestrating innovative olive culture practices soon.

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“…This generally involves locating and classifying objects by assigning labels to pixels based on shared characteristics. In the artifi-cial perception of agricultural and forestry robotics, simple and efficient object detection and classification methods have often been used to perform parsing, including deep learning algorithms using bounding box partitioning; for recent examples, see [138][139][140]. These have the significant advantage of being suited for real-time implementations (Section 4.5 will discuss these issues in more depth).…”

Section: Image Segmentation: Object Detection and Semantic Segmentationmentioning

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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Edge AI-Based Tree Trunk Detection for Forestry Monitoring Robotics

Cited by 12 publications

References 56 publications

Exploring the Feasibility of Autonomous Forestry Operations: Results from the First Experimental Unmanned Machine

Exploring the Feasibility of Autonomous Forestry Operations: Results from the First Experimental Unmanned Machine

Innovations towards sustainable olive crop management: a new dawn by precision agriculture including endo-therapy

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

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