Methods and systems for transporting trees with an unmanned aerial vehicles
The use of UAVs to transport trees to designated ground vehicles based on parameter matching addresses inefficiencies in traditional forestry methods, improving efficiency and reducing costs in difficult terrains.
Patent Information
- Authority / Receiving Office
- WO · WO
- Patent Type
- Applications
- Current Assignee / Owner
- AIRFORESTRY AB
- Filing Date
- 2025-11-10
- Publication Date
- 2026-05-21
AI Technical Summary
Traditional tree harvesting and transportation methods are inefficient and costly, especially in difficult terrains, and there is a need for more efficient forestry operations that can selectively harvest and transport trees without disturbing the surrounding ecosystem.
A method and system utilizing remotely controlled unmanned aerial vehicles (UAVs) to transport trees to designated trucks, trailers, or self-driving pods, determining the most suitable UAV and transportation means based on tree and handling parameters, enabling efficient tree transportation and unloading.
Enables efficient forestry operations in challenging terrains by optimizing task delegation and improving tree transportation and unloading processes, enhancing operational efficiency and reducing costs.
Smart Images
Figure EP2025082482_21052026_PF_FP_ABST
Abstract
Description
W2032000211METHODS AND SYSTEMS FOR TRANSPORTING TREES WITH AN UNMANNED AERIAL VEHICLESTechnical field
[0001] The present invention relates generally to forestry operations from air, and specifically to methods and systems for transporting trees within an operating area comprising a plurality remotely and / or autonomously controlled unmanned aerial vehicles, UAVs and at least one truck and / or trailer.Background art
[0002] Traditional tree harvesting or tree falling has long been conducted by persons and equipment based on the ground. In earlier times, from the early twentieth century and going back to the early nineteenth century, little consideration was given to the state of the forest or to the eco-system within the forest. Logging was done on a massive scale to keep up with the demand caused by the industrial revolution and the subsequent expansion of human life at the time. Depending on the terrain, tree harvesting process usually begins with experienced tree fellers cutting down a stand of trees or by using heavy ground based manned harvesting machines.
[0003] Many locations are extremely difficult to reach by land, even with the use of heavy equipment such as bulldozers, and removal of trees from such locations is expensive. Sometimes it may be desirable to harvest a single tree amongst a stand of trees, so called tree thinning, without disturbing the surrounding trees.
[0004] Performing forestry operations, such as transporting trees from air via suitable means, such as via unmanned aerial vehicles, UAVs, is known. In order to facilitate more efficient a more efficient forestry operation at scale, further solutions are necessary.W2032000212Summary of invention
[0005] It is therefore an object of the present disclosure to provide a method and a system to mitigate, alleviate or eliminate one or more of the above-identified deficiencies and disadvantages.
[0006] This object is achieved by means of the subject matter of the independent claims of the present disclosure, wherein further aspects of the present disclosure are incorporated in the dependent claims.
[0007] According to a first aspect of the present disclosure it is provided a method for transporting a tree within an operating area comprising a plurality of remotely and / or autonomously controlled unmanned aerial vehicles, UAVs and at least one truck and / or trailer and / or load changer bed and / or self-driving pod, the method comprising receiving, by a base station, data indicative of at least one UAV parameter of the plurality of UAVs within an operating area, positions of the at least one truck and / or trailer and / or load changer bed and / or self-driving pod within the operating area, at least one tree handling parameter of the at least one truck and / or trailer and / or load changer bed and / or self-driving pod, at least one tree parameter of a tree, determining, by the base station, a designated UAV based on the at least one tree parameter and the at least one UAV parameter, determining, by the base station a designated truck and / or trailer and / or load changer bed and / or self-driving pod based on the at least one tree parameter, the positions of the at least one truck and / or trailer and / or load changer bed and / or self-driving pod and the at least one tree handling parameter, transporting the tree, by the designated UAV, to the designated truck and / or trailer and / or load changer bed and / or self-driving pod, unloading, by designated UAV, the tree onto the designated truck and / or trailer and / or load changer bed and / or self-driving pod.
[0008] The method enables forestry operations at scale to be efficiently conducted in areas where the terrain makes certain areas difficult to reach.
[0009] In various example embodiments the at least one UAV parameter may comprise positions of the UAVs and / or transporting capacities of the UAVs.W2032000213
[0010] The advantage of these embodiments is that a further efficient delegation of tasks within the forestry operation is achieved.
[0011] In various example embodiments the at least one tree handling parameter may comprise load capacities of the at least one truck and / or trailer and / or load changer bed and / or self-driving pod and / or tree type criteria of the at least one truck and / or trailer and / or load changer bed and / or self-driving pod.
[0012] The advantage of these embodiments is that further improvements in transporting of trees may be achieved.
[0013] In various example embodiments the at least one tree parameter may comprise at least one of: a position of the tree, a length of at least a portion of the tree, a tree species of the tree, and a weight of the tree.
[0014] The advantage of these embodiments is that further improvements in transporting of trees may be achieved.
[0015] In various example embodiments the data indicative of at least one UAV parameter of a plurality of UAVs within an operating area and / or positions of at least one truck and / or trailer and / or load changer bed and / or self-driving pod within the operating area may be time dependent.
[0016] The advantage of these embodiments is that a more accurate delegation of tasks within the forestry operation is achieved.
[0017] In various example embodiments, determining the designated UAV may further comprise matching a UAV with a tree based on that the at least one UAV parameter is compatible with the at least one tree parameter.
[0018] The advantage of these embodiments is that a more efficient delegation of tasks is achieved.
[0019] In various example embodiments, determining the designated truck and / or trailer and / or load changer bed and / or self-driving pod may further comprise matching a truck and / or trailer and / or load changer bed and / or self-driving pod withW2032000214a tree based on that the at least tree handling parameter is comparable with the at least one tree parameter.
[0020] The advantage of these embodiments is that a more efficient delegation of unloading tasks may be achieved.
[0021] In various example embodiments the at least one UAV parameter may comprise positions of the UAVs, and wherein determining the designated truck and / or trailer and / or load changer bed and / or self-driving pods may further comprise matching a UAV with a truck and / or trailer and / or load changer bed and / or self-driving pod closest to the UAV.
[0022] The advantage of these embodiments is that a more efficient delegation of transportation tasks may be achieved.
[0023] In various example embodiments the data indicative of positions of at least one truck and / or trailer and / or load changer bed and / or self-driving pod may be received via at least one of a group of: a GPS, a mesh network, dead reckoning, and pattern detection.
[0024] The advantage of these embodiments is that various data is received in a more accurate and reliable manner.
[0025] In various example embodiments the data indicative of at least one tree parameter may be provided by at least one of the UAVs comprising means for determining the at least one tree parameter.
[0026] The advantage of these embodiments is that the tree parameter can be received on the fly.
[0027] In various example embodiments the tree may be directly unloaded onto the designated truck and / or trailer and / or load changer bed and / or self-driving pod by means of the designated UAV.
[0028] The advantage of these embodiments is that an efficient unloading of the tree may be achieved.W2032000215
[0029] In various example embodiments the tree may be indirectly unloaded onto the designated truck and / or trailer and / or load changer bed and / or self-driving pod by means of the designated truck and / or trailer and / or load changer bed and / or self-driving pod.
[0030] The advantage of these embodiments is that an efficient unloading of the tree may be achieved.
[0031] In various example embodiments the method may further comprise harvesting the tree by means of the designated UAV.
[0032] The advantage of these embodiments is that efficiency of forestry operations may be further improved.
[0033] In various example embodiments, harvesting may further comprise delimbing the tree by means of the designated UAV.
[0034] The advantage of these embodiments is that the trees are easier to arrange for truck and / or trailer and / or load changer bed and / or self-driving pod transportation.
[0035] In another aspect of the present disclosure it is provided a system for transporting a tree within an operating area, the system comprising a plurality of remotely and / or autonomously controlled unmanned aerial vehicles, UAVs, wherein each UAV comprises a receiver device and means for transporting and unloading a tree to at least one truck and / or trailer and / or load changer bed and / or self-driving pod, a base station comprising transmitter / receiver device for receiving data indicative of at least one UAV parameter of a plurality of UAVs within an operating area, positions of at least one truck and / or trailer and / or load changer bed and / or self-driving pod within the operating area, at least one tree handling parameter of the at least one truck and / or trailer and / or load changer bed and / or self-driving pod, and at least one tree parameter of a tree, the base station is further configured to a determine a designated UAV based on the at least one tree parameter and the at least one UAV parameter, and to determine designated truck and / or trailer and / or load changer bed and / or self-driving pod based on the at leastW2032000216one tree parameter, the positions of the at least one truck and / or trailer and / or load changer bed and / or self-driving pod and the at least one tree handling parameter, and to transmit instructions to the designated UAV , the instructions causing the designated UAV to transport and unload the tree to the designated truck and / or trailer and / or load changed bed and / or self-driving pod.
[0036] This provides a system enabling forestry operations at scale to be efficiently conducted in areas where the terrain makes certain areas difficult to reach.
[0037] In various example embodiments, each UAV may comprise a transmitter device for transmitting data indicative of the at least one UAV parameter to the base station.
[0038] The advantage of these embodiments is that the modularity of the system may be improved.
[0039] In various example embodiments each UAV may comprise means for determining the at least one tree parameter.
[0040] The advantage of these embodiments is that tree parameter data may be received on the fly.
[0041] In various example embodiments, each truck and / or trailer may comprise a transmitter device for transmitting data indicative of a position of the truck and / or trailer and / or load changer bed and / or self-driving pod and the at least one tree handling parameter to the base station.
[0042] The advantage of these embodiments is that the modularity of the system is improved.
[0043] In various example embodiments, at least one UAV may comprise means for unloading the harvested tree onto the designated truck and / or trailer and / or load changer bed and / or self-driving pod.W2032000217
[0044] In various example embodiments, the designated truck and / or trailer may comprise means for unloading the harvested tree onto the designated truck and / or trailer and / or load changer bed and / or self-driving pod from the designated UAV.
[0045] In various example embodiments, each UAV may further comprise a remotely and / or autonomously controlled tool configured for harvesting the at least a portion of a tree.
[0046] The advantage of these embodiments is that the trees are easier to arrange for truck and / or trailer and / or load changer bed and / or self-driving pod transportation.
[0047] Further advantages with and features of the invention will be apparent from the following detailed description of preferred embodiments.Brief description of drawings
[0048] A more complete understanding of the abovementioned and other features and advantages of the present invention will be apparent from the following detailed description of preferred embodiments in conjunction with the appended drawings, wherein:Fig. 1 depicts a schematic block diagram of a method for unloading a harvested tree onto a designated truck and / or trailer and / or load changer bed and / or selfdriving pod from a remotely and / or autonomously controlled unmanned aerial vehicle, UAV according to various example embodiments of the present disclosure.Figs. 2-5 depicts a schematic illustration of an operating area in which methods according to various example embodiments of the present disclosure are performed.Fig. 6 depicts a schematic illustration of a system for unloading a harvested tree onto a designated truck and / or trailer and / or load changer bed and / or self-driving pod according to various example embodiments of the present disclosure.W2032000218Description of embodiments
[0049] The invention is not limited only to the embodiments described above and shown in the drawings, which primarily have an illustrative and exemplifying purpose. This patent application is intended to cover all adjustments and variants of the preferred embodiments described herein; thus, the present invention is defined by the wording of the appended claims and the equivalents thereof. Thus, the apparatus and system may be modified in all kinds of ways within the scope of the appended claims.
[0050] Figure 1 depicts a schematic block diagram of a method for transporting a tree 135 within an operating area 130. The tree 135 may in various example embodiments be analogous to timber, logs, scrap, and the like. However, it is appreciated that the tree 135 may be a tree that is uprooted or cut down. The tree 135 may be harvested prior to the method or as part of a step in the method as will be described herein. The method may comprise receiving S1, by a base station 120, data indicative of at least one UAV parameter of a plurality of UAVs 100a, 100b, 100c, 100d within an operating area 130, positions of at least one truck and / or trailer and / or load changer bed and / or self-driving pod 200a, 200b, 200c, 200d within the operating area 130, at least one tree handling parameter of the at least one truck and / or trailer and / or load changer bed and / or self-driving pod 200a, 200b, 200c, 200d, at least one tree parameter of a tree 135. The physical means and / or apparatuses enabling the method to be performed (e.g., UAVs, trucks and / or trailers and / or load changer beds and / or self-driving pods, base station) are depicted in further figures of the present disclosure. Further, the skilled person appreciated that the wording “data indicative of” intends to capture use of both directly data of the intended parameter and indirect data through various mathematical and / or technical means may be used to arrive at the intended parameter.
[0051] Self-driving pods may be small, autonomous vehicles designed for on-demand transport of goods on the ground. The pods may be electrically driven and / or driven by an internal combustion engine. The pods may use sensors like cameras, lidar, and sonar to navigate on the ground.W2032000219
[0052] Data indicative of at least one UAV parameter of a plurality of UAVs 100a, 100b, 100c, 100d within an operating area 130 may generally refer to the operational status of each UAV 100a, 100b, 100c, 100d. The data indicative of the at least one UAV parameter may be at least partially pre-determined. In various example embodiments the at least one UAV parameter may comprise positions of the UAVs 100a, 100b, 100c, 100d. In various example embodiments the at least one UAV parameter may comprise the transporting capacities of the UAVs 100a, 100b, 100c, 100d. E.g., due to constructional features present on each given UAV may be chosen for transporting trees of various lengths, weights or types. The UAV parameter may be data indicative of such information singly or in combination.
[0053] Data indicative of positions of at least one truck and / or trailer and / or load changer bed and / or self-driving pod 200a, 200b, 200c, 200d within an operating area 130 may in various example embodiments be received via at least one of a group of: a GPS, a mesh network, dead reckoning, and pattern detection.However, it is appreciated various other possibilities exist, e.g., via imagery taken from the air by at least one UAV, plane, helicopter, or the like. The data indicative positions of at least one truck and / or trailer and / or load changer bed and / or selfdriving pod 200a, 200b, 200c, 200d within an operating area 130 may be at least partially pre-determined. For example, each truck and / or trailer and / or load changer bed and / or self-driving pod 200a, 200b, 200c, 200d may be operative to receive trees within pre-determined loading zones, in other words designated tree receiving areas (not shown). As such, the positions of at least one truck and / or trailer and / or load changer bed and / or self-driving pod 200a, 200b, 200c, 200d may in these embodiments refer to the position of said loading zones.
[0054] In various example embodiments, the data indicative of at least one UAV parameter the of UAVs 100a, 100b, 100c, 100d within an operating area and / or positions of the at least one truck and / or trailer and / or load changer bed and / or self-driving pod 200a, 200b, 200c, 200d within the operating area 130 is time dependent. In other words, the data is dynamic data and maybe discretely (e.g. in batches at predetermined intervals or times) or continuously updated. It isW20320002110appreciated that any given parameters of the UAV 100a, 100b, 100c, 100d and / or the positions of the at least one trucks and / or trailer and / or load changer bed and / or self-driving pod 200a, 200b, 200c, 200d may change over time.
[0055] Data indicative of at least one tree handling parameter of the at least one truck and / or trailer and / or load changer bed and / or self-driving pod 200a, 200b, 200c, 200d may generally relate to which type of trees and how many trees it is possible for each truck and / or trailer and / or load changer bed and / or self-driving pod 200a, 200b, 200c, 200d to receive. The tree handling parameter may be at least partially pre-determined. In various example embodiments the at least one tree handling parameter may comprise load capacities of the at least one truck and / or trailer and / or load changer bed and / or self-driving pod 200a, 200b, 200c, 200d. In various example embodiments the at least one tree handling parameter may comprise a tree type handling criterion of the at least one truck and / or trailer and / or load changer bed and / or self-driving pod 200a, 200b, 200c, 200d.
[0056] Data indicative of at least one tree parameter of a tree 135 may for instance be a diameter of the at least a portion of a tree (top diameter, base diameter, mean diameter, median diameter), length of the at least a portion of a tree, tree species of the at least a portion of a tree and / or the weight of the at least a portion of a tree, dry content, age of tree, number of annual rings, distance between annual rings, color of annual rings, width of annual rings, amount of leaves, amount of fir needle, color, chemical composition of the tree, twig-free, deformation(s), cracks (dry cracks (partial or all trough), end crack, ring crack), rootstock, density, rot, discolored, dead tree, insect infested, microorganism infested, weather damage (storm, wind, fire, drought), machine damage (root, tree trunk), amount of fruits, seeds, berries, nuts, cones, flowers on the tree, form of root, root structure, root depth, root volume etc. The color of the tree may be an indicator of tree species. The color may be the color of the outer surface of the tree trunk or the color of a cut area. The form of the tree may be determined by a 3D camera. Form may comprise total volume of tree, leaves or fir needles, deformations, shape deviations etc. Tree parameters may also comprise material properties of the tree such as moisture content (%), tensile strength (MPa), flexuralW20320002111strength (MPa), compressive strength (MPa), shear strength (MPa), impact strength (KJ / m2), hardness (Brinell, Vickers, Rockwell), elasticity module (MPa), thermal conductivity (W / m°C), heat capacity (J / kg°C), Calorific value (MJ / kg), etc. In various example embodiments the at least one tree parameter may at least one of: a position of a tree, a length of at least a portion of a tree, a tree species of a tree, and a weight of a tree. In various example embodiments, the data indicative of at least one tree parameter may be provided by at least one of the UAVs 100a, 100b, 100c, 100d comprising means 102 to determine the at least one tree parameter. The data indicative of at least one tree parameter may be at least partially pre-determined.
[0057] It is appreciated data indicative of the at least one UAV parameter of the UAVs 100a, 100b, 100c, 10Od, the at least on tree handling parameter of the at least one truck and / or trailer and / or load changer bed and / or self-driving pod 200a, 200b, 200c, 200d, may be represented by the same data and / models as the data indicative of the at least one tree parameter of a tree 135 as described herein. For example, a UAV parameter may be data indicative of a length of a tree, the tree handling parameter may be data indicative of a length of a tree and the tree parameter may data indicative of a length of a tree as well. Similarities in these parameters may result in a simplified matching in various example embodiments of the methods described herein.
[0058] The method may further comprise determining S2, by the base station 120, a designated UAV 100e based on the at least one tree parameter and the at least one UAV parameter. In other words, the base 120 station, once data indicative of the parameters has been received may cause one of the UAVs 100a, 100b, 100c, 100d to be the designated UAV 100e for later steps in the method. The method may further comprise determining S3, by the base station 120 a designated truck and / or trailer 200e based on the at least one tree parameter, the positions of the at least one truck and / or trailer and / or load changer bed and / or self-driving pod 200a, 200b, 200c, 200d and the at least one tree handling parameter. In various example embodiments, determining S2 the designated UAV 100e may further comprise matching a UAV 100a, 100b, 100c, 100d with a treeW20320002112135 based on that the at least one UAV parameter is compatible with the at least one tree parameter of the tree 135. In various example embodiments, determining S3 the designated truck and / or trailer 200e may further comprise matching a truck and / or trailer and / or load changer bed and / or self-driving pod 200a, 200b, 200c, 200d with a tree 135 based on that the at least tree handling parameter is compatible with the at least one tree parameter. In various example embodiments, wherein the at least one UAV parameter may comprise positions of the UAVs 100a, 100b, 100c, 100d, determining S2 the designated truck and / or trailer 100e may further comprise matching a UAV 100e with a truck and / or trailer and / or load changer bed and / or self-driving pods 200e having a position closest to the designated UAV 100e.
[0059] The method may further comprise transporting S4 the tree 135, by the designated UAV 100e, to the designated truck and / or trailer 200e. It is appreciated that whilst the tree may be harvested prior to this step, it is not necessary that the harvesting is part of the method as such. In various example embodiments, however, the method may further comprise harvesting the tree by means of the designated UAV. Further, in various example embodiments, the tree 135 may be delimbed before transporting S4 the tree 135 to the designated truck and / or trailer 200e. Again, delimbing of the tree may be done prior to harvesting, during harvesting or after harvesting. Delimbing is not necessary a part of the method as such.
[0060] The method may further comprise unloading S5, by designated UAV 100e, the tree 135 onto the designated truck and / or trailer and / or load changer bed and / or self-driving pod 200e. In various example embodiments, the tree 135 may be directly unloaded onto the designated truck and / or trailer and / or load changer bed and / or self-driving pod 200e by means 105 of the designated UAV 100e. In various example embodiments the tree 135 may be indirectly unloaded onto the designated truck and / or trailer and / or load changer bed and / or self-driving pod 200e by means 205 of the designated truck and / or trailer 200e. Details of the means 105, 205 for unloading the tree 135 will be further discussed below.W20320002113
[0061] In Figures 2-5 schematic illustrations of various steps of methods described herein are depicted.
[0062] Turning to figure 2, an operating area 130 is depicted with an exemplary four UAVs 100a, 100b, 100c, 100d and four trucks or trailers or load changer beds and / or self-driving pod 200a, 200b, 200c, 200d. The term “operating area” is intended to be interpreted as a broader term than a forest. Consequently, an operating area 130 may include roads in connection and / or in vicinity to a forest wherein UAVs and at least one truck and / or trailer and / or load changer bed and / or self-driving pod may operate. Further, it is appreciated that fewer or more UAVs and / or trucks and / or trailers and / or load changer beds and / or self-driving pod may be present in the operating area 130 than the four depicted in figures 2-5. A singular truck and / or trailer and / or load changer bed and / or self-driving pod may be sufficient to achieve the methods and systems described. The number of UAVs and the comparative number of at least one truck and / or trailer and / or load changer bed and / or self-driving pod may be different or the same. In various example embodiments, it is appreciated that the features of UAVs and the at least one truck and / or trailer and / or load changer bed and / or self-driving pod may differ in regard to the at least one parameter UAV and the at least one tree handling parameter as well as various constructional features. Further examples are described below.
[0063] As an illustrative example, in various example embodiments the UAV 100a in figure 1 may be located at a position in the operating area 130. The UAV 100a may further have a transporting capacity, in other words, a loading capacity such that it can transport trees having certain weights and / or lengths and / or types of trees. The weight may be e.g., be 40-80 kg and the length may be e.g., 8-15 meters. These weights and lengths are common in so called “first thinning” operations. In another example the weight may be e.g., 75-150 kg and the length may be e.g., 15-25 meters. These weights and lengths are common in so called “second thinning” operations. In other words, the at least one parameter UAV relate to data indicative of the weight and / or length capacity of trees the given UAV can transport, and / or a position of the UAV. Combinations of UAV parameters areW20320002114possible. In accordance with the methods described herein, the at least one UAV parameter may be received by the base station 120 such that of methods described herein may be performed. Other UAV parameters are possible, e.g., if a UAV is electrically driven, the UAV parameter may comprise data indicative of a SoC, battery depletion rate, battery health or the like, and may be received by the base station 120 to perform the methods described herein. Analogously, if a UAV is driven by an internal combustion engine the UAV parameter may comprise data indicative of a fuel gauge, fuel depletion rate, or the like.
[0064] As a further example, the at least one UAV parameter of e.g., the UAV 100b may differ from the UAV 100a. As an example, the transporting capacity may be e.g., the UAV 100b may be adapted to transport trees having a weight or length e, whereas the UAV 100a may may be adapted to transport trees having different a weight and / or length, or the like. However, it is appreciated that each UAV may share at least one UAV parameters as well. For example, the UAV 100a and the UAV 100b may be adapted to transport trees having similar weights, lengths and types. However, the positions of the UAVs 100a, 100b may be different.Principally, the same applies for UAVs 100c, 100d and if further UAVs are present, for these UAVs as well.
[0065] As illustrated in figure 1 , each truck and / or trailer and / or load changer bed and / or self-driving pod 200a, 200b, 200c, 200d may comprise different positions within the operating area 130. The data indicative of such positions may be received by the base station 120 to perform the methods described herein. Further, each truck and / or trailer and / or load changer bed and / or self-driving pod 200a, 200b, 200c, 200d may be operationally suited to receiving trees based on at one tree handling parameter. For example, the truck and / or trailer and / or load changer bed and / or self-driving pod 200a may be able to transport 40-60 harvested trees.
[0066] As a further example, the at least one tree handling parameter of e.g., the truck and / or trailer and / or load changer bed and / or self-driving pod 200b may differ from the truck and / or trailer and / or load changer bed and / or self-driving podW20320002115200a. For example, the truck and / or trailer and / or load changer bed and / or selfdriving pod 200b, may be able to transport 10-30 logs of the same diameter and length as the truck and / or trailer and / or load changer bed and / or self-driving pod 200a. Further, the tree handling parameter may additionally or alternatively include the current load and storage room in each truck and / or trailer and / or load changer bed and / or self-driving pod 200a, 200b, 200c, 200d. It is appreciated the same principles apply for trucks and / or trailers and / or load changer beds and / or selfdriving pod 200c, 200d and if fewer or lesser trucks and / or trailers and / or load changer beds and / or self-driving pod are present, for these trucks and / or trailers and / or load changer beds and / or self-driving pod as well.
[0067] Turning to figure 3, an operating area 130 is depicted relating to a scenario where the UAV 100d has been determined, by the base station 120, as a designated UAV 100e according to the methods are and systems described herein. In this scenario, the UAV 100e may have been instructed to transport and unload the tree 135. Furthermore, figure 3 also depicts that the truck and / or trailer and / or load changer bed and / or self-driving pod 200d has been determined, by the base station 120 as the designated truck and / or trailer and / or load changer bed and / or self-driving pod 200e.
[0068] Turning to figure 4 an operating area 130 is depicted relating to a scenario where the designated UAV 10Oe transports a tree 135 to the designated truck and / or trailer and / or load changer bed and / or self-driving pod 200e. Turning to figure 5 an operating area 130 is depicted relating to a scenario where the designated UAV 100e unloads the tree 135 onto the designated truck and / or trailer and / or load changer bed and / or self-driving pod 200e.
[0069] Turning to figure 6, various example embodiments of an aspect of the present disclosure relating to a system 10 for transporting a tree 135 within an operating area 130 are depicted. The system 10 may comprise a plurality of remotely and / or autonomously controlled unmanned aerial vehicles, UAVs 100a, 100b, 100c, 100d. Each UAV 100a, 100b, 100c, 100d may comprise a receiver device 101a and means 105 for transporting a tree 135 to a designated truckW20320002116and / or trailer and / or load changer bed and / or self-driving pod 200e. The system 10 may further comprise at least one truck and / or trailer and / or load changer bed and / or self-driving pod 200a, 200b, 200c, 200d.
[0070] The system may further comprise a base station 120 comprising transmitter / receiver device 121 for receiving data indicative of at least one UAV parameter of the plurality of UAVs 100a, 100b, 100c, 10Od within an operating area 130, positions of the at least one truck and / or trailer and / or load changer bed and / or self-driving pod 200a, 200b, 200c, 200d, within the operating area 130, at least one tree handling parameter of the at least one truck and / or trailer and / or load changer bed and / or self-driving pod 200a, 200b, 200c, 200d, and at least one tree parameter of a tree 135. The base station 120 may, when remotely controlled, be operated by at least one human being (in other words as a “back office”), whereas, when autonomously controlled, be a base station 120 with programmed software algorithms used for supporting each UAV 100a, 100b, 100c, 100d. The base station 120 may be a stationary unit or a mobile unit. In various example embodiments, the base station 120 may be a UAV, e.g., a “master drone”. In various example embodiments, a satellite comprising transmitter / receiver device 121 for receiving data indicative of at least one UAV parameter of the plurality of UAVs 100a, 100b, 100c, 100d may be used to perform the methods and systems described herein.
[0071] The base station 120 may further be configured to a determine a designated UAV 100e based on the at least one tree parameter and the at least one UAV parameter, and to determine designated truck and / or trailer and / or load changer bed and / or self-driving pod 200e based on the at least one tree parameter, the positions of the at least one truck and / or trailer and / or load changer bed and / or self-driving pod 200a, 200b, 200c, 200d and the at least one tree handling parameter, and to transmit instructions to the designated UAV 100e, the instructions causing the designated UAV 100e to transport and unload the harvested tree to the designated truck and / or trailer and / or load changer bed and / or self-driving pod 200e. In various example embodiments each UAV 100a, 100b, 100c, 100d comprises a transmitter device 101b for transmitting dataW20320002117indicative of the at least one UAV parameter to be received by the transmitter / receiver device 121 of the base station 120. The receiver device 101a and transmitter device 101b of each UAVs 100a, 100b, 100c, 100d may be integrated as one device performing both functions. In various example embodiments each truck and / or trailer and / or load changer bed and / or self-driving pod 200a, 200b, 200c, 200d may comprise a transmitter device 201 for transmitting data indicative of a position of the truck and / or trailer and / or load changer bed and / or self-driving pod and the at least one tree handling parameter to the base station.
[0072] As depicted in figure 6, in various example embodiments at least one UAV 100a, 100b, 100c, 100d may comprise means 102 for detecting at least one tree parameter as described herein. The means 102 may be a camera or optical sensor in combination with Artificial Intelligence Al. Al may be used for training a model for recognizing one or a plurality of the tree parameters. Tree parameters may be recognized visually and / or by measurement and / or by at least on physical sample. Measurement may be made by optical inspection at a distance from the tree and / or by physical measurement, for instance integrated in means for gripping / holding tree present on at least one UAV 100a, 100b, 100c, 100d. The means 102 for detecting at least one tree parameter may be a laser scanner attached to the UAV 100a, 100b, 100c, 100d. By laser scanning the tree trunk the tree species may be determined and other surface conditions of the tree trunk such as the presence of any moss and / or any damage. Detected tree parameters may be compared with stored tree parameters in a data base for categorization and / or future choice and / or prioritization.
[0073] In various example embodiment at least one UAV 100a, 100b, 100c, 100d may comprise means 105 for unloading a tree 135 onto the designated truck and / or trailer and / or load changer bed and / or self-driving pod 200e. In figure 6, the UAV 100a is depicted as comprising the means 105 for unloading. The means 105 for unloading may be at least one movable gripping arm. In various example embodiments the means 105 may be one or a plurality of metal bars which may at least partially penetrate a tree trunk of a tree 135. In various exampleW20320002118embodiments the means 105 for unloading may be a unit surrounding the tree trunk and being able to change its holding area and thereby compress around a tree trunk of tree 135 for securing purposes and decompress for releasing a tree trunk or entering a tree 135. The means for unloading the tree may comprise the sample detection means. In various example embodiments, the means 105 for unloading a tree 135 onto the designated truck and / or trailer and / or load changer bed and / or self-driving pod 200e may comprise a receiving unit for unloading the tree and a cleaving unit for cutting / separating the tree into two or more pieces.
[0074] Alternatively, or additionally, the designated truck and / or trailer and / or load changer bed and / or self-driving pod 200e may comprise means 205 for unloading the tree 135 onto the designated truck and / or trailer and / or load changer bed and / or self-driving pod 200e from the designated UAV 100e. The means 205 for unloading the tree 135 arranged on the designated truck and / or trailer and / or load changer bed and / or self-driving pod 200e may be a loader arm of the like. In other words, these means 205 allow the designated truck and / or trailer and / or load changer bed and / or self-driving pod 200e to receive the tree 135.
[0075] In various example embodiments, wherein each UAV 100a, 100b, 100c, 100d further comprises a remotely and / or autonomously controlled tool 110 configured for harvesting at least a portion of a tree 135. The tool 110 configured for harvesting at least a portion of a tree 135 may include knives, saw-blades, motorized saws and / or knives, and the like.
[0076] The person skilled in the art realized that the present disclosure by no means is limited to the preferred embodiments described above. On the contrary, many modifications and variations are possible within the scope of the appended claims. It should further be noted that the drawings not necessarily are to scale, and dimensions of certain features may have been exaggerated for the sake of clarity. Emphasis is instead placed upon illustrating the principle of the embodiments herein. Additionally, in the claims, the word “comprising” does not exclude other elements or steps, and the indefinite article “a” or “an” does not exclude a plurality.W20320002119
[0077] Various examples have been described. These and other examples are within the scope of the following claims.
Claims
W20320002120CLAIMS1. A method for transporting a tree (135) within an operating area (130) comprising a plurality of remotely and / or autonomously controlled UAVs (100a, 100b, 100c, 10Od) and at least one truck and / or trailer and / or load changer bed and / or self-driving pod (200a, 200b, 200c, 200d), the method comprising:- receiving (S1), by a base station (120), data indicative of:o at least one UAV parameter of the plurality of UAVs (100a, 100b, 100c, 100d) within an operating area (130),o positions of the at least one truck and / or trailer and / or load changer bed and / or self-driving pod (200a, 200b, 200c, 200d) within the operating area (130),o at least one tree handling parameter of the at least one truck and / or trailer and / or load changer bed and / or self-driving pod (200a, 200b, 200c, 200d),o at least one tree parameter of a tree (135),- determining (S2), by the base station (120), a designated UAV (100e) based on the at least one tree parameter and the at least one UAV parameter,- determining (S3), by the base station (120) a designated truck and / or trailer and / or load changer bed and / or self-driving pod (200e) based on the at least one tree parameter, the positions of the at least one truck and / or trailer and / or load changer bed and / or self-driving pod (200a, 200b, 200c, 200d) and the at least one tree handling parameter,- transporting (S4) the tree (135), by the designated UAV (100e), to the designated truck and / or trailer and / or load changer bed and / or self-driving pod (200e),W20320002121- unloading (S5), by designated UAV (100e), the tree (135) onto the designated truck and / or trailer and / or load changer bed and / or self-driving pod (200e).
2. The method according to claim 1 , wherein the at least one UAV parameter comprises positions of the UAVs (100a, 100b, 100c, 100d) and / or transporting capacities of the UAVs (100a, 100b, 100c, 100d).
3. The method according to claim 1 or 2, wherein the at least one tree handling parameter comprises load capacities of the at least one truck and / or trailer and / or load changer bed and / or self-driving pod (200a, 200b, 200c, 200d) and / or tree type handling criteria of the at least one truck and / or trailer and / or load changed bed and / or self-driving pod (200a, 200b, 200c, 200d).
4. The method according to any one of claims 1-3, wherein the at least one tree parameter comprises at least one of: a position of a tree, a length of at least a portion of a tree, a tree species of a tree, and a weight of a tree.
5. The method according to any one of the preceding claims, wherein the data indicative of at least one UAV parameter of the UAVs (100a, 100b, 100c, 100d) and / or positions of the at least one truck and / or trailer and / or load changer bed and / or self-driving pod (200a, 200b, 200c, 200d) within the operating area (130) is time dependent.
6. The method according to one of the preceding claims, wherein determining (S2) the designated UAV (100e) further comprises matching a UAV (100a, 100b, 100c, 100d) with a tree (135) based on that the at least one UAV parameter is compatible with the at least one tree parameter.
7. The method according to any one of the preceding claims, wherein determining (S3) the designated truck and / or trailer(200e) further comprises matching a truck and / or trailer and / or load changed bed and / or self-driving pod (200a, 200b, 200c, 200d) with a tree (135) based on that the at least tree handling parameter is comparable with the at least one tree parameter.W203200021228. The method according to claim 7, wherein the at least one UAV parameter comprises positions of the UAVs (100a, 100b, 100c, 100d), and wherein determining (S3) the designated truck and / or trailer (100e) further comprises matching a UAV (100a, 100b, 100c, 100d) with a truck and / or trailer and / or load changed bed and / or self-driving pod (200a, 200b, 200c, 200d) closest to the UAV (100a, 100b, 100c, 100d).
9. The method according to any one of the preceding claims, wherein the data indicative of positions of the at least one truck and / or trailer and / or load changer bed and / or self-driving pod (200a, 200b, 200c, 200d) is received via at least one of a group of: a GPS, a mesh network, dead reckoning, and pattern detection.
10. The method according to any one of the preceding claims, wherein the data indicative of at least one tree parameter is provided by at least one of the UAVs (100a, 100b, 100c, 100d) comprising means (102) for determining the at least one tree parameter.
11. The method according to claim any one of the preceding claims, wherein the tree (135) is directly unloaded onto the designated truck and / or trailer and / or load changer bed and / or self-driving pod (200e) by means (105) of the designated UAV (100e).
12. The method according to claim any one of claims 1-11, wherein the tree (135) is indirectly unloaded onto the designated truck and / or trailer and / or load changed bed and / or self-driving pod (200e) by means (205) of the designated truck and / or trailer and / or load changer bed and / or self-driving pod (200e).
13. The method according to any of the preceding claims, the method further comprising harvesting the tree (135), by means of the designated UAV (100e).
14. The method according to claims 13, wherein the harvesting further comprises delimbing the tree (135), by means of the designated UAV (100e).W2032000212315. A system (10) for transporting a tree (135) within an operating area (130), the system (10) comprising:- a plurality of remotely and / or autonomously controlled unmanned aerial vehicles, UAVs (100a, 100b, 100c, 100d), wherein each UAV (100a, 100b, 100c, 100d) comprises a receiver device (101a) and means (105) for transporting a tree (135),- at least one truck and / or trailer and / or load changed bed and / or self-driving pod (200a, 200b, 200c, 200d),- a base station (120) comprising transmitter / receiver device (121) for receiving data indicative of at least one UAV parameter of the plurality of UAVs (100a, 100b, 100c, 100d) within an operating area (130), positions of the at least one truck and / or trailer and / or load changer bed and / or selfdriving pod (200a, 200b, 200c, 200d), within the operating area (130), at least one tree handling parameter of the at least one truck and / or trailer and / or load changer bed and / or self-driving pod (200a, 200b, 200c, 200d), and at least one tree parameter of a tree (135), the base station (120) is further configured to a determine a designated UAV (100e) based on the at least one tree parameter and the at least one UAV parameter, and to determine designated truck and / or trailer and / or load changed bed and / or self-driving pod (200e) based on the at least one tree parameter, the positions of the at least one truck and / or trailer and / or load changer bed and / or self-driving pod (200a, 200b, 200c, 200d) and the at least one tree handling parameter, and to transmit instructions to the designated UAV (100e), the instructions causing the designated UAV (100e) to transport and unload the tree (135) to the designated truck and / or trailer and / or load changer bed and / or self-driving pod (200e).
16. The system (10) according to claim 15, wherein each UAV (100a, 100b, 100c, 100d) comprises a transmitter device (101b) for transmitting data indicative of the at least one UAV parameter to be received by the transmitter / receiver device (121) of the base station (120).W2032000212417. The system (10) according to claim 16, wherein at least one UAV (100a, 100b, 100c, 100d) comprises means (102) for determining the at least one tree parameter.
18. The system (10) according to any one of claims 15-17, wherein each truck and / or trailer and / or load changer bed and / or self-driving pod (200a, 200b, 200c, 200d) comprises a transmitter device (201) for transmitting data indicative of a position of the truck and / or trailer and / or load changed bed and / or self-driving pod and the at least one tree handling parameter to the base station.
19. The system (10) according to any one of claims 15-18, wherein at least one UAV (100a, 100b, 100c, 100d) comprises means (105) for unloading the tree (135) onto the designated truck and / or trailer and / or load changer bed and / or selfdriving pod (200e).
20. The system (10) according to any one of claims 15-19, wherein the designated truck and / or trailer and / or load changer bed and / or self-driving pod (200e) comprises means for (205) for unloading the tree (135) onto the designated truck and / or trailer and / or load changer bed and / or self-driving pod (200e) from the designated UAV (100e).
21. The system according to any one of claims 15-20, wherein each UAV (100a, 100b, 100c, 100d) further comprises a remotely and / or autonomously controlled tool (110) configured for harvesting at least a portion of the tree (135).