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Hansson, L. J., Sten, G., Rossander, M., Lideskog, H., Manner, J., van Westendorp, R., . . . Karlberg, M. (2024). Autoplant—Autonomous Site Preparation and Tree Planting for a Sustainable Bioeconomy. Forests, 15(2), Article ID 263.
Open this publication in new window or tab >>Autoplant—Autonomous Site Preparation and Tree Planting for a Sustainable Bioeconomy
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2024 (English)In: Forests, ISSN 1999-4907, E-ISSN 1999-4907, Vol. 15, no 2, article id 263Article in journal (Refereed) Published
Abstract [en]

Sustainable forestry requires efficient regeneration methods to ensure that new forests are established quickly. In Sweden, 99% of the planting is manual, but finding labor for this arduous work is difficult. An autonomous scarifying and planting machine with high precision, low environmental impact, and a good work environment would meet the needs of the forest industry. For two years, a collaborative group of researchers, manufacturers, and users (forest companies) has worked together on developing and testing a new concept for autonomous forest regeneration (Autoplant). The concept comprises several subsystems, i.e., regeneration and route planning, autonomous driving (path planning), new technology for forest regeneration with minimal environmental impact, automatic plant management, crane motion planning, detection of planting spots, and follow-up. The subsystems were tested separately and integrated together during a field test at a clearcut. The concept shows great potential, especially from an environmental perspective, with significantly reduced soil disturbances, from approximately 50% (the area proportion of the area disturbed by disc trenching) to less than 3%. The Autoplant project highlights the challenges and opportunities related to future development, e.g., the relation between machine cost and operating speed, sensor robustness in response to vibrations and weather, and precision in detecting the size and type of obstacles during autonomous driving and planting.

Place, publisher, year, edition, pages
MDPI, 2024
Keywords
automation, silviculture, planting, mechanical site preparation, route planning, obstacle detection, system analysis, motion planning
National Category
Forest Science
Research subject
Machine Design
Identifiers
urn:nbn:se:ltu:diva-104035 (URN)10.3390/f15020263 (DOI)
Funder
Vinnova, 2020-04202
Note

Validerad;2024;Nivå 2;2024-01-31 (joosat);

Funder: “Autonomous forest regeneration for a sustainable bioeconomy (AutoPlant)”;

Part of Special Issue: FORMEC/FEC 2023—Improving Access to Sustainable Forest Materials in a Resource-Constrained World

Full text: CC BY License

Available from: 2024-01-31 Created: 2024-01-31 Last updated: 2024-01-31Bibliographically approved
La Hera, P., Mendoza-Trejo, O., Lindroos, O., Lideskog, H., Lindbäck, T., Latif, S., . . . Karlberg, M. (2024). Exploring the feasibility of autonomous forestry operations: Results from the first experimental unmanned machine. Journal of Field Robotics
Open this publication in new window or tab >>Exploring the feasibility of autonomous forestry operations: Results from the first experimental unmanned machine
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2024 (English)In: Journal of Field Robotics, ISSN 1556-4959, E-ISSN 1556-4967Article in journal (Refereed) Epub ahead of print
Abstract [en]

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 labor, autonomous machines have the potential to increase productivity and reduce labor 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.

Place, publisher, year, edition, pages
John Wiley & Sons, 2024
National Category
Forest Science
Research subject
Machine Design
Identifiers
urn:nbn:se:ltu:diva-104220 (URN)10.1002/rob.22300 (DOI)
Funder
Swedish Energy Agency, HAFSBIT no. 48003-1The Kempe Foundations, JCK-1713
Note

License full text: CC BY-NC-ND

Funder: Mistra Digital Forest

Available from: 2024-02-08 Created: 2024-02-08 Last updated: 2024-02-08
Latif, S., Lindbäck, T., Lideskog, H. & Karlberg, M. (2024). Outdoor tests of autonomous navigation system based on two different reference points of PurePursuit algorithm for 10-ton articulated vehicle.. IEEE Access, 12, 8413-8421
Open this publication in new window or tab >>Outdoor tests of autonomous navigation system based on two different reference points of PurePursuit algorithm for 10-ton articulated vehicle.
2024 (English)In: IEEE Access, E-ISSN 2169-3536, Vol. 12, p. 8413-8421Article in journal (Refereed) Published
Abstract [en]

This work presents outdoor test results of autonomous navigation system based on two different reference points of PurePursuit algorithm for a 10-ton articulated research platform. PurePursit is commonly used simplified tracking algorithm based on geometric calculation of desired steering angle by pursuing certain number of points/distance ahead on given path from a fixed reference point of vehicle. Choice of fixed reference point effects the tracking accuracy particularly for articulated/center-steered vehicles. In this experimental work, PurePursuit algorithm with a virtual reference point(PPV) and commonly used front-axle reference point(PPF) is evaluated for heavy duty articulated vehicles in outdoor experiments. Experimental data shows that choice of reference point in PurePursuit algorithm for articulated vehicle has impact on tracking accuracy in terms of crosstrack errors and heading errors. Navigation tests were performed on a flat asphalt surface for paths of sharp complexities i-e a path with continuous curvature (circular path) and a path with sharp turns (zigzag path) with different initial conditions i-e initial position of vehicle. In general, it can be concluded that PurePursuit algorithm with front reference point (PPF) produced fewer crosstrack errors while PurePursuit algorithm with virtual midpoint reference (PPV) produced fewer heading errors.

Place, publisher, year, edition, pages
IEEE, 2024
Keywords
Autonomous navigation, articulated vehicle, outdoor experiments, PurePursuit algorithm, virtual mid reference point, front-axle mid reference point
National Category
Control Engineering
Research subject
Machine Design
Identifiers
urn:nbn:se:ltu:diva-103848 (URN)10.1109/access.2024.3353616 (DOI)
Funder
Stiftelsen Svenska Lantbrukarnes Olycksfallsförsäkringsfond (SLO-fonden)
Note

Validerad;2024;Nivå 2;2024-01-22 (signyg)

Full text license: CC BY-NC-ND

Available from: 2024-01-22 Created: 2024-01-22 Last updated: 2024-02-01Bibliographically approved
Arvidsson, E., Karlberg, M., Hjelm, K. & Lideskog, H. (2023). Digital precision planning tool for autonomous forest regeneration of mixed tree species. In: : . Paper presented at 16th European-African Regional Conference of the International Society for Terrain-Vehicle Systems(ISTVS), Lublin, Poland, October 11-13, 2023.
Open this publication in new window or tab >>Digital precision planning tool for autonomous forest regeneration of mixed tree species
2023 (English)Conference paper, Published paper (Refereed)
Research subject
Machine Design
Identifiers
urn:nbn:se:ltu:diva-103149 (URN)10.56884/SDFR7512 (DOI)
Conference
16th European-African Regional Conference of the International Society for Terrain-Vehicle Systems(ISTVS), Lublin, Poland, October 11-13, 2023
Note

ISBN for host publication: 978-1-942112-55-6

Available from: 2023-12-05 Created: 2023-12-05 Last updated: 2023-12-05Bibliographically approved
Latif, S., Lindbäck, T. & Karlberg, M. (2023). Evaluation of Autonomous Navigational Accuracy for Different Reference Points in PurePursuit Algorithm for Center-Steered Articulated Vehicles. In: Jo, J.; Helbig, M.; Stantic, B.; Choi, H-L.; Oh, H.; Hwangbo, J.; Lee, C-H. (Ed.), Robot Intelligence Technology and Applications 7: Results from the 10th International Conference on Robot Intelligence Technology and Applications. Paper presented at 10th International Conference on Robot Intelligence Technology and Applications (RiTA 2022), Gold Coast, Australia, December 7-9, 2022 (pp. 201-212). Springer Nature
Open this publication in new window or tab >>Evaluation of Autonomous Navigational Accuracy for Different Reference Points in PurePursuit Algorithm for Center-Steered Articulated Vehicles
2023 (English)In: Robot Intelligence Technology and Applications 7: Results from the 10th International Conference on Robot Intelligence Technology and Applications / [ed] Jo, J.; Helbig, M.; Stantic, B.; Choi, H-L.; Oh, H.; Hwangbo, J.; Lee, C-H., Springer Nature, 2023, p. 201-212Conference paper, Published paper (Refereed)
Abstract [en]

Accurate autonomous navigation for off-terrain utility vehicles with no human intervention is an essential requirement to achieve full automation. Within several applications, though higher autonomous navigational accuracy (almost ±2.5 cm) has been achieved in some commercially available vehicles yet requirements for human intervention is still very much required in several situations. This study investigates autonomous navigational accuracy of PurePursuit algorithm for different reference points for a non-steerable-wheels center-steered articulated vehicle. PurePursuit algorithm is preferable choice for path tracking for its simplicity and for vehicles where high speed is not a requirement. Evaluation of PurePursuit algorithm for utility vehicles of type studied in this paper is somewhat less explored area. We have compared the autonomous navigational accuracy of PurePursuit algorithm for different reference points for a set of different path complexities that also includes vehicles kinematic constraints in simulation environment. Average lateral and heading deviations were calculated for a set of different path complexities, and it was found that in general proposed reference point for PurePursuit algorithm for center-steer articulated vehicle shows better lateral and heading autonomous navigational accuracy than the traditional PurePursuit algorithm.

Place, publisher, year, edition, pages
Springer Nature, 2023
Series
Lecture Notes in Networks and Systems (LNNS), ISSN 2367-3370, E-ISSN 2367-3389 ; 642
National Category
Control Engineering Computer Sciences
Research subject
Machine Design
Identifiers
urn:nbn:se:ltu:diva-90267 (URN)10.1007/978-3-031-26889-2_18 (DOI)2-s2.0-85151057994 (Scopus ID)
Conference
10th International Conference on Robot Intelligence Technology and Applications (RiTA 2022), Gold Coast, Australia, December 7-9, 2022
Note

ISBN för värdpublikation: 978-3-031-26888-5, 978-3-031-26889-2

Available from: 2022-07-26 Created: 2022-07-26 Last updated: 2023-10-11Bibliographically approved
Rautio, P., Lideskog, H., Bergsten, U. & Karlberg, M. (2023). Lean forestry – A paradigm shift from economies of scale to precise and sustainable use of ecosystem services in forests. Forest Ecology and Management, 530, Article ID 120766.
Open this publication in new window or tab >>Lean forestry – A paradigm shift from economies of scale to precise and sustainable use of ecosystem services in forests
2023 (English)In: Forest Ecology and Management, ISSN 0378-1127, E-ISSN 1872-7042, Vol. 530, article id 120766Article in journal (Refereed) Published
Abstract [en]

Modern forestry practices are based on the idea of ‘big is beautiful’. Especially in the regeneration phase, the operations are often excessive in relation to the profit that one can expect to gain in decades to come. Excessive operations also constrain the use of ecosystem services. Lean forestry is a novel philosophy of forestry practise that aims to direct the idea of “big is beautiful” in modern silviculture more into “do cost effectively only what is needed to fulfil the goals”. To succeed Lean forestry requires exact spatial information to be able to carry out forestry measures very precisely only where they are really needed to fulfil goals. This kind of a paradigm shift requires systems with new kinds of abilities to remotely sense the surrounding environment and to make better and faster decisions based on sensed data. Automated unmanned offroad vehicle that is able to sense the environment and to make lean decisions is presented as an example of initiatives that can make forestry more cost-effective and simultaneously improve utilisation of wide range of ecosystem services in forests.

Place, publisher, year, edition, pages
Elsevier, 2023
National Category
Forest Science
Research subject
Machine Design
Identifiers
urn:nbn:se:ltu:diva-95202 (URN)10.1016/j.foreco.2022.120766 (DOI)
Projects
ArcticHubs
Funder
EU, Horizon 2020, 869580
Note

Validerad;2023;Nivå 2;2023-01-10 (hanlid)

Available from: 2023-01-10 Created: 2023-01-10 Last updated: 2023-01-10Bibliographically approved
Li, S., Lideskog, H., Karlberg, M. & van Westendorp, R. (2023). Obstacle detection vision system enabling autonomous mounding on clearcuts. In: Proceedings of the 16th European-African Regional Conference of the ISTVS: . Paper presented at 16th European-African Regional Conference of the ISTVS, Lublin, Poland, October 11-13 2023. International Society for Terrain-Vehicle Systems
Open this publication in new window or tab >>Obstacle detection vision system enabling autonomous mounding on clearcuts
2023 (English)In: Proceedings of the 16th European-African Regional Conference of the ISTVS, International Society for Terrain-Vehicle Systems , 2023Conference paper, Published paper (Refereed)
Place, publisher, year, edition, pages
International Society for Terrain-Vehicle Systems, 2023
National Category
Computer Vision and Robotics (Autonomous Systems) Other Mechanical Engineering
Research subject
Machine Design
Identifiers
urn:nbn:se:ltu:diva-101677 (URN)10.56884/VQZG2856 (DOI)
Conference
16th European-African Regional Conference of the ISTVS, Lublin, Poland, October 11-13 2023
Funder
Vinnova, 2020-04202Interreg, 20357984
Note

Funder: EU (869580)

Available from: 2023-10-16 Created: 2023-10-16 Last updated: 2023-10-27Bibliographically approved
Latif, S., Lindbäck, T., Karlberg, M. & Wallsten, J. (2022). Bale Collection Path Planning Using an Autonomous Vehicle with Neighborhood Collection Capabilities. Agriculture, 12(12), Article ID 1977.
Open this publication in new window or tab >>Bale Collection Path Planning Using an Autonomous Vehicle with Neighborhood Collection Capabilities
2022 (English)In: Agriculture, E-ISSN 2077-0472, Vol. 12, no 12, article id 1977Article in journal (Refereed) Published
Abstract [en]

This research was mainly focused on the evaluation of path planning approaches as a prerequisite for the automation of bale collection operations. A comparison between a traditional bale collection path planning approach using traditional vehicles such as tractors, and loaders with an optimized path planning approach using a new autonomous articulated concept vehicle with neighborhood reach capabilities (AVN) was carried out. Furthermore, the effects of carrying capacity on reduction in the working distance of the bale collection operation was also studied. It was concluded that the optimized path planning approach using AVN with increased carrying capacity significantly reduced the working distance for the bale collection operation and can thus improve agricultural sustainability, particularly within forage handling.

Place, publisher, year, edition, pages
MDPI, 2022
Keywords
agriculture, path planning, neighborhood collection, autonomous vehicle, genetic algorithm, global optimization, bale collection problem, forage handling
National Category
Robotics Agricultural Science
Research subject
Machine Design
Identifiers
urn:nbn:se:ltu:diva-90359 (URN)10.3390/agriculture12121977 (DOI)000900244800001 ()2-s2.0-85144717928 (Scopus ID)
Projects
Automation for Autonomous Terrain Mobility (AUTO2)
Funder
The Royal Swedish Academy of Agriculture and Forestry (KSLA)Vinnova
Note

Validerad;2022;Nivå 2;2022-12-02 (hanlid)

Available from: 2022-04-21 Created: 2022-04-21 Last updated: 2023-05-09Bibliographically approved
Latif, S., Lindbäck, T., Wallsten, J. & Karlberg, M. (2021). Challenges and Opportunities for Automation of Agricultural Vehicles in Sweden. In: Martelli M., Kovecses J., Shenvi M., Dixon J. (Ed.), Proceedings of the 20th International Conference of the International Society for Terrain-Vehicle Systems and 9th Americas Conference of the International Society for Terrain-Vehicle Systems (ISTVS 2021): . Paper presented at 20th International Conference and 9th Americas Conference of the International Society for Terrain-Vehicle Systems (ISTVS 2021), [Online], September 27-29, 2021 (pp. 313-324). International Society for Terrain-Vehicle Systems
Open this publication in new window or tab >>Challenges and Opportunities for Automation of Agricultural Vehicles in Sweden
2021 (English)In: Proceedings of the 20th International Conference of the International Society for Terrain-Vehicle Systems and 9th Americas Conference of the International Society for Terrain-Vehicle Systems (ISTVS 2021) / [ed] Martelli M., Kovecses J., Shenvi M., Dixon J., International Society for Terrain-Vehicle Systems , 2021, p. 313-324Conference paper, Published paper (Refereed)
Abstract [en]

Swedish agriculture has gone through many changes over past years in terms of production, working methods, technology and use of natural resources. To achieve its vision of 2030, Swedish agricultural is rapidly transforming into more and more digitized and automated alternatives and the objective for the research presented in this paper was to identify challenges and opportunities by using automated agricultural vehicles. Data was collected through a survey and review of scientific literature and official reports. The current use and level of automation in Swedish agriculture was studied as well as aspects of productivity, profitability, ergonomics and sustainability by use of regular agricultural vehicles and farming practices. Furthermore, key challenges and opportunities related to automation of agricultural vehicles were further identified. It was found that farmers foresee several areas where automated agricultural vehicles could add value in their production (improved productivity, work environment, environmental impact etc.). However, to utilize these values, there are several challenges identified including technology readiness levels, security, responsibility distribution etc. By overcoming these challenges, it is plausible that the sustainability of agricultural operations with vehicles involved could be significantly improved through automation.

Place, publisher, year, edition, pages
International Society for Terrain-Vehicle Systems, 2021
Keywords
Agricultural operations, Agricultural vehicles, Automated agricultural vehicles, Automation, Challenges, Ergonomics, Opportunities, Sustainability, Swedish agriculture, Work environment
National Category
Agricultural Science
Research subject
Machine Design
Identifiers
urn:nbn:se:ltu:diva-83707 (URN)2-s2.0-85124530168 (Scopus ID)
Conference
20th International Conference and 9th Americas Conference of the International Society for Terrain-Vehicle Systems (ISTVS 2021), [Online], September 27-29, 2021
Note

ISBN för värdpublikation: 978-1-7138-4105-0

Available from: 2021-04-15 Created: 2021-04-15 Last updated: 2023-01-24Bibliographically approved
Marti Bigorra, A., Isaksson, O. & Karlberg, M. (2020). Semi-autonomous methodology to validate and update customer needs database through text data analytics. International Journal of Information Management, 52, Article ID 102073.
Open this publication in new window or tab >>Semi-autonomous methodology to validate and update customer needs database through text data analytics
2020 (English)In: International Journal of Information Management, ISSN 0268-4012, E-ISSN 1873-4707, Vol. 52, article id 102073Article in journal (Refereed) Published
Abstract [en]

To develop highly competitive products, companies need to understand customer needs (CNs) by effectively gathering and analysing customer data. With the advances in Information Technology, customer data comes not only from surveys and focus groups but also from social media and networking sites. Few studies have focused on developing algorithms that are devised exclusively to help to understand customer needs from big opinion data. Topic mining, aspect-based sentiment analysis and word embedding are some of the techniques adopted to identify CNs from text data. However, most of them do not consider the possibility that part of the customer data analysed is already known by companies. With the aim to continuously enhance company understanding of CNs, this paper presents an autonomous methodology for automatically classifying a set of text data (customer sentences) as referring to known or unknown CN statements by the company. For verification purposes, an example regarding a set of customer answers from an open survey questionnaire regarding the climate system of a car is illustrated. Results indicate that the proposed methodology helps companies to validate and update the customer need database with an average of 90 % precision and 60 % recall.

Place, publisher, year, edition, pages
Elsevier, 2020
Keywords
Customer need, CN, Company knowledge, Text data
National Category
Applied Mechanics Other Mechanical Engineering
Research subject
Machine Design; Computer Aided Design
Identifiers
urn:nbn:se:ltu:diva-77834 (URN)10.1016/j.ijinfomgt.2020.102073 (DOI)000519969300025 ()2-s2.0-85079843008 (Scopus ID)
Note

Validerad;2020;Nivå 2;2020-04-20 (alebob)

Available from: 2020-02-24 Created: 2020-02-24 Last updated: 2020-04-20Bibliographically approved
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Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0002-2342-1647

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