Forest harvester with automated optimal bucking guidance system

Abstract

A bucking guidance system for a forest harvester includes a perception sensor configured to image a set of trees and produce perception data comprising a digital representation of at least one tree. The system also includes a control unit configured to process the perception data to determine an optimal bucking sequence for a trunk of the at least one tree and provide control instructions for the forest harvester to buck the trunk according to the optimal bucking sequence.

Description

[0001] Forest Harvester with Automated Optimal Bucking Guidance System

[0002] Field

[0003] The technology relates to the field of forestry and logging, specifically to the development of advanced forest harvesting equipment and systems for optimizing the cutting and processing of trees into logs.

[0004] The forestry industry plays a crucial role in providing various wood products, such as lumber, paper, and pulp, which are essential for numerous applications in construction, manufacturing, and other industries. One of the critical processes in the forestry industry is the harvesting of trees and the subsequent conversion of tree trunks into logs, which are then processed further to produce the desired wood products. This process, known as bucking, involves cutting a tree trunk into multiple logs of varying lengths and quality, depending on the intended use of the logs.

[0005] In recent years, the cut-to-length (CTL) method has become a popular approach for forest harvesting operations. The CTL method involves bucking the tree trunks directly in the forest, immediately after the tree is felled. This method offers several advantages, such as reduced transportation costs and minimized environmental impact. However, the CTL method also presents several challenges, particularly in terms of maximizing the quality and value of the logs obtained from each tree.

[0006] One of the main challenges in the bucking process is accounting for the shape irregularities of the tree trunks, such as bends, twists, and knots. These irregularities can significantly affect the quality and value of the logs obtained from the tree, as high- value lumber products, such as beams, planks, and boards, can only be produced from straight, defect-free logs. Logs with shape irregularities are typically used for lower- value products, such as paper, pulp, or firewood, which have a shorter lifespan in the carbon cycle. Therefore, it is both financially and environmentally beneficial to maximize the ratio of high-quality lumber logs obtained from each tree. Modern forest harvesting machines are equipped with automatic bucking systems that rely on mechanical measurements of log lengths to determine the optimal bucking points based on an up-to-date lumber price list. However, these systems do not account for the shape irregularities of the tree trunks, which can lead to suboptimal bucking decisions and a lower overall yield of high-quality logs. Instead, it is up to the operator to manually override the automatic system to account for shape irregularities, which can be a slow and error-prone process.

[0007] Furthermore, the operator's limited visual perspective may make it difficult to accurately detect and assess shape irregularities, particularly those that are oriented in a way that makes them less visible from the operator's position. This can lead to errors in manual overrides and a further reduction in the overall yield of high-quality logs. Additionally, the reliance on manual overrides can negatively impact the overall productivity of the CTL operations, as the process interrupts the otherwise automated workflow and introduces an element of uncertainty for the operator.

[0008] Summary

[0009] According to a first aspect of the disclosure, a bucking guidance system for a forest harvester is provided. This system comprises a perception sensor configured to image a set of trees and produce perception data. This data comprises a digital representation of at least one tree. The system also includes a control unit. This control unit is configured to process the perception data to determine an optimal bucking sequence for a trunk of the at least one tree. The control unit is also configured to provide control instructions for the forest harvester to buck the trunk according to the optimal bucking sequence. This aspect of the disclosure allows for more efficient and precise bucking of trees, leading to increased productivity and reduced waste.

[0010] Optionally in some examples, the control unit is configured to process the perception data using a tree detection algorithm. This algorithm determines which subsets of the perception data correspond to individual trees. This feature allows for the accurate identification and separation of individual trees within the perception data, improving the accuracy of the bucking process. Optionally in some examples, the control unit is configured to process the subsets of perception data using a shape estimation algorithm. This algorithm determines a geometric representation of each tree. This feature allows for a detailed understanding of the shape and structure of each tree, enabling more precise and efficient bucking.

[0011] Optionally in some examples, the control unit is configured to process the perception data using an optimal bucking algorithm. This algorithm computes the optimal bucking sequence from the geometric representation and a set of bucking optimization criteria. This feature allows for the determination of the most efficient sequence of cuts to maximize the value of the harvested wood.

[0012] Optionally in some examples, the bucking optimization criteria include at least one of maximizing the number of straight, high-value logs obtained from each tree, minimizing the length of logs containing shape irregularities, minimizing waste and maximizing yield from each tree, and maximizing product value given a prize list and constraints imposed by shape irregularities. This feature allows for the optimization of the bucking process based on a variety of factors, leading to increased yield and value from each harvested tree.

[0013] Optionally in some examples, the bucking guidance system further comprises a communication system. This system is configured to transmit the control instructions to the bucking guidance system or the operator. This feature allows for efficient communication of instructions, improving the speed and accuracy of the bucking process.

[0014] Optionally in some examples, the bucking guidance system further comprises a display. This display is configured to communicate control instructions to an operator. This feature provides a clear and easily understandable method of communicating instructions to the operator, improving the ease of use of the system.

[0015] Optionally in some examples, the perception sensor is selected from the group consisting of a lidar sensor, a camera, and a radar sensor. Optionally in some examples, the perception sensor is mounted on the forest harvester. This feature allows for the direct and immediate imaging of the trees by the sensor, improving the accuracy and timeliness of the perception data.

[0016] Optionally in some examples, the geometric representation comprises at least one of a 3D point cloud representation of the tree trunk, a 3D mesh representation generated from the perception data, and a parametric geometric model, for example a set of circles or ellipses with dimensions, positions and orientations that represent the geometry of the tree. This feature allows for a detailed and accurate representation of the tree, improving the precision of the bucking process.

[0017] Optionally in some examples, the optimal bucking sequence provides cutting positions for the trunk. This feature provides clear and precise instructions for the bucking process, improving the efficiency and accuracy of the process.

[0018] Optionally in some examples, the forest harvester is controlled by an operator to buck the trunk according to the control instructions. This feature allows for the involvement of a human operator in the bucking process, providing flexibility and the ability to respond to unexpected situations.

[0019] Optionally in some examples, the forest harvester bucks the trunk automatically according to the control instructions. This feature allows for the automation of the bucking process, reducing the need for human intervention and increasing efficiency.

[0020] According to a second aspect of the disclosure, a forest harvester comprising the bucking guidance system is provided. This aspect of the disclosure allows for the integration of the bucking guidance system into a forest harvester, providing a complete solution for the efficient and precise bucking of trees.

[0021] Optionally in some examples, the forest harvester further comprises a cutting head configured to buck the trunk according to the optimal bucking sequence. This feature allows for the direct implementation of the bucking sequence by the cutting head, improving the efficiency and accuracy of the bucking process. According to a third aspect of the disclosure, a method of operating a bucking guidance system for a forest harvester is provided. This method comprises imaging a set of trees with a perception sensor to produce perception data. This data comprises a digital representation of at least one of the set of trees. The method also includes processing the perception data with a control unit to determine an optimal bucking sequence for a trunk of the at least one tree. The method further includes providing control instructions for the forest harvester to buck the trunk according to the optimal bucking sequence. This aspect of the disclosure provides a clear and efficient method for operating the bucking guidance system, leading to improved productivity and reduced waste.

[0022] Brief Description of the Drawings

[0023] Examples are described in more detail below with reference to the appended drawings. Figure 1 is a schematic view of a forest harvester 100 equipped with a bucking guidance system 20.

[0024] Figure 2 is a block diagram illustrating the components of the bucking guidance system 20.

[0025] Figure 3 is a flowchart depicting the operation of the bucking guidance system 20 in determining an optimal bucking sequence for a tree trunk.

[0026] Figure 4 is an example of perception data 35 generated by the perception sensor 30 and comprising a digital representation of a tree trunk.

[0027] Figure 5 is a graphical representation of an optimal bucking sequence determined by the optimal bucking algorithm 46.

[0028] Detailed Description

[0029] The detailed description set forth below provides information and examples of the disclosed technology with sufficient detail to enable those skilled in the art to practice the disclosure.

[0030] Figure 1 shows a forest harvester 100 with a cutting head 10. The cutting head 10 is designed to cut trees 55 into multiple logs. The forest harvester 100 is equipped with a bucking guidance system 20, which may be integrated or retrofitted to the forest harvester 100. Figure 2 shows a detailed block diagram of the bucking guidance system 20. The system includes a perception sensor 30, which images a set of trees 55 to produce perception data 35. The perception data 35 comprises a digital representation of the trunk of the trees 55. The perception sensor 30 can be a lidar, camera, or radar and is mounted on the forest harvester 100. The bucking guidance system 20 also includes a control unit 40, which processes data from the perception sensor 30 to determine an optimal bucking sequence 45 for a trunk of a trees 55. The control unit 40 provides control instructions 41 to buck the trunk according to the optimal bucking sequence 45. The control instructions 41 can be transmitted electronically to the cutting head 10 for automated operation or to the operator to guide the control cutting head 10 to buck the trunk.

[0031] Figure 3 shows a flowchart of the operation of the bucking system. The process begins with the perception sensor 30 scanning and analyzing the shape of tree trunks. The computer then processes data from the perception sensor. The tree detection algorithm 42 determines which subsets of the perception data 35 correspond to individual trees 55. The shape estimation algorithm 44 determines a geometric representation of each tree based on the perception data 35. The optimal bucking algorithm 46 computes the optimal bucking sequence 45 from the geometric representation and a set of bucking optimization criteria. The display communicates supporting information to the operator.

[0032] Figure 4 shows an example of perception data 35 generated by the perception sensor 30, comprising a digital representation of a set of trees 55 in a forest. The perception data 35 comprises a detailed digital image of the tree trunk, showing its position, shape and any irregularities.

[0033] Figure 5 shows a tree 55 with an optimal bucking sequence 45. The optimal bucking sequence 45 provides the optimal cutting positions for the trunk of the tree 55. The sequence is determined by the control unit 40 based on the perception data 35 and the bucking optimization criteria. The bucking optimization criteria may include maximizing the number of straight, high-value logs obtained from each tree, minimizing the length of logs containing shape irregularities, and minimizing waste and maximizing yield from each tree.

[0034] 1 . Forest Harvester Details

[0035] The forest harvester 100 is a specialized machine designed for the task of felling, delimbing, and bucking trees in a forest environment. The forest harvester 100 is typically a large, heavy-duty vehicle equipped with a variety of components and systems to facilitate the efficient and safe harvesting of trees. The forest harvester 100 may be designed to operate in a variety of terrains and weather conditions, and may be capable of handling a wide range of tree sizes and species. The forest harvester 100 may be operated by a human operator, or it may be capable of semi-autonomous or fully autonomous operation.

[0036] 1 .1 . Cutting Head

[0037] The cutting head 10 of the forest harvester 100 is responsible for the physical task of cutting the trees. The cutting head 10 may be a robust and powerful tool capable of cutting through the trunks of trees with precision and efficiency. The cutting head 10 may be equipped with a variety of cutting tools, such as chainsaws, circular saws, or other types of cutting blades. The cutting head 10 may be designed to cut trees at their base, and may also be capable of bucking the trees into multiple logs. The cutting head 10 may be mounted on a movable arm or boom, allowing it to reach and cut trees in various positions relative to the forest harvester 100. The cutting head 10 may be controlled by the operator of the forest harvester 100, or it may be controlled automatically based on instructions from a control unit 40.

[0038] 1.2. Bucking Guidance System

[0039] The bucking guidance system 20 is a system integrated into the forest harvester 100 that provides guidance for the bucking process. The bucking process involves cutting a felled tree into multiple logs, and the bucking guidance system 20 is designed to optimize this process based on a variety of factors. The bucking guidance system 20 may include a variety of components, such as a perception sensor 30, a control unit 40, and a communication system. The bucking guidance system 20 may be designed to maximize the yield of high-value logs from each tree, minimize waste, and optimize the overall efficiency of the harvesting operation.

[0040] 1.2.1. Perception Sensor

[0041] The perception sensor 30 is configured to image the set of trees 55 and produce perception data 35. The perception sensor 30 may be a capable of producing high- resolution, three-dimensional images of the trees. The perception sensor 30 may use a variety of imaging technologies, such as lidar, camera, or radar. The perception sensor 30 may be mounted on the forest harvester 100 in a position that allows it to image the trees from a suitable angle and distance. The perception sensor 30 may be capable of imaging the trees in a variety of lighting conditions and weather conditions. The perception data 35 produced by the perception sensor 30 may include a digital representation of the trunk of the trees 55, which may be used by the control unit 40 to determine an optimal bucking sequence 45.

[0042] 1.2.1.1. Perception Data

[0043] The perception data 35 is the output produced by the perception sensor 30. The perception data 35 comprises a digital representation of the set of trees 55 that have been imaged by the perception sensor 30. The perception data 35 may be in the form of a three-dimensional point cloud, a two-dimensional image, or any other suitable format. The perception data 35 may include information about the size, shape, and orientation of the trees, as well as other relevant features. The perception data 35 may be processed by the control unit 40 to extract useful information for the bucking process.

[0044] 1.2.1.1.1. Comprises A Digital Representation Of The Trunk Of The Trees

[0045] In some implementations, the perception data 35 comprises a digital representation of the trunk of the trees 55. This digital representation may be a detailed, three- dimensional model of the trunk, including information about its size, shape, and orientation. The digital representation may be generated based on the raw data collected by the perception sensor 30, using a variety of image processing and computer vision techniques. The digital representation of the trunk may be used by the control unit 40 to determine an optimal bucking sequence 45 for the tree.

[0046] 1 .2.2. Control Unit

[0047] The control unit 40 is a component of the bucking guidance system 20 that processes the perception data 35 and determines an optimal bucking sequence 45 for the trunk of the trees 55. The control unit 40 may be a computer or a similar device equipped with a processor, memory, and other necessary hardware and software. The control unit 40 may use a variety of algorithms and computational techniques to process the perception data 35 and determine the optimal bucking sequence 45. The control unit 40 may also provide control instructions 41 to the cutting head 10 of the forest harvester 100, instructing it to buck the trunk according to the optimal bucking sequence 45.

[0048] 1 .2.2.1. Control Instructions

[0049] The control instructions 41 are instructions generated by the control unit 40 for operating the cutting head 10 of the forest harvester 100. The control instructions 41 are based on the optimal bucking sequence 45 determined by the control unit 40. The control instructions 41 may specify the exact positions and orientations at which the cutting head 10 should cut the trunk to produce the desired logs. The control instructions 41 may be transmitted electronically to the cutting head 10 for automated operation, or they may be displayed to the operator of the forest harvester 100 to guide manual operation.

[0050] 1 .2.2.2. Tree Detection Algorithm

[0051] In some configurations, the control unit 40 uses a tree detection algorithm 42 to process the perception data 35. The tree detection algorithm 42 is a computational algorithm designed to determine which subsets of the perception data 35 correspond to individual trees 55. The tree detection algorithm 42 may use a variety of techniques, such as image segmentation, pattern recognition, machine learning, or other suitable methods. The tree detection algorithm 42 may be capable of accurately identifying individual trees 55 even in complex forest environments with overlapping trees and other visual clutter. The output of the tree detection algorithm 42 may be used by the control unit 40 to determine an optimal bucking sequence 45 for each identified tree.

[0052] 1 .2.2.3. Shape Estimation Algorithm

[0053] In some examples, the control unit 40 uses a shape estimation algorithm 44 to process the perception data 35. The shape estimation algorithm 44 is a computational algorithm designed to determine a geometric representation of each tree based on the perception data 35. The shape estimation algorithm 44 may use a variety of techniques, such as point cloud segmentation, point cloud clustering, random sample consensus, spline interpolation, curve fitting, optimization, dense reconstruction, or other suitable methods. The shape estimation algorithm 44 may be capable of accurately estimating the shape of the trunk of the tree, including any shape irregularities, based on the perception data 35. The output of the shape estimation algorithm 44 may be used by the control unit 40 to determine an optimal bucking sequence 45 for each tree.

[0054] 1 .2.2.4. Optimal Bucking Algorithm

[0055] In some implementations, the control unit 40 uses an optimal bucking algorithm 46 to determine the optimal bucking sequence 45. The optimal bucking algorithm 46 is a computational algorithm designed to compute the optimal bucking sequence from the geometric representation of the tree and a set of bucking optimization criteria. The optimal bucking algorithm 46 may use a variety of techniques, such as rule-based algorithms, nonlinear optimization algorithms (such as interior point, simulated annealing, genetic algorithm, Bayesian optimization, branch and bound), or other suitable methods. The optimal bucking algorithm 46 may be capable of determining the optimal sequence of cuts to maximize the yield of high-value logs, minimize waste, and optimize the overall efficiency of the harvesting operation.

[0056] 1 .2.2.5. Geometric Representation The geometric representation is a digital model of the tree that is generated by the shape estimation algorithm 44 based on the perception data 35. The geometric representation may be a three-dimensional model that accurately represents the size, shape, and orientation of the tree. The geometric representation may include detailed information about the trunk of the tree, including any shape irregularities. The geometric representation may be used by the optimal bucking algorithm 46 to determine the optimal bucking sequence 45. The geometric representation may comprise at least one of a 3D point cloud representation of the tree trunk, a 3D mesh representation generated from the perception data (35), or a parametric geometric model, for example a set of circles or ellipses with dimensions, positions and orientations that represent the geometry of the tree.

[0057] 1 .2.2.6. Optimal Bucking Sequence

[0058] The optimal bucking sequence 45 is a sequence of cuts determined by the control unit 40 that optimizes the yield of high-value logs from the tree. The optimal bucking sequence 45 is based on the geometric representation of the tree and a set of bucking optimization criteria. The optimal bucking sequence 45 may specify the exact positions and orientations at which the cutting head 10 should cut the trunk to produce the desired logs. The optimal bucking sequence 45 may be communicated to the cutting head 10 or the operator of the forest harvester 100 via the control instructions 41 . The optimal bucking sequence 45 may comprise, or may be said to be indicative of a longitudinal quality index. The longitudinal quality index may provide a quality index for all parts of the trunk, indicating the lumber quality of each section. For example, long straight sections, sections with minor curvature, sections with significant curvature, sections with damages or other forms of shape irregularities will all have different LQI. In other words, the longitudinal quality index may indicate the lumber quality of each section of the tree. Hence, the existing bucking computer has additional information to use in the existing optimization scheme. For example, if there's a bent bit in the middle, but the tree is otherwise straight, the middle bit would get a different quality index, and the existing functionality in the existing bucking computer could account for that.

[0059] 1 .2.2.7. Bucking Optimization Criteria The bucking optimization criteria are a set of criteria used by the optimal bucking algorithm 46 to determine the optimal bucking sequence 45. The bucking optimization criteria may include a variety of factors, such as maximizing the number of straight, high-value logs obtained from each tree, minimizing the length of logs containing shape irregularities, minimizing waste and maximizing yield from each tree, and maximizing product value given a prize list and constraints imposed by shape irregularities. The bucking optimization criteria may be predefined, or they may be dynamically adjusted based on the specific conditions of the harvesting operation.

[0060] 1.2.3. Display

[0061] In some examples, the bucking guidance system 20 includes a display. The display may be a screen, head-up display, or augmented reality glasses that are used to communicate information to the operator of the forest harvester 100. The display may show the control instructions 41 , the optimal bucking sequence 45, or other relevant information. The display may be designed to present the information in a clear, concise, and easily understandable format. The display may be located in a position that is easily visible to the operator, and it may be designed to be easily readable in a variety of lighting conditions and weather conditions.

[0062] An audible indicator may also be used independently or in combination with the display. In one configuration, an audible indicator is used to signal that a manual override should be considered or is required by the operator to ensure a successful bucking operation by the harvester.

[0063] 1.2.4. Communication System

[0064] In some configurations, the bucking guidance system 20 includes a communication system. The communication system is responsible for transmitting the control instructions 41 and the optimal bucking sequence 45 from the control unit 40 to the cutting head 10 or the operator. The communication system may use a variety of communication technologies, such as wired or wireless communication protocols. The communication system may be designed to ensure reliable and timely transmission of the control instructions 41 and the optimal bucking sequence 45, even in challenging environmental conditions.

[0065] 1 .3. Operator

[0066] The operator is the person who operates the forest harvester 100 and the bucking guidance system 20. The operator may be a trained professional who is skilled in the operation of forest harvesting equipment. The operator may control the movement of the forest harvester 100, the operation of the cutting head 10, and the operation of the bucking guidance system 20. The operator may also be responsible for monitoring the operation of the forest harvester 100 and the bucking guidance system 20, and for making manual adjustments or overrides when necessary. The operator may use the display to receive information about the control instructions 41 and the optimal bucking sequence 45, and to monitor the operation of the forest harvester 100 and the bucking guidance system 20.

[0067] 2. Trees Details

[0068] The trees 55 are the targets of the harvesting operation performed by the forest harvester 100. The trees 55 may be of various species, sizes, and shapes. Each tree 55 includes a trunk, which is the part of the tree that is cut into logs by the cutting head 10. The trunk of the tree may have various shape irregularities, such as bends, knots, or other deformations. The perception sensor 30 images the trees 55 to produce the perception data 35, which includes a digital representation of the trunk of the trees 55. The control unit 40 processes the perception data 35 to determine an optimal bucking sequence 45 for the trunk of each tree 55. The cutting head 10 then bucks the trunk according to the optimal bucking sequence 45, producing a set of logs.

[0069] 2.1. Trunk

[0070] The trunk is the part of the tree 55 that is cut into logs by the cutting head 10. The trunk is typically a cylindrical or conical structure that extends from the base of the tree to the branches. The trunk is composed of wood, and its size, shape, and quality can vary greatly depending on the species of the tree, its age, and its growing conditions. The trunk may have various shape irregularities, such as bends, knots, or other deformations. These shape irregularities can affect the quality and value of the logs produced from the trunk, and they are taken into account by the control unit 40 when determining the optimal bucking sequence 45.

[0071] 3. Logs Details

[0072] The logs are the products of the bucking process performed by the forest harvester 100. The logs are sections of the trunk of the tree 55 that have been cut by the cutting head 10 according to the optimal bucking sequence 45. The logs may be of various lengths and diameters, depending on the size of the trunk and the bucking sequence. The logs may be used for a variety of purposes, such as lumber, pulp, or fuel. The quality and value of the logs can depend on various factors, such as the species of the tree, the quality of the wood, and the presence of shape irregularities in the trunk. The bucking guidance system 20 is designed to maximize the yield of high-value logs from each tree, by determining an optimal bucking sequence 45 that takes into account the size, shape, and quality of the trunk.

[0073] 4. Operational Process

[0074] The operational process is the sequence of steps performed by the forest harvester 100 and the bucking guidance system 20 to fell the trees 55 and buck them into logs. The operational process begins with the perception sensor 30 imaging the set of trees 55 to produce the perception data 35. The perception data 35 is then processed by the control unit 40, which uses a tree detection algorithm 42, a shape estimation algorithm 44, and an optimal bucking algorithm 46 to determine an optimal bucking sequence 45 for the trunk of each tree 55. The control unit 40 then provides control instructions 41 to the cutting head 10 or the operator, instructing them to buck the trunk according to the optimal bucking sequence 45.

[0075] 4.1. Initial Scanning and Data Collection

[0076] The initial scanning and data collection is the first step of the operational process. During this step, the perception sensor 30 images the set of trees 55 to produce the perception data 35. The perception sensor 30 may use a variety of imaging technologies, such as lidar, camera, or radar, to produce a high-resolution, three- dimensional image of the trees. The perception data 35 includes a digital representation of the trunk of the trees 55, which is used by the control unit 40 to determine the optimal bucking sequence 45.

[0077] 4.1.1. Tree Identification and Segmentation

[0078] In some examples, the control unit 40 uses a tree detection algorithm 42 to identify individual trees 55 in the perception data 35. The tree detection algorithm 42 determines which subsets of the perception data 35 correspond to individual trees. This process, known as tree identification and segmentation, is a necessary step for determining the optimal bucking sequence 45 for each tree. The tree detection algorithm 42 may use a variety of techniques, such as image segmentation, pattern recognition, or machine learning, to accurately identify individual trees even in complex forest environments with overlapping trees and other visual clutter.

[0079] 4.2. Data Analysis and Sequence Determination

[0080] The data analysis and sequence determination is the next step of the operational process. During this step, the control unit 40 processes the perception data 35 to determine an optimal bucking sequence 45 for the trunk of each tree 55. The control unit 40 uses a shape estimation algorithm 44 to determine a geometric representation of each tree, and an optimal bucking algorithm 46 to compute the optimal bucking sequence from the geometric representation and a set of bucking optimization criteria. The bucking optimization criteria may include factors such as maximizing the number of straight, high-value logs obtained from each tree, minimizing the length of logs containing shape irregularities, and minimizing waste and maximizing yield from each tree. The result of this step is a set of control instructions 41 that instruct the cutting head 10 or the operator to buck the trunk according to the optimal bucking sequence 45.

[0081] 4.2.1. Geometric Representation and Bucking Sequence Computation In some implementations, the control unit 40 uses a shape estimation algorithm 44 to determine a geometric representation of each tree based on the perception data 35. The geometric representation may be a detailed, three-dimensional model of the trunk, including information about its size, shape, and orientation. The geometric representation may be generated based on the raw data collected by the perception sensor 30, using a variety of image processing and computer vision techniques. The geometric representation of the trunk may be used by the control unit 40 to determine an optimal bucking sequence 45 for the tree. The control unit 40 uses an optimal bucking algorithm 46 to compute the optimal bucking sequence from the geometric representation and a set of bucking optimization criteria. The optimal bucking algorithm 46 may use a variety of techniques, such as rule-based algorithms, nonlinear optimization algorithms, or other suitable methods. The optimal bucking algorithm 46 may be capable of determining the optimal sequence of cuts to maximize the yield of high-value logs, minimize waste, and optimize the overall efficiency of the harvesting operation.

[0082] 4.3. Execution of Bucking Sequence

[0083] The execution of the bucking sequence is the final step of the operational process. During this step, the cutting head 10 or the operator bucks the trunk of each tree 55 according to the control instructions 41 provided by the control unit 40. The control instructions 41 specify the exact positions and orientations at which the cutting head 10 should cut the trunk to produce the desired logs. The control instructions 41 may be transmitted electronically to the cutting head 10 for automated operation, or they may be displayed to the operator of the forest harvester 100 to guide manual operation. The execution of the bucking sequence results in the production of a set of logs from each tree 55.

[0084] Example 1 : A bucking guidance system for a forest harvester, the system comprising a perception sensor configured to image a set of trees and produce perception data comprising a digital representation of at least one tree, and a control unit configured to process the perception data to determine an optimal bucking sequence for a trunk of the at least one tree and provide control instructions for the forest harvester to buck the trunk according to the optimal bucking sequence. Example 2: The bucking guidance system of example 1 , wherein the control unit is configured to process the perception data using a tree detection algorithm to determine which subsets of the perception data correspond to individual trees.

[0085] Example 3: The bucking guidance system of example 2, wherein the control unit is configured to process the subsets of perception data using a shape estimation algorithm to determine a geometric representation of each tree.

[0086] Example 4: The bucking guidance system of any one of examples 1 to 3, wherein the control unit is configured to process the perception data using an optimal bucking algorithm to compute the optimal bucking sequence from the geometric representation and a set of bucking optimization criteria.

[0087] Example 5: The bucking guidance system of example 4, wherein the bucking optimization criteria include at least one of maximizing the number of straight, high- value logs obtained from each tree, minimizing the length of logs containing shape irregularities, minimizing waste and maximizing yield from each tree, and maximizing product value given a prize list and constraints imposed by shape irregularities.

[0088] Example 6: The bucking guidance system of any one of examples 1 to 5, further comprising a communication system configured to transmit the control instructions to the bucking guidance system or the operator.

[0089] Example 7: The bucking guidance system of any one of examples 1 to 6, further comprising a display configured to communicate control instructions to an operator.

[0090] Example 8: The bucking guidance system of any one of examples 1 to 7, further comprising an audible indicator for signaling to an operator that a manual override should be considered or is required by the operator.

[0091] Example 9: The bucking guidance system of any one of examples 1 to 8, wherein the perception sensor is selected from the group consisting of a lidar sensor, a camera, and a radar sensor. Example 10: The bucking guidance system of any one of examples 1 to 9, wherein the perception sensor is mounted on the forest harvester.

[0092] Example 11 : The bucking guidance system of any one of examples 1 to 10, wherein the geometric representation comprises at least one of a 3D point cloud representation of the tree trunk, a 3D mesh representation generated from the perception data, or a parametric geometric model.

[0093] Example 12: The bucking guidance system of any one of examples 1 to 11 , wherein the optimal bucking sequence provides cutting positions for the trunk.

[0094] Example 13: The bucking guidance system of any one of examples 1 to 12, wherein the forest harvester is controlled by an operator to buck the trunk according to the control instructions.

[0095] Example 14: The bucking guidance system of any one of examples 1 to 12, wherein the forest harvester bucks the trunk automatically according to the control instructions.

[0096] Example 15: A forest harvester comprising the bucking guidance system according to any one of examples 1 to 14.

[0097] Example 16: The forest harvester according to example 15, further comprising a cutting head configured to buck the trunk according to the optimal bucking sequence.

[0098] Example 17: A method of operating a bucking guidance system for a forest harvester, the method comprising imaging a set of trees with a perception sensor to produce perception data comprising a digital representation of at least one of the set of trees, processing the perception data with a control unit to determine an optimal bucking sequence for a trunk of the at least one tree, and providing control instructions for the forest harvester to buck the trunk according to the optimal bucking sequence.

[0099] The terminology used herein is for the purpose of describing particular aspects only and is not intended to be limiting of the disclosure. As used herein, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. As used herein, the term "and / or" includes any and all combinations of one or more of the associated listed items. It will be further understood that the terms "comprises," "comprising," "includes," and / or "including" when used herein specify the presence of stated features, integers, actions, steps, operations, elements, and / or components, but do not preclude the presence or addition of one or more other features, integers, actions, steps, operations, elements, components, and / or groups thereof.

[0100] It will be understood that, although the terms first, second, etc., may be used herein to describe various elements, these elements should not be limited by these terms. These terms are only used to distinguish one element from another. For example, a first element could be termed a second element, and, similarly, a second element could be termed a first element without departing from the scope of the present disclosure.

[0101] Relative terms such as "below" or "above" or "upper" or "lower" or "horizontal" or "vertical" may be used herein to describe a relationship of one element to another element as illustrated in the Figures. It will be understood that these terms and those discussed above are intended to encompass different orientations of the device in addition to the orientation depicted in the Figures. It will be understood that when an element is referred to as being "connected" or "coupled" to another element, it can be directly connected or coupled to the other element, or intervening elements may be present. In contrast, when an element is referred to as being "directly connected" or "directly coupled" to another element, there are no intervening elements present.

[0102] Unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this disclosure belongs. It will be further understood that terms used herein should be interpreted as having a meaning consistent with their meaning in the context of this specification and the relevant art and will not be interpreted in an idealized or overly formal sense unless expressly so defined herein.

[0103] It is to be understood that the present disclosure is not limited to the aspects described above and illustrated in the drawings; rather, the skilled person will recognize that many changes and modifications may be made within the scope of the present disclosure and appended claims. In the drawings and specification, there have been disclosed aspects for purposes of illustration only and not for purposes of limitation, the scope of the disclosure being set forth in the following claims.

Claims

Claims1 . A bucking guidance system (20) for a forest harvester (100), the system comprising: a perception sensor (30) configured to image a set of trees and produce perception data (35) comprising a digital representation of at least one tree; a control unit (40) configured to: process the perception data (35) to determine an optimal bucking sequence for a trunk of the at least one tree; and provide control instructions for the forest harvester (100) to buck the trunk according to the optimal bucking sequence.

2. The bucking guidance system (20) according to claim 1 , wherein the control unit (40) is configured to process the perception data (35) using a tree detection algorithm (42) to determine which subsets of the perception data (35) correspond to individual trees.

3. The bucking guidance system (20) according to claim 2, wherein the control unit (40) is configured to process the subsets of perception data (35) using a shape estimation algorithm (44) to determine a geometric representation of each tree.

4. The bucking guidance system (20) according to any one of claims 1 to 3, wherein the control unit (40) is configured to process the perception data (35) using an optimal bucking algorithm (46) to compute the optimal bucking sequence from the geometric representation and a set of bucking optimization criteria.

5. The bucking guidance system (20) according to claim 4, wherein the bucking optimization criteria include at least one of maximizing the number of straight, high- value logs obtained from each tree, minimizing the length of logs containing shape irregularities, minimizing waste and maximizing yield from each tree, and maximizing product value given a prize list and constraints imposed by shape irregularities.

6. The bucking guidance system (20) according to any one of claims 1 to 5, further comprising a communication system configured to transmit the control instructions to the bucking guidance system (20) or the operator.

7. The bucking guidance system (20) according to any one of claims 1 to 6, further comprising a display configured to communicate control instructions to an operator.

8. The bucking guidance system (20) according to any one of claims 1 to 7, further comprising an audible indicator for signalling to an operator that a manual override should be considered or is required by the operator.

9. The bucking guidance system (20) according to any one of claims 1 to 8, wherein the perception sensor (30) is selected from the group consisting of a lidar sensor, a camera, and a radar sensor.

10. The bucking guidance system (20) according to any one of claims 1 to 9, wherein the perception sensor (30) is mounted on the forest harvester (100).

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