Large manipulator and method for continuously deriving a three-dimensional model of the surroundings of a large manipulator

Abstract

The invention relates to a large manipulator, in particular a truck-mounted concrete pump, comprising: a boom pedestal which can be rotated about a vertical axis by means of a rotary drive and is arranged on a frame; an articulated boom which comprises two or more boom segments, wherein the boom segments are pivotally connected via articulated joints to the adjacent boom pedestal or boom segment, respectively, by means of a pivot drive in each case; and a control device which is designed to actuate the rotary drive and the pivot drives of the large manipulator. At least one surroundings detection sensor for continuously detecting information regarding the surroundings of the large manipulator during the movement of the articulated boom or the operation of the large manipulator is arranged on the articulated boom. A three-dimensional model of the surroundings of the large manipulator is continuously derived from the information regarding the surroundings of the at least one surroundings detection sensor. The invention also relates to a method for continuously deriving a three-dimensional model of the surroundings of a corresponding large manipulator.

Description

[0001] SHWG1367

[0002] October 13, 2025

[0003] BD / AY

[0004] Large manipulator and method for continuously deriving a three-dimensional model of the environment of a large manipulator

[0005] The invention relates to a large manipulator, in particular a truck-mounted concrete pump, with a mast base rotatable about a vertical axis by means of a rotary drive and arranged on a frame, an articulated mast comprising two or more mast segments, wherein the mast segments are pivotally connected to the respective adjacent mast base or mast segment by means of a swivel drive via articulated joints, and a control device designed for controlling the rotary drive and the swivel drives of the large manipulator. The invention also relates to a method for continuously deriving a three-dimensional environmental model of the environment of a corresponding large manipulator.

[0006] Large manipulators of this type are known, for example, as truck-mounted concrete pumps for conveying concrete to a delivery point on construction sites, but they can also be designed, for example, as aerial work platforms, turntable ladders, mobile cranes or any other form of lifting or working equipment with a tool at the top of the articulated mast with articulated and / or extendable mast segments connected to each other.

[0007] When controlling such large manipulators, for example during manual operation or automatic folding and unfolding processes, as presented in EP3559374A1, the problem repeatedly arises that obstacles or objects in the vicinity of the manipulator must be taken into account. These obstacles can be read from a building information model, if one exists. The problem here is that this data is not up-to-date or sufficiently complete and does not take moving objects, such as vehicles, into account. The problem to be solved, therefore, is to capture the environment of the large manipulator in such a way that the manipulator, or rather its articulated mast, can be controlled automatically or manually without colliding with obstacles in the vicinity.

[0008] The invention solves this problem, starting from a large manipulator of the type mentioned above, by arranging at least one environmental detection sensor connected to the control unit on the articulated mast, which is designed for the continuous acquisition of environmental information of the large manipulator, wherein the control unit is further designed to continuously derive a three-dimensional environmental model of the large manipulator from the environmental information acquired by the at least one environmental detection sensor during the movement of the articulated mast and / or the operation of the large manipulator, or to generate a three-dimensional environmental model and continuously supplement or update it.By positioning a sensor on the articulated mast to continuously monitor the surroundings of the large manipulator as the mast moves—meaning the sensor is constantly positioned at different locations in space during its monitoring—a highly accurate and detailed three-dimensional environmental model can be continuously derived and created from this environmental information. This allows the articulated mast to be controlled safely, either automatically or manually, taking the three-dimensional model into account, thus preventing collisions with obstacles in the environment. The monitoring during movement brings different areas of the surroundings into the field of view of the at least one environmental monitoring sensor, and the collected environmental information can then be integrated into the three-dimensional environmental model, resulting in a more complete and comprehensive model of the environment.

[0009] In this context, the term "surroundings" refers specifically to the immediate vicinity or area around the installation site of the large manipulator. The term "surroundings" or similar could also be used. Specifically, this refers to the area around the large manipulator that remains accessible with a fully extended articulated mast, which on modern large manipulators can reach 60 meters or more, including a certain safety distance that must be maintained, for example, from high-voltage power lines. This also relates to the reachable height of the large manipulator's articulated mast. Extending or moving the articulated mast typically requires first stabilizing the large manipulator with its outriggers.This means that the detection of the environment of the large manipulator before or during the support process is not the subject of the invention described here.

[0010] The term "capture" refers to the fact that the environmental sensing sensor should, for example, be capable of creating a virtual, spatial representation of the environment from the data generated by the sensor through appropriate further processing. Therefore, instead of the term "three-dimensional environmental model," the term "virtual, spatial representation of the environment" or something similar could also be used.

[0011] The term "continuous derivation" means that a constantly updated three-dimensional environmental model is continuously created from the environmental information continuously acquired by the at least one environmental detection sensor. In other words, the continuously acquired environmental information is constantly aggregated to provide the most up-to-date representation of the environment possible.

[0012] Advantageous embodiments and further developments of the invention result from the dependent claims.

[0013] In its initial configuration, the control unit is designed to continuously supplement and / or update the three-dimensional environment model during the movement of the articulated mast or during the operation of the large manipulator. Because the three-dimensional environment model is continuously supplemented and / or updated based on environmental information provided by at least one environmental detection sensor, it is not static but always adapted to the current situation, thus very effectively preventing collisions with obstacles. Conversely, obstacles that are no longer detected can be removed from the three-dimensional environment model during the update, potentially increasing the articulated mast's operating range.

[0014] Advantageously, at least one environmental sensing sensor detects points in space as environmental information. The detected points in space represent the spatial coordinates of objects that are reflected, for example, by beams emitted by the environmental sensing sensor.

[0015] In a preferred embodiment, the at least one environmental detection sensor, which detects points in space, is a radar or LiDAR sensor. Radar or LiDAR sensors are particularly well suited for detecting points in space.

[0016] Advantageously, at least one environmental sensing sensor can also be configured as an imaging sensor, for example, a camera that creates a digital image of the environment as environmental information. The camera can, for instance, be a stereo camera to take three-dimensional images. However, this is not strictly necessary, as a three-dimensional environmental model can also be generated, particularly through the images captured sequentially during the movement of the articulated mast.

[0017] It is particularly advantageous that the control unit is designed to determine the trajectory of the at least one environmental sensing sensor. The trajectory describes the path the environmental sensing sensor travels in space over time and establishes a relationship between time, position, and orientation of the sensor. This information is helpful, for example, in continuously deriving the most precise possible three-dimensional environmental model from the environmental information acquired by the environmental sensing sensor.

[0018] In one embodiment, the control device is configured to create a point cloud of the large manipulator's surroundings based on the determined trajectory of the at least one environmental sensing sensor and the points detected in space by the at least one environmental sensing sensor. By combining the individual detected points into a point cloud, it is particularly easy to identify certain structures in the large manipulator's environment.

[0019] Preferably, the control device is configured to eliminate from the point cloud of the large manipulator's environment those points that are caused by the large manipulator itself. During movement, particularly during the unfolding process of the articulated mast, the environmental detection sensors regularly detect elements of the large manipulator, especially the articulated mast, which interfere with the generation of the three-dimensional environment model because these points cannot be assigned to the large manipulator's environment.

[0020] Advantageously, the control unit is designed to eliminate points in the point cloud surrounding the large manipulator that are caused by the large manipulator, using a virtual model of the large manipulator. A virtual model of the large manipulator is particularly well-suited for eliminating points in the point cloud that are caused by the large manipulator itself.

[0021] The control unit is advantageously designed to evaluate the point cloud of the large manipulator's surroundings for the creation of the three-dimensional environment model. The points in the point cloud, that is, the raw data from the environmental sensors, initially reveal nothing about objects in the large manipulator's vicinity. Only through evaluation does the point cloud become usable, for example, for collision avoidance.

[0022] The control unit is preferably configured to identify objects when evaluating the point cloud of the large manipulator's environment. This means that, for example, a collection of points within the point cloud can be grouped together to form a physically existing object, which can then be taken into account when controlling the articulated mast to prevent collisions. Preferably, the control unit is configured to identify, in particular, horizontally or vertically oriented, linear structures in the three-dimensional environment model during evaluation. This allows, for example, pipes, building edges, the suspension cable of a crane, and similar objects to be recognized and taken into account when controlling the articulated mast.

[0023] In particular, vertically oriented and / or linear structures and / or sagging structures identified during the evaluation of the three-dimensional environment model can be identified as power lines. While an object identified as a building, for example, can be easily accommodated with a relatively small safety distance during collision avoidance, power lines must be treated separately due to the risk of arcing, which can occur even at greater distances. This means that a significantly larger safety distance to power lines must be maintained, or the operation of the large manipulator in the vicinity of power lines must be completely prohibited.

[0024] In one embodiment, the three-dimensional environment model is continuously updated during the movement of the articulated mast based on the trajectory and environmental information of the at least one environmental sensing sensor. This measure effectively captures the environment from different perspectives continuously for the generation of the three-dimensional environment model. This increases the accuracy and completeness of the model, for example, by reducing shadowing. Furthermore, it allows changes in the environment to be taken into account when updating the three-dimensional environment model. Advantageously, the environmental information acquired by the at least one environmental sensing sensor is used to determine its trajectory.This means that the position or change in position of the environmental sensor in space is determined from the environmental information captured by the environmental sensor from different positions or perspectives by evaluating the continuously captured environmental information, which in turn improves the accuracy of the three-dimensional environmental model.

[0025] In a preferred embodiment, for example, mast sensors are arranged on the articulated mast to determine its position, and the control unit is configured to use the position of the articulated mast determined by the mast sensors to determine the trajectory of the at least one environmental sensing sensor. The mast sensors are, for example, rotary angle sensors arranged on the mast base and / or on the articulated joints, and / or tilt sensors or inertial measurement units (IMUs) or similar sensors arranged on the mast segments, which are suitable for determining the position of the articulated mast, i.e., the position of the individual mast segments of the articulated mast in space.Together with the known mounting position of the environmental detection sensor(s) on the articulated mast, the trajectory of at least one environmental detection sensor can be easily recorded, thus improving the precision of the three-dimensional environmental model.

[0026] The accuracy of the three-dimensional environment model can be further improved by using a satellite navigation sensor mounted on the articulated mast to acquire position data. This data is then used by the control unit to determine the trajectory of the at least one environmental sensing sensor. An inertial measurement unit (IMU) designed to detect accelerations and / or rotation rates, preferably located in close proximity to an environmental sensing sensor, can further enhance the accuracy of trajectory acquisition and, consequently, the accuracy of the three-dimensional environment model.

[0027] Advantageously, the environmental sensing sensor, which detects at least one point in space, has a 360-degree horizontal viewing angle and a vertical viewing angle of 0 to 90 degrees. Combined with the movement in space that the environmental sensing sensor performs in conjunction with the movement of the articulated mast, the environment can be very well captured without necessarily requiring one or more sensors whose field of view covers the entire environment at all times.

[0028] In one embodiment of the invention, at least two environmental detection sensors, each with a 360-degree horizontal field of view and a vertical field of view of 0 to 90 degrees, are arranged on the articulated mast. One environmental detection sensor is configured to detect the environment along the unfolding plane, and the other environmental detection sensor is configured to detect the environment orthogonally to the unfolding plane of the articulated mast. This arrangement allows the environment of the large manipulator to be detected very effectively and thus used for generating and continuously deriving or updating the three-dimensional environmental model.

[0029] It has also proven advantageous if at least one point-detecting environmental sensing sensor has a hemispherical field of view to effectively and precisely capture the environment of the large manipulator. If at least two point-detecting environmental sensing sensors with hemispherical fields of view are arranged laterally opposite each other on a first mast segment of the articulated mast, the environment of the large manipulator can advantageously be captured quickly and accurately, requiring little or no movement of the articulated mast to capture the environment of the large manipulator from at least one perspective.

[0030] Advantageously, two additional point-detecting environmental sensors with hemispherical field of view are arranged laterally opposite each other on a second mast segment of the articulated mast. This provides more environmental information, particularly from a different perspective, for the continuous derivation of the three-dimensional environmental model. Compared to a single pair of sensors, this also has the advantage that the immediate surroundings of the entire articulated mast can be continuously monitored, as obstructions, such as building edges, do not cause parts of the boom's immediate vicinity to be outside the sensor pair's field of view. This continuous monitoring also offers the advantage of more reliable detection of dynamically occurring obstacles.

[0031] It is particularly advantageous if the control system is designed to continuously derive the three-dimensional environment model of the articulated boom during extension, operation, and / or retraction. Both the extension and movement of the articulated boom during operation, as well as the retraction, are essential processes for operating, for example, a truck-mounted concrete pump. These processes can be used to capture the environment of the large manipulator in order to continuously derive a three-dimensional environment model or to update an existing one. For example, the three-dimensional environment model derived during the extension of the articulated boom can be used during operation and later during retraction to prevent collisions between the articulated boom and objects in the environment.

[0032] In a preferred embodiment, the control device is configured to determine a control sequence for the automatic unfolding and / or automatic folding of the folding mast based on the three-dimensional environment model. The three-dimensional environment model available to the control device can be particularly useful for preventing collisions between the folding mast and obstacles in the environment during automatic folding and unfolding.

[0033] It is particularly advantageous if the movement sequence for the automatic unfolding and / or folding of the folding mast is updated based on the three-dimensional environment model of the large manipulator, which is continuously derived during the unfolding and / or folding process. During the movement of the folding mast, which is accompanied by the continuous updating or enhancement of the three-dimensional environment model, the movement sequence can be continuously adapted to the potentially changed or better understood environment.

[0034] Advantageously, the control device can also limit the movement of the articulated mast during manually controlled operation, based on the generated three-dimensional environment model of the large manipulator, so that the articulated mast does not collide with objects in the environment.

[0035] Furthermore, the invention relates to a method for continuously deriving a three-dimensional environmental model of the environment of a large manipulator, wherein the method comprises the following steps: - unfolding the folding mast

[0036] - Continuous acquisition of environmental information captured by at least one environmental sensing sensor during the unfolding of the articulated mast

[0037] - Capturing the trajectory of at least one environmental sensing sensor during the unfolding of the articulated mast,

[0038] - Continuous derivation of a three-dimensional environmental model of the large manipulator based on the environmental information continuously acquired by the at least one environmental detection sensor and the trajectory of the at least one environmental detection sensor.

[0039] Further features, details, and advantages of the invention will become apparent from the following description and the drawings. Exemplary embodiments of the invention are shown purely schematically in the following drawings and are described in more detail below. Corresponding objects or elements are designated with the same reference numerals in all figures. The figures show:

[0040] Figure 1: Left side view of a large manipulator according to the invention

[0041] Figure 2: Right side view of a large manipulator according to the invention

[0042] Figure 3: Top view of the large manipulator according to the invention with folded folding mast

[0043] Figure 4: Top view of the large manipulator according to the invention with the folding mast extended. Figure 5: Schematic representation of the

[0044] Unfolding process of a large manipulator according to the invention

[0045] Figure 6: Large manipulator according to the invention at the

[0046] Concreting process

[0047] Figure 7a, b Top view, sectional view of surroundings

[0048] Detection sensors in the first variant

[0049] Figure 8a, b Top view, sectional view of surroundings

[0050] Detection sensors in the second variant

[0051] Figure 9 Illustration of joint angle correction

[0052] Figure 10 schematic representation of the control device according to the invention

[0053] Figure 11 Representation of a point cloud for the generation of a three-dimensional environment model

[0054] Figure 12 Top view of environmental detection sensors in the third variant

[0055] Figure 1 schematically shows a large manipulator according to the invention in the form of a truck-mounted concrete pump, which is designated in its entirety by reference numeral 1. Within the scope of this disclosure, the term "large manipulator 1" refers to a working device, for example, with an arm, a boom, a lifting mechanism, a lifting frame, or a mast. The truck-mounted concrete pump 1 comprises, for example, a chassis 12 on which the articulated mast 5 is mounted and a driver's cab 2. The extendable articulated mast 5 is arranged on a mast support 3 that is rotatable about a vertical axis. In the illustrations of Figures 1, 2, and 3, the articulated mast 5 is folded and placed on the mast support 15.The articulated mast 5 is mounted on a frame 4, which can also be referred to as the substructure, via the mast base 3. In the case of a truck-mounted concrete pump 1, this substructure includes, in particular, a concrete pump 28, which conveys fresh concrete, filled into the feed hopper 13 by a truck mixer, along a conveying line 29 to the mast tip 9 or to the end hose 14 (Fig. 2). The rotation of the mast base 3 about the vertical axis is effected by a rotary drive 2, which consists, for example, of a gearbox and a hydraulic motor, preferably controlled by a proportional control valve. The articulated mast 5 is articulated to the mast base 3 and has a plurality of mast segments 6a, 6b, 6c, 6d, 6e, in the exemplary embodiment.The mast segments 6a, 6b, 6c, 6d, 6e, which are arranged at parallel, horizontally aligned hinge joints 7a, 7b, 7c, 7d, 7e, are each pivotable relative to an adjacent mast segment 6a, 6b, 6c, 6d, 6e or the mast support 3 by means of a rotary actuator 8a, b, c, d, e. The first mast segment 6a is pivotally mounted on the mast support 3 about a horizontal axis at the hinge joint 7a. The pivoting movement of the first mast segment 6a is effected by the first rotary actuator 8a. The rotary actuators 8b, c, d, e each have one or more hydraulic cylinders or other suitable drives, for example, a worm gear or a hydraulic rotary actuator, which are controlled, for example, by proportionally operating control valves. These, as well as the control valve for the hydraulic motor of the rotary drive 2, are in turn controlled by a control unit 50 (Fig. 10) for the mast movement.The slewing drives 8a, b, c, d, e can be controlled by an operator, for example, via a remote control 51, which is connected to the control unit 50 by a cable or radio link. The control of the articulated mast 5 can be simplified for the operator, for example, by the control unit 50, which converts the operator's commands for the movement of the mast tip 9 (e.g., up / down; right / left) into control commands for the individual slewing drives 8a, b, c, d, e within the framework of a so-called Cartesian control system. This can also be described as semi-automatic operation. Furthermore, the control unit 50 can execute automatic movement sequences activated via the remote control 51, for example, for the automatic extension or retraction of the articulated mast 5.In the exemplary embodiment, the frame 4 of the large manipulator 1 has a support structure 11 consisting of four extendable supports for stabilizing it on the ground. The supports of the support structure 11 can be extended or folded down via support arms to increase the contact area and prevent the truck-mounted concrete pump 1 from tipping over when the articulated boom 5 is extended.

[0056] The large manipulator 1 preferably has mast sensors 44, for example in the form of angle sensors for the articulated joints 7a,b,c,d,e or displacement sensors for detecting the piston positions of the individual hydraulic cylinders, the rotation angle of the mast support 3, and the swivel angles of the articulated joints 7a,b,c,d,e, wherein the control unit 50 preferably controls the speed of the mast movement depending on the slewing angle and the instantaneous swivel angles of the articulated joints 7a,b,c,d,e by appropriately controlling the valves of the hydraulic cylinders and the hydraulic motor of the rotary drive 2. Additionally or alternatively, geodetic tilt sensors or inertial measurement units (IMUs) 42 can be arranged on one or more of the mast segments 6a,b,c,d,e for detecting the pose of the articulated mast 5, i.e., the position of the mast segments 6a,b,c,d,e relative to each other.

[0057] In the illustrations of the large manipulator 1, designed as a truck-mounted concrete pump 1, at least one environmental sensing sensor 40a,b,c,d,e,f,g,h,i,j; 41a,b, connected to the control unit 50, is arranged on the articulated mast 5. This sensor is designed for the continuous acquisition of environmental information for the large manipulator 1 during the movement of the articulated mast 5 or during operation of the large manipulator 1. The control unit 50 is designed to continuously derive a three-dimensional environmental model of the large manipulator 1 from the continuously acquired environmental information of the at least one environmental sensing sensor 40a,b,c,d,e,f,g,h,i,j; 41a,b.For movement, the articulated mast 5 does not need to be moved in a specific, predefined sequence of movements. Instead, the control unit 50 can continuously derive the three-dimensional environment model while the articulated mast 5 is being extended or retracted and / or while the articulated mast 5 is being moved during operation. In particular, because the environmental information is acquired during the movement of the articulated mast 5, the environment of the large manipulator 1 is continuously captured from different perspectives, resulting in advantages for creating the three-dimensional environment model, as will become clear from the following explanations of the invention.The at least one environmental sensing sensor 40a, b, c, d, e, f, g, h, i, j; 41 a, b also acquires environmental information as soon as the large manipulator (1) or the truck-mounted concrete pump 1 is put into operation, for example, while the articulated mast 5 is still resting on the mast support 15. During this time, the at least one environmental sensing sensor 40a, b, c, d, e, f, g, h, i, j; 41 a, b already acquires an initial image of the environment, which is further completed or aggregated during the movement of the articulated mast 5 together with the at least one environmental sensing sensor 4040a, b, c, d, e, f, g, h, i, j; 41 a, b.

[0058] In the exemplary illustrations in Figures 1, 2, 3, 4 and 5, four environmental detection sensors 40a,b,c,d designed as LiDaR or radar sensors are arranged on the articulated mast 5, each having a hemispherical field of view, as is shown, for example, in Figure 7a based on a top view of a mast segment 6b with two LiDaR sensors 40a, b.

[0059] LiDaR stands for "Light Detection and Ranging" and is a well-known method for environmental sensing. It uses light in the form of a pulsed laser to detect and categorize objects. LiDaR sensors generate precise, three-dimensional information about the shape and surface properties of surrounding objects by emitting laser beams in an eye-safe range to continuously derive a three-dimensional representation of the detected environment. A LiDaR sensor, which scans the environment and maps it in a virtual 3D format, primarily consists of a laser source that emits laser pulses, a scanner that deflects the light, and a detector that receives the reflected light. Other components include, for example, optical lenses. A LiDaR sensor typically operates on a principle also known as the time-of-flight principle.It emits pulsed light waves into the environment, which are reflected by surrounding objects and return to the sensor's detector. The time each pulse takes to return is used to calculate the distance traveled. The distance between the sensor and the object can be determined from the pulse's return time. The environment is scanned point by point, i.e., points in space are detected, by continuously changing the laser beam's orientation. This is achieved through deflection mechanisms within the sensor, such as MEMS (micro-electro-mechanical system) mirrors, and through the continuous movement of the environmental detection sensor 40a,b,c,d with the articulated mast 5. From these individual points in space detected by the LiDAR sensors, the control unit 50, shown in Figure 10, first generates a point cloud by combining the individually detected points.Further processing and analysis of this point cloud ultimately creates a three-dimensional environment model, which can be used, for example, for collision avoidance. To convert the point cloud into a three-dimensional environment model, individual points are transformed into voxels, which, in computer graphics, represent a grid point in a three-dimensional grid. Voxels are thus practically equivalent to a pixel in a 2D image. The environment of the concrete pump 1 is divided into voxels, and based on the point clouds, a decision is made as to whether a voxel is free (i.e., not considered an obstacle H1, H2, H3, H4) or whether it represents an object constituting an obstacle H1, H2, H3, H4. From these classified voxels, the position of obstacles H1, H2, H3, H4 in the environment is then deduced.

[0060] Alternatively or additionally to LiDAR sensors 40a, b, c, d, e, f, g, h, i, j, radar (radio detection and ranging) sensors can also be used as environmental sensing sensors, which scan the environment using radio signals. Their measurement principle is similar to that of optical LiDAR sensors in that a point cloud for creating a three-dimensional environmental model can also be generated from the measurement signals of radar sensors. The advantage of radar sensors is that good results are achieved even in adverse weather conditions such as rain, fog, and snow.

[0061] Figure 7b shows a corresponding cross-sectional view through the mast segment 6b at the level of the LiDAR sensors 40a, b. Such sensors are referred to as dome sensors, for example, due to their hemispherical field of view. The hemispherical field of view of a dome sensor 40a, b results, for example, from a sensor viewing angle a of 90 degrees in conjunction with the rotation of the sensor beam around the central axis m of the sensor, as shown in Figure 7b. The environmental detection sensors 40a, b, c, d are shown here, by way of example, arranged laterally opposite each other on the second mast segment 6b and the fourth mast segment 6d of the articulated mast 5.To prevent the concrete delivery line 29, which runs parallel to the mast segments 6a, b, c, d, e, from obstructing the field of view of the environmental detection sensors 40a, b, c, d, the environmental detection sensors 40a, b, located on the side of the delivery line 29, are mounted on the delivery line supports 30, ensuring the sensors have an unobstructed view of the surroundings. By arranging two LiDAR sensors 40a, b, c, d, each with a hemispherical field of view, opposite each other on a mast segment 6b, d, it is possible to detect an almost spherical area around the position of the sensors 40a, b, c, d on the articulated mast 5. This has the advantage of continuously monitoring a large portion of the surroundings, which is beneficial, for example, in dynamic environments and thus enables rapid and complete environmental coverage when the articulated mast 5 is extended.A single LiDAR sensor can, for example, have 32 scan planes with a vertical angular spacing of 2.8°. Depending on the defined sampling frequency, the horizontal angular resolution can be, for example, 0.1°, 0.2°, or 0.4°.

[0062] Alternatively or additionally, for example, two LiDAR sensors 40e,f, each with a 360-degree field of view (i.e., a circular field of view in the horizontal direction and, for example, a field of view a in the vertical direction of 0 to 90 degrees), could be arranged at a suitable position on the articulated mast 5. One environmental detection sensor 40e is configured to detect the environment along the unfolding plane, and one environmental detection sensor 40f is configured to detect the environment in a direction orthogonal to the unfolding plane of the articulated mast 5, as illustrated, for example, in Figures 8a and 8b. The vertical field of view a, which is approximately 60 degrees for both LiDAR sensors 40e,f in Figures 8a and 8b, does not necessarily have to be symmetrically aligned with the sensor housing. Depending on the sensor type and manufacturer, a field of view a larger than 90 degrees, theoretically up to 180 degrees, is also possible.At a viewing angle α of 0 degrees, the sensor scans only two-dimensionally. However, the sensor's movement in space, in conjunction with the articulated mast 1, results in a three-dimensional scan of the surroundings. The LiDAR sensors 40e,f are typically cylindrical, with the scanning process taking place across the cylinder's outer surface. As an alternative to mounting these sensors on one or more of the mast segments 6a,b,c,d,e, they could also be arranged in the area of ​​the articulated joints 7a,b,c,d,e, for example, on the deflection levers of the articulated mast 5's kinematic linkage. The optimal arrangement of the sensors 40a,b,c,d,e,fg,h,i,j can vary considerably depending on the different folding mechanisms of the articulated mast 5, such as Z-folding, roll folding, roll-Z folding, etc., and other design differences, and must be adapted to the specific construction.An advantage for the arrangement would be, for example, that at least one of the sensors 40a, b, c, d, e, f, g, h, i, j already has a certain view in the direction of the planned unfolding direction and / or laterally to the truck-mounted concrete pump 1 at the beginning of the unfolding process of the articulated mast 5, in order to contribute to the construction of the three-dimensional environment model from the beginning and to complete it in the course of the further movements of the articulated mast 5.

[0063] Figure 5 schematically depicts the large manipulator 1 according to the invention in a construction site environment, where the articulated mast 5 is unfolded from a folded position 5a to an extended position 5b. This figure illustrates, by way of example, the trajectory B resulting from the unfolding process of the articulated mast 5, i.e., the temporal progression of the position and orientation of the environmental sensing sensor 40a. In Figure 5, with the articulated mast 5 folded, the environmental sensing sensor 40a is still located on the rear side of the large manipulator 1 and begins sensing the environment while the articulated mast 5 is still resting on the mast support 15. For the unfolding process, the entire articulated mast 5, i.e., the mast segments 6a, b, c, d, e folded relative to each other, is first brought into an approximately vertical position as a mast package via the first mast joint 7a.The second mast joint 7b is then actuated until the ambient detection sensor 40a, for example, reaches its highest position. After rotating the mast support 3 by approximately 180 degrees, it is possible to unfold the articulated mast 5 further forward over the driver's cab 10 and bring it into its working position. As can be clearly seen in Figure 5 from the representation of trajectory B, the ambient detection sensor 40a alone already detects a large part of the area surrounding the large manipulator 1. The trajectory of the ambient detection sensor 40c on the mast segment 6d, which is not shown in Figure 5, typically includes even more changes in direction than the trajectory B of the ambient detection sensor 40a, but is omitted from Figure 5 for the sake of clarity.

[0064] Figure 5 also shows static obstacles H1, H2 and a dynamic obstacle H4 detected according to the invention, which were detected during the unfolding process of the folding mast 5 and entered into the three-dimensional environment model. Only the solid edges of the obstacles or objects H1, H2 are present in the three-dimensional environment model. The dashed edges of obstacle H2 are shadowed by the obstacle itself and cannot be detected by the sensors 40a, b, c, d.

[0065] To generate or continuously derive a three-dimensional environmental model from the points recorded by the environmental sensing sensors 40a,b,c,d,e,f,g,h,i,j, the trajectories B of the environmental sensing sensors 40a,b,c,d,e,f are required. This is because, in order to assign a position in the three-dimensional environmental model to the points recorded by the LiDaR sensors, the current position and orientation of the sensors 40a,b,c,d,e,f,g,h,i,j in space or the environment must first be known as accurately as possible. A simple way to determine the trajectories B of the sensors 40a,b,c,d,e,f,g,h,i,j is to use the mast sensors 44 to detect the pose of the articulated mast 5. Because the mounting position of the sensor(s) 40a,b,c,d,e,f,g,h,i,j on the articulated mast 5 is known, the position of the sensors 40a,b,c,d,e,f,g,h,i,j in space can be deduced.Due to inaccuracies in the mast sensors of the articulated mast 5 during operation, the deflection of the mast segments 6a,b,c,d,e, tolerances in the steel structure, and other factors, the trajectory B of the environmental detection sensors 40a,b,c,d,e,f,g,h,i,j, using only the mast sensors 44, may not be sufficiently accurate for creating a sufficiently precise three-dimensional environmental model. A highly accurate estimation of the trajectory B of all sensors 40a,b,c,d,e,f,g,h,i,j is crucial for mapping. An erroneous trajectory B would result in the sensor data, i.e., the points of the point cloud, being entered into the three-dimensional environmental model at an incorrect position, and consequently, this data could, for example, be incorrectly interpreted as obstacles H1, H2.

[0066] The trajectories B of sensors 40a, b, c, d, e, f, g, h, i, j are therefore estimated primarily by sensor fusion of data from the tilt sensors or inertial measurement units 42, that is, the accelerations and rotation rates recorded by these sensors 42, together with LiDaR odometry. For LiDaR odometry, point cloud odometry algorithms are used, for example, which make it possible to match temporally successive scans of the LiDaR sensors 40a, b, c, d, e, f, g, h, i, j and to determine the motion between them based on this. It is, of course, advantageous to use LiDaR sensors with the highest possible resolution. Due to the high cost of high-resolution LiDaR sensors, it may be more advantageous or economical to use LiDaR sensors with a lower resolution, whereby the odometry method used must be adapted accordingly in order to determine the trajectories B as accurately as possible.

[0067] Additionally, position information from one or more satellite navigation sensors 43, arranged at suitable positions on the articulated mast 5 or in close proximity to the LiDaR sensors 40a,b,c,d,e,f,g,h,i,j, can be used to further improve the estimation of the trajectories B of the LiDaR sensors 40a,b,c,d,e,f,g,h,i,j. Acceleration and / or rotation rate inertial measurement units (IMUs) 42, for example, can also be arranged in close proximity to an environment sensing sensor to detect its position changes in space by recording the acceleration and / or rotation rate of the environment sensing sensor, thus achieving improved trajectory determination.

[0068] The data from the LiDaR sensors 40a, b, c, d, e, f are combined in a factor graph using suitable libraries for LiDaR odometry. The data from the inertial measurement units (IMUs) 42 primarily serve to estimate high-frequency movements, such as vibrations of the articulated mast 5, while the LiDaR odometry is essential for estimating the long-term movement of the articulated mast 5 throughout the entire mapping process. Suitable solutions for odometry are available to those skilled in the art, known, for example, as Iterative Closest Point (ICP) algorithms. To achieve sufficient accuracy, the odometry algorithms can be specifically optimized for the sensor shape used, such as dome sensors 40a, b, c, d, h, i or cylindrical sensors 40e, f, i.

[0069] In addition to or as an alternative to the odometry based on the LiDaR sensors 40a,b,c,d,e,f,g,h,i,j, at least one or more imaging environmental detection sensors 41, for example in the form of a simple or stereoscopic camera 41, can also be arranged on the articulated mast 5 at a suitable position.The image recordings of the at least one camera 41 are taken from different perspectives as the articulated mast 5 moves, as already described in connection with the LiDaR sensors 40a,b,c,d,e,f,g,h,i,j and can be used on the one hand for optical verification / supplementation of the three-dimensional environment model, and on the other hand the camera images can also be used to supplement / improve the odometry, in which the position or movement of the camera 41 in space is deduced from temporally successive images, which in conjunction with other data helps to estimate or determine the trajectories B of the LiDaR sensors 40a,b,c,d,e,f,g,h,i,j.

[0070] The three-dimensional environment model can be subdivided by the control unit 50, for example, into static objects H1, H2, H3 and dynamic objects H4. Dynamic objects H4, such as people, vehicles, or other construction equipment, or, as shown in Figure 5, a transport vehicle, must not be permanently entered into the three-dimensional environment model, as they would distort the environment model and could be interpreted as a permanent obstacle or object H1, H2. To avoid this, a so-called "free space mapping" approach, based on the ray casting principle, can be used. In this approach, all voxels along a LiDaR beam between the LiDaR sensor and the detected LiDaR point (echo) are marked as "free." This ensures that dynamic objects are removed from the environment model as soon as at least one of the LiDaR sensors 40a, b, c, d, e, f, g, h, i, j no longer detects them.It should be noted that a LiDAR sensor that initially detects an object / obstacle may, due to the movement of the articulated mast 5, no longer detect this object / obstacle at all later on, and that this object / obstacle may then be within the field of view of another LiDAR sensor. Dynamic obstacles H4 are also detected by the at least one environment detection sensor that continuously scans the surroundings, while the articulated mast 5 is stationary but the large manipulator 1 is operating and is taken into account in the three-dimensional environment model. For example, a vehicle parked near the mast tip 9 during an interruption of the mast's movement will be detected and considered an obstacle as soon as the articulated mast 5 resumes its movements.

[0071] The control unit 50 can, in particular, evaluate the three-dimensional environment model not only to distinguish between static objects H1, H2 and dynamic objects H4, but also to identify objects of specific categories. This is especially advantageous because it allows, for example, a distinction to be made between structures classified as simple obstacles H1, H2, to which the articulated mast 5 may move relatively close, and, for example, power lines H3, for which a particularly large safety distance must be maintained, as illustrated in Figure 6. The term "power lines H3" here refers specifically to overhead high-voltage power lines, which pose a particular danger to truck-mounted concrete pumps 1 and for which a particularly large safety distance must therefore be maintained.

[0072] At least the presence and, if applicable, the distance, but not the exact position, of active, alternating current power lines could be detected, for example, using suitable field strength sensors, in addition to the environmental detection sensors presented here. Such field strength sensors can indicate whether a power line detected in the three-dimensional environmental model is actually live or perhaps switched off. However, it should also be noted that it can be catastrophic if a power line is put into operation while the articulated mast 5 is near this power line. Furthermore, field strength sensors generally do not detect the presence of direct current lines.However, a high voltage detected by a field strength sensor in the vicinity of the large manipulator 1 could also be used to pay more attention to the detection of high-voltage lines H3 when sensing the environment of the large manipulator 1 and, for example, to activate algorithms that improve the detection of power lines H3.

[0073] Especially when using simple and inexpensive LiDAR sensors 40a, b, c, d, e, f, g, h, i, j with a relatively low resolution, an existing power line H3 in the environment is often not detected, or only incompletely detected, with a single sensor scan. Continuously acquiring data with the environmental detection sensors 40a, b, c, d, e, f as they move through space, and superimposing the scans over time, makes it possible to detect even very narrow or thin objects, such as power lines H3.

[0074] Based on the data acquired by the LiDAR sensors 40a,b,c,d,e,f,g,h,i,j, which are used to detect power lines H3, these can also be automatically identified within the point cloud. This process utilizes, for example, the so-called "catenary" property of the power lines H3, which describes their geometric sag (catenary curve). The process can be carried out in several steps, as shown below. The first step is to delineate the power line H3 from other elements, such as building edges. Here, the linearity property of the power line H3 can be used. Points within the point cloud that exhibit a linear profile and are horizontally oriented are examined. This allows for a clear differentiation of transitions between power lines H3 and other elements.In a subsequent step, areas in the point cloud are divided into so-called clusters, which are then examined in more detail. By checking the "catenary" similarity of the clusters, it is now possible to distinguish between "normal" obstacles or objects H1, H2, H4 and power lines H3.

[0075] When creating or continuously deriving the three-dimensional environment model by the control unit 50, it is also advantageous to delineate and separately consider the large manipulator 1, in particular its articulated mast 5, its undercarriage 4, especially consisting of the operator's cab 10, the chassis 12, the feed hopper 13, and the outriggers 11 extended during operation. For this purpose, a virtual model of the large manipulator 1, which can also be referred to as a digital twin, can be stored on the control unit 50, for example, in URDF format (Unified Robotics Description Format). Together with the known pose of the articulated mast 5 and the extended position of the outriggers 11, structural elements of the large manipulator 1 can be recognized in the point clouds of the LiDAR sensors and classified or eliminated accordingly.For example, an adjacent mast segment 6a,b,c,d,e moving past or stationary next to one of the LiDaR sensors 40a,b,c,d,e,f,g,h,i,j can be classified as an element of the large manipulator 1 and not as an obstacle H1, H2 to be considered. The URDF model also includes, for example, the position, arrangement, and orientation of the LiDaR sensors 40a,b,c,d,e,f,g,h,i,j and, if applicable, at least one imaging sensor 41 on the large manipulator 1 or its articulated mast 5. This is necessary, on the one hand, for the detection of elements of the large manipulator 1, as described above. On the other hand, the position of the sensors with the articulated mast 5 folded can be used as a starting point for further acquisition of the trajectories B of these sensors 40a,b,c,d,e,f,g,h,i,j. 41 are used during the movement of the folding mast 5.

[0076] The structure and function of the control unit 50 for the continuous updating according to the invention, i.e., the generation of a three-dimensional environment model of a large manipulator 1, are explained in detail below with reference to Figure 10. In this exemplary representation, the control unit 50 shown in Figure 10 consists of different modules 50a, b, c, d, e, f, g, h, which can run together or distributed across one or more processors. It is also possible for the control unit 50 to offload computationally intensive processes to an external computing unit, for example, in a cloud, perhaps via a real-time wireless connection. The description given here, based on modules 50a, b, c, d, e, f, g, h, serves in particular to illustrate one embodiment of the invention.Other divisions, combinations, or modifications of the modules of the control unit 50 are conceivable without deviating from the basic idea of ​​the invention. The preferred embodiment of the control unit 50 shown by way of example in Figure 10 is based in particular on a specific technology and number of environmental sensors and other sensors. The use of other sensor technologies could, for example, result in a completely different design of the control unit 50. Likewise, individual modules, such as module 50f for the automatic control of the articulated mast 5 or module 50g for collision avoidance during manual mast control, could be omitted. It is also conceivable that the three-dimensional environmental model of the large manipulator created according to the invention could be used for other applications not shown here, which could, for example, be executed by the control unit 50.

[0077] As shown in the exemplary illustration in Figure 10, for example, two LiDAR sensors 40a, b, an imaging sensor in the form of a camera 41, an inertial measurement unit (IMU) 42, a satellite navigation sensor 43, and the mast-mounted sensor system 44 described above are connected to a module 50a for determining the trajectories B of the LiDAR sensors 40a, b. Further / other LiDAR sensors 40c, d, e, f can be connected to the module 50a for trajectory determination if they are arranged on the articulated mast 5 for environmental sensing, as shown, for example, in Figures 1 to 5 and 6.

[0078] In module 50a, for example, the odometry method already explained in detail above is used to determine the trajectories B of the two LiDaR sensors 40a, b. This method utilizes the points provided by the LiDaR sensors 40a, b, a camera 41, one or more inertial measurement units (IMUs) 42, a satellite navigation sensor 43, and additional mast-mounted sensors 44. Determining the trajectories B would also be possible without the application of LiDaR odometry, provided the mast-mounted sensors 44 have sufficient precision. Crucially, module 50a ultimately reproduces the trajectories B of the LiDaR sensors 40a, b with sufficient accuracy to use the data from the LiDaR sensors 40a, b for the creation or continuous derivation of a three-dimensional environmental model.

[0079] Module 50a, used for trajectory determination, transmits the trajectories B from the LiDaR sensors 40a and 40b to module 50b. Module 50b then uses the points in space detected by the LiDaR sensors 40a and 40b and their corresponding trajectories B to generate a three-dimensional point cloud of the environment surrounding the large manipulator 1. An optional feedback connection between module 50b and module 50a improves the estimation and determination of the trajectories B from the LiDaR sensors 40a and 40b. The three-dimensional point cloud in module 50b essentially contains only the raw data from the LiDaR sensors 40a and 40b, but no usable information about the physical environment of the large manipulator 1.

[0080] Module 50e contains a virtual model of the large manipulator 1, which is continuously updated, for example, by the movement of the articulated mast 5 and, if necessary, by its extension or retraction. This virtual model primarily serves to eliminate self-detections, meaning the detection of elements of the large manipulator 1 by the LiDaR sensors 40a and 40b in the point cloud of module 50b. In module 50e, the position or pose of the articulated mast 5 is continuously updated, for example, by the sensor data from the mast sensor 44 and by the LiDaR odometry performed in module 50a. This means that a virtual model of the large manipulator 1 is created based on the angles of the articulated joints 7a, b, c, d, e detected by the mast sensor 44. This is particularly important for two different applications.In both cases, the basis is the additional generation of a sampled point cloud on the 3D model of the large manipulator 1. Using this point cloud, on the one hand, all self-detections of laser beams can be removed, and on the other hand, it is used as a distance measurement to the environment to determine how far the large manipulator 1 is from other elements or obstacles H1, H2, H3, H4 in the three-dimensional environment model.

[0081] The following describes, by way of example, the creation and positioning of the virtual model or digital twin of the large manipulator 1 in the three-dimensional environment model based on the arrangement of at least one LiDaR sensor 40g on the mast segment 6e near the articulated joint 7e, as shown in Figure 9, whereby it is assumed, for example, that the mast sensor system 44 detects the angles of the articulated joints 7a,b,c,d,e using joint angle sensors arranged on the articulated joints 7a,b,c,d,e.

[0082] During the mapping process, the pose or trajectory B of the LiDaR sensor 40g is continuously determined in three-dimensional space. Based on the angles of the articulated joints 7a,b,c,d,e detected by the mast sensors 44, the position of the large manipulator 1 in space is initially determined from this sensor pose back to the chassis 12. Due to various inaccuracies in the mast sensors 44, such as inaccuracies in reading the joint angles, deflections of the mast segments 6a,b,c,d,e, and constant oscillations or vibrations, this back-process from the sensor pose to the chassis 12 is relatively imprecise. This results in an imprecise representation of the articulated mast 5 in the three-dimensional environment model.

[0083] This error can be largely eliminated by the joint angle optimization described below. The aim is to distribute the errors, which already occur at the beginning of the articulated mast 5, evenly across all articulated joints 7a, b, c, d, e. To achieve this, at the beginning of the generation of the three-dimensional environment model, for example, after the large manipulator 1 has been supported and before the articulated mast 5 has been unfolded—that is, while the folded articulated mast 5 is still resting in the mast support 15—the chassis 12 of the large manipulator 1 is fixed in the three-dimensional environment model. This is because, at this point, the position and orientation of the sensor pose relative to the chassis 12 are known almost exactly, as deflections of the mast segments 6a, b, c, d, e are negligible in this state.As soon as the articulated mast 5 is unfolded, or rather, when the articulated mast 5 is unfolded, all angles of the articulated joints 7a, b, c, d, e are estimated, for example, by solving a nonlinear optimization problem based on the LiDaR odometry performed in module 50a for the LiDaR sensor 40g located in the area of ​​the mast joint 7e, such that the pose or trajectory B of the LiDaR sensor 40g corresponds to the position or orientation of the LiDaR sensor 40g in the virtual model of the large manipulator 1. To allow a comparison between the original and the corrected position of the large manipulator 1, both positions of the large manipulator 1 are shown in Figure 9.It is particularly noticeable with chassis 12 that the original position of chassis 12, shown as a dashed line and thus determined solely by angle measurement, is significantly higher in space than the fixed position, i.e., the position corrected using the joint angle optimization described above. The structure of the large manipulator 1, or rather its components, determined in this way, can now be eliminated from the point cloud in the three-dimensional map of module 50b to prevent self-detections.

[0084] For the creation of the three-dimensional environment model, in the following description, which refers further to Figure 10, only the data of the LiDaR sensors 40a, 40b are used in this exemplary representation in addition to the trajectories B of the LiDaR sensors 40a, 40b.

[0085] Module 50b, which initially contains only the raw data for the three-dimensional environment model in the form of point clouds, is followed by module 50c, which processes this raw data. In the processing module 50c, for example, the voxel-based representation of the environment of the large manipulator 1, as described above, is generated from the point cloud. This voxel-based representation allows for the easy detection and abstract description of large obstacles, such as those H1, H2, and H4 shown in Figure 5, for further processing. To minimize the computational effort, for example, during subsequent collision avoidance, the individual voxels should be as large as possible; conversely, the smaller the voxels, the higher the resolution of the three-dimensional environment model.To minimize computational effort, for example during subsequent collision avoidance, virtual bounding boxes can be derived from connected structures such as obstacles H1, H2, and H4 consisting of non-free voxels. These bounding boxes enclose all non-free voxels of the structures, for example, as cuboids to abstract buildings. Furthermore, based on the time course of the evaluation, the detected obstacles H1, H2, H4 can be divided into dynamic obstacles H4 and static obstacles H1, H2. Due to the voxel-based evaluation, dynamic obstacles H4 are simply eliminated from the environment model as soon as they are no longer detected.

[0086] Furthermore, for example, an algorithm running in module 50c can detect power lines in the point cloud of module 50b, as described above, and pass them on, classified accordingly, to the three-dimensional environment model stored in module 50d. In the three-dimensional environment model 50d, power lines classified in this way can be assigned an increased safety distance that the articulated mast 5 must maintain. The results of the evaluation of the point cloud from module 50b in module 50c can, if necessary, be fed back into the generation of the point cloud in module 50b for improvement purposes.

[0087] Module 50d, containing the three-dimensional environment model, can also be connected to a display showing the large manipulator 1 within the previously captured environment. This display allows an operator to identify which areas around the large manipulator 1 are already well mapped, indicating where, for example, the articulated mast 1 can be safely moved automatically. The display can also show the necessary safety distances to objects H1, H2, H4, and especially to detected power lines H4. This helps determine, for example, whether the intended position of the articulated mast 5 for concrete pouring is even achievable, taking these safety distances into account. Based on the three-dimensional environment model stored in module 50d, module 50f calculates an automatic movement sequence for folding and / or unfolding and / or operating the articulated mast 5 automatically.When folding and unfolding the articulated mast 5, information from the three-dimensional environment model of module 50d regarding obstacles H1, H2, H3, and H4 can be easily taken into account, and the articulated mast 5 can be controlled accordingly. During automatic unfolding of the articulated mast, the unfolding process can be controlled by skillfully manipulating the mast 5 so that the LiDAR sensors mounted on the mast 5 capture the environment, particularly in the direction of the planned work / concreting area, as quickly and in as much detail as possible.

[0088] In automated operation, for example, formwork for concrete walls identified in the three-dimensional environment model, or inserted into the three-dimensional environment model via a connection to a site information model (BIM), can be automatically moved from the mast tip 9 of the articulated mast 5. Similarly, when pouring a foundation slab for a building, the articulated mast 5 could, for instance, move automatically in a meandering pattern at a constant height over the concreting area, based on the evaluated three-dimensional environment model, during concrete pouring. This is possible in conjunction with a BIM model (site information model) of the environment, which contains information about the building to be constructed, such as the position of walls, etc.The knuckle mast 5, which is equipped with a concrete print head at the mast tip 9 instead of an end hose 14, can be used for the automatic printing of concrete walls, taking into account the current environmental conditions.

[0089] Furthermore, in this exemplary illustration, the control unit 50 has a module 50g for collision avoidance in manual and / or semi-automatic operation, which is based on the three-dimensional environment model stored in module 50d. For example, in manual operation, the collision avoidance module 50g receives control commands for the articulated mast 5 from an operator, such as from the remote control 51, and checks whether the entered control commands could lead to a collision with an obstacle H1, H2, H4, or to proximity to a power line H3. In the case of obstacles H1, H2, H4, the speed of movement of the articulated mast 5 is reduced, if necessary, in the vicinity of the obstacle, and the movement is stopped if the mast approaches the obstacle too closely. An audible or verbal warning can also be activated on the remote control 51 to indicate the risk of collision.Furthermore, the operator could be shown, for example, using traffic light colors green, yellow, and red, or in a similar suitable manner, whether the mast tip 9 or the articulated mast 5 is located in a very well-mapped area (green) or, for example, in an unmapped area (red), such as behind buildings / building edges that the sensors have not yet been able to detect. Areas that are only partially mapped, where an operator cannot yet rely on complete obstacle detection, could, for example, be marked yellow.

[0090] In the event of an obstacle H3 being detected as a power line, a significantly greater distance must be maintained between the articulated mast 5 and the obstacle. If the power line is located relatively close, the unfolding of the articulated mast 5 can, under certain circumstances, be prevented from the outset, either automatically or manually, by the control unit 50. Both the module 50f, which determines automatic movement sequences, and the module 50g for collision avoidance during manual / semi-automatic operation, transmit the control information to a module for mast control 50f, which then generates, for example, the control commands for the hydraulic valves of the slewing drive 2 and the slewing drives 8a, b, c, d, e.

[0091] Figure 11 shows a point cloud generated by the invention presented here during the actual unfolding of a folding mast 5 of a large manipulator 5. This point cloud can be used by the control unit 50 to generate a three-dimensional environment model. The position of the large manipulator 1 itself is indicated in the center of this virtual model as a white box for illustrative purposes only. In reality, the large manipulator 1 is not visible in this virtual model because, as explained above, the elements of the large manipulator 1 were eliminated using the virtual model of the large manipulator 1 in module 50e. This also applies to the folding mast 5, because the points in the point cloud reflected by the folding mast 5 itself were eliminated from the point cloud using the virtual model of the large manipulator 1 in module 50e of the control unit 50, as explained above.For illustration, the trajectories B of two LiDAR sensors 40a and 40c (see Figure 4) are shown in Figure 11, illustrating the temporal evolution of the positions of the two LiDAR sensors 40a and 40c during the unfolding process of the articulated mast 5. Only through evaluation in module 50c of the control unit 50 do the individual points of the point cloud become objects, for example, a hall H1 and silos H2, which represent obstacles to be considered in the movement area of ​​the articulated mast 5. The density of the points in the point cloud is highest in the immediate vicinity of the large manipulator 1 and decreases with increasing distance from the large manipulator 1. It is easy to understand that the three-dimensional environment model becomes increasingly precise through the continuous acquisition and movement of the articulated mast 5 and its continuous updating and supplementation, because more and more detected points in space can be used to derive the three-dimensional environment model.As explained above, by cleverly positioning and aligning at least one environmental sensing sensor 40a, a very simple three-dimensional environmental model can be created even at the beginning of the unfolding process of the articulated mast 5. This model supports the unfolding process from the outset. A pre-calculated and predefined sequence of movements for the automatic unfolding and / or folding of the articulated mast 5, intended, for example, to move the tip 9 of the articulated mast 5 to the concrete dispensing point in the shortest possible time, is updated based on the three-dimensional environmental model of the large manipulator 1, which is continuously updated during the unfolding of the articulated mast 5. This ensures that there is no risk of the articulated mast 5 colliding with obstacles / objects H1, H2, H3, H4 within its movement area.Alternatively, for the automatic unfolding process, the folding mast 5 could first be moved into a raised starting position to acquire initial environmental information. The control unit 50's module 50f then searches for the optimal path to the target point based on a target position specified for the mast tip 9 and the information currently available from the three-dimensional environment model. This path is continuously updated. Module 50f thus continuously generates control commands for the individual actuators 2, 8a, 8b, 8c, 8d, and 8e, which are forwarded to the actuators via the mast control unit of module 50h.

[0092] Figure 12 shows a top view of a mast segment 6a, b, c, d or e with, for example, environmental detection sensors 40g, 40h, 40i designed as LiDaR sensors, wherein the sensors are selected in such a way that a high accuracy for the derivation of the three-dimensional environmental model is achieved with the simplest possible, i.e. also cost-effective sensors.

[0093] The first principle behind this sensor selection is to combine sensors with different resolutions. The second principle is to combine sensors with different fields of view, for example, dome sensors with hemispherical vision and surround sensors with 360-degree surround view. The third principle is to assign different tasks to the sensors.

[0094] For the sensor selection shown in Figure 12, this means, for example, that at least one, preferably two, LiDaR dome sensors 40h and 40j, for example with lower resolution, which are generally correspondingly inexpensive, are arranged, for example, laterally, preferably opposite each other, on a mast segment 6a, 6b, 6c, 6d, 6e, which are preferably designed for the continuous detection of the environment, but are primarily not used for localization, i.e., position determination.

[0095] One or more additional LiDAR sensors 40i, for example with 360-degree surround view, shown below the LiDAR sensor 40j as an example here, have a higher resolution or point quality and are used for localization, i.e., position determination. This makes them advantageous for determining the trajectory of sensors 40h, 40i, and 40j. The precise determination of the trajectory by the LiDAR sensors 40h and 40j allows the current measurements from these sensors to be preferentially incorporated into the three-dimensional environment model. This enables the consideration of highly dynamic objects as well as areas that the higher-resolution 360-degree surround view sensor 40i cannot detect due to its smaller field of view.The use of lower resolution sensors also has the advantage that the requirements for the necessary computing power for creating the three-dimensional environment model are lower overall, and the overall costs are significantly lower than those of the high-resolution sensor.

[0096] During the continuous creation or derivation of the three-dimensional environment model, especially over a longer period, there is a risk that errors, for example in position determination, will accumulate over time. This could prevent the currently acquired environmental information from being assigned to the existing environmental model with sufficient accuracy, ultimately rendering the model unusable. This problem can occur, for example, if one or more sensors are pointed at an environment with few or no reference points for an extended period, such as the sky, a meadow, or an asphalt surface.If, for example, it becomes impossible to unambiguously assign new environmental data, the currently recorded environmental data, which contains usable reference points, such as the outline of a building, can be compared with the previously created environmental model. This allows the current position and orientation of the sensor(s) in space to be traced back so that the data provided by the environmental detection sensor in the future can again be unambiguously assigned to the three-dimensional environmental model, thus contributing to the ongoing development of the environmental model.

[0097] To provide the operator with simple visual assistance when controlling the articulated boom 5, the large manipulator 1 can display the current position of the articulated boom 5, for example, on the screen of the remote control 51 or on the truck-mounted concrete pump 1. The boom segments 6a, b, c, d, e and / or the joints 7a, b, c, d, e are displayed in different colors to indicate the proximity of each element to an obstacle. For example, the colors red (close to an obstacle), yellow, and green (far from obstacles) can be used. An additional indicator, for example, a color-coded bar graph, can display the worst-case scenario, such as red when one of the joints is close to an obstacle, so that the operator can quickly and reliably see that caution is required when moving the articulated boom 5 further.Additionally, an audible signal can support the visual display or be used as an alternative to it. Furthermore, alternatively or additionally, a voice output can audibly signal the danger when approaching an obstacle.

[0098] Reference sign list - Reference sign list

[0099] 1 Large manipulator I Truck-mounted concrete pump

[0100] 2 Rotary drive

[0101] 3 turntables

[0102] 4 frame

[0103] 5 Folding mast

[0104] 6a,b,c,d,e first to fifth mast segment

[0105] 7a,b,c,d,e first to fifth articulation joint

[0106] 8a,b,c,d,e first to fifth rotary actuator

[0107] 9 Masthead

[0108] 10 Driver's cab

[0109] 11 Support

[0110] 12 chassis

[0111] 13 feed hoppers

[0112] 14 End hose

[0113] 15 mast support

[0114] 16 Input unit

[0115] 19 Control unit

[0116] 28 concrete pump

[0117] 29 Conveyor line

[0118] 30 Conveyor pipe holders

[0119] 40a,b,c,d,e,f,g,h,i,j Area detection point detection

[0120] Sensor (LiDaR, RaDaR) 41 Imaging environment detection sensor (camera)

[0121] 42 Inertial Measurement Unit (IMU)

[0122] 43 satellite navigation receivers

[0123] 44 Mast sensors 50 Control unit

[0124] 50a Trajectory Determination

[0125] 50b raw data / point cloud

[0126] 50c evaluation

[0127] 50d Three-dimensional environment model 50e Virtual model of the large manipulator

[0128] 50f Determination of movement sequence automatic operation

[0129] 50g Collision avoidance manual operation

[0130] 50h mast control

[0131] 51 Remote control B Trajectory

[0132] H1, H2, H3, H4 objects

[0133] -Patent claims-

Claims

Patent claims 1. Large manipulator (1), in particular a truck-mounted concrete pump, with a mast support (3) rotatable about a vertical axis by means of a rotary drive (2) and arranged on a frame (4), a hinged mast (5) comprising two or more mast segments (6a, b, c, d, e), wherein the mast segments (6a, b, c, d, e) are pivotably connected to the respective adjacent mast support (3) or mast segment (6a, b, c, d, e) via hinge joints (7a, b, c, d, e) by means of a swivel drive (8a, b, c, d, e), a control device (50) designed for controlling the rotary drive (2) and the swivel drives (8a, b, c, d, e) of the large manipulator (1), characterized in that at least one [unclear] is connected to the control device on the hinged mast (5). (50) connected environmental sensing sensor (40a, b, c, d, e, f, g; h, i, j;41) is arranged, which is designed for the continuous acquisition of environmental information of the large manipulator (1), wherein the control device (50) is further designed to continuously derive a three-dimensional environmental model of the large manipulator (1) from the environmental information acquired by the at least one environmental detection sensor (40a, b, c, d, e, f, g; h, i, j; 41) during the movement of the articulated mast (5) and / or the operation of the large manipulator (1).

2. Large manipulator according to claim 1, characterized in that the control device (50) is configured to continuously supplement and / or update the three-dimensional environment model during the movement of the articulated mast (5) and / or the operation of the large manipulator (1).

3. Large manipulator (1 ) according to one of the preceding claims, characterized in that the at least one environment detection sensor (40a, b, c, d, e, f, g, h, i, j) detects points in space as environment information.

4. Large manipulator (1) according to claim 3, characterized in that the at least one environmental detection sensor (40a, b, c, d, e, f, g, h, i, j) is designed as a radar or LiDaR sensor.

5. Large manipulator (1 ) according to one of claims 1 or 2, characterized in that the at least one environmental detection sensor (41 ) is designed as an imaging sensor.

6. Large manipulator according to one of the preceding claims, characterized in that the control device (50) is configured to determine the trajectory (B) of the at least one environment detection sensor (40a, b, c, d, e, f, g; h, i, j; 41 ).

7. Large manipulator (1 ) according to claim 6, characterized in that the control device (50) is configured to create a point cloud of the environment of the large manipulator (1 ) on the basis of the determined trajectory (B) of the at least one environment detection sensor (40a, b, c, d, e, f, g; 41 ) and the points detected in space by the at least one environment detection sensor (40a, b, c, d, e, f, g; h, i, j; 41 ).

8. Large manipulator (1 ) according to claim 7, characterized in that the control device (50) is configured to eliminate from the point cloud of the environment of the large manipulator (1 ) such points that are caused by the large manipulator (1 ) itself.

9. Large manipulator (1 ) according to claim 8, characterized in that the control device (50) is configured to eliminate points in the point cloud of the environment of the large manipulator (1 ) caused by the large manipulator (1 ) using a virtual model of the large manipulator (1 ).

10. Large manipulator (1 ) according to one of claims 7 to 9, characterized in that the control device (50) is configured to evaluate the point cloud of the environment of the large manipulator (1 ) for the generation of the three-dimensional environment model.

11. Large manipulator (1 ) according to claim 10, characterized in that the control device (50) is configured to identify objects (H1 , H2, H3) when evaluating the point cloud of the environment of the large manipulator (1 ).

12. Large manipulator (1 ) according to claim 10 or 11 , characterized in that the control device (50) is configured to identify, in particular, horizontally or vertically oriented, linear structures when evaluating the point cloud of the environment of the large manipulator (1 ).

13. Large manipulator (1 ) according to claim 12, characterized in that the control device (50) is configured to identify, in particular horizontally oriented and / or linearly formed and / or sagging linear structures as current lines when evaluating the point cloud of the environment of the large manipulator (1 ).

14. Large manipulator (1 ) according to one of claims 6 to 13, characterized in that the control device (50) is configured to continuously update the three-dimensional environment model during the movement of the articulated mast (5) on the basis of the trajectory (B) of the at least one environment detection sensor (40a, b, c, d, e, f, g; h, i, j; 41 ) and the environment information of the at least one environment detection sensor (40a, b, c, d, e, f, g; h, i, j, 41 ).

15. Large manipulator (1 ) according to one of claims 6 to 14, characterized in that the control device (50) is configured to use the environmental information provided by the at least one environmental sensing sensor (40a, b, c, d, e, f, g, h, i, j; 41 ) for determining the trajectory (B) of the at least one environmental sensing sensor (40a, b, c, d, e, f, g, h, i, j; 41 ).

16. Large manipulator (1 ) according to one of claims 6 to 15, characterized in that a mast sensor (44) for determining the pose of the articulated mast (5) is arranged on the articulated mast (5) and the control device (50) is designed to use the pose of the articulated mast (5) determined by the mast sensor (44) for determining the trajectory (B) of the at least one environment detection sensor (40a, b, c, d, e, f, g, h , i, j; 41 ).

17. Large manipulator (1 ) according to one of claims 6 to 16, characterized in that at least one satellite navigation sensor (43) for acquiring position data is arranged on the articulated mast (5) and the control device (50) is designed to use the position data acquired by the satellite navigation sensor (43) for determining the trajectory (B) of the at least one environment detection sensor (40a, b, c, d, e, f, g, h, i, j; 41 ).

18. Large manipulator (1 ) according to one of claims 6 to 17, characterized in that at least one inertial measurement unit (IMU) is designed for detecting accelerations and / or rotation rates and is preferably arranged in the immediate vicinity of an environment detection sensor and the control device (50) is designed to use the accelerations and / or rotation rates detected by the inertial measurement unit (IMU) for determining the trajectory (B) of the at least one environment detection sensor (40a, b, c, d, e, f, g, h, i, j; 41 ).

19. Large manipulator (1 ) according to one of claims 3 to 18, characterized in that at least one ambient detection sensor (40e, f, i) detecting points in space has a 360-degree viewing angle in the horizontal direction and a viewing angle (a) of 0 to 90 degrees in the vertical direction.

20. Large manipulator (1) according to claim 19, characterized in that at least two ambient detection sensors (40e, f) with a 360-degree viewing angle in the horizontal direction and a viewing angle (a) of 0 to 90 degrees in the vertical direction are arranged on the articulated mast (5), wherein an ambient detection sensor (40e) is configured to detect the environment along the unfolding plane and an ambient detection sensor (40f) is configured to detect the environment in a direction orthogonal to the unfolding plane of the articulated mast (5).

21. Large manipulator (1 ) according to one of claims 3 to 17, characterized in that at least one ambient detection sensor (40a, b, c, d, h, j) detecting points in space has a hemispherical field of view.

22. Large manipulator (1) according to claim 21, characterized in that at least two points in space detecting ambient sensors are mounted on the articulated mast (5). Detection sensors (40a, b) with hemispherical vision are arranged laterally opposite each other on a first mast segment (6b) of the articulated mast (5).

23. Large manipulator (1 ) according to claim 22, characterized in that two additional environmental detection sensors (40c, d) with hemispherical vision are arranged laterally opposite each other on a second mast segment (6d).

24. Large manipulator (1 ) according to one of the preceding claims, characterized in that the control device (50) is designed to continuously derive the three-dimensional environment model of the folding mast (5) during unfolding and / or during operation and / or during folding of the folding mast (5).

25. Large manipulator (1 ) according to one of the preceding claims, characterized in that the control device (50) is configured to determine a control sequence for the automatic unfolding and / or the automatic folding of the folding mast (5) on the basis of the three-dimensional environment model.

26. Large manipulator (1 ) according to claim 24, characterized in that the control device (50) is configured to update the sequence of movements for the automatic unfolding and / or folding of the folding mast (5) on the basis of the three-dimensional environment model of the large manipulator (1 ) which is continuously updated during the unfolding and / or folding of the folding mast (5).

27. Large manipulator (1) according to one of claims 1 to 24, characterized in that the control device (50) is configured to control the movement of the articulated mast (5) during manually controlled operation of the articulated mast (5) on the basis of the continuously derived three-dimensional to limit the environment model of the large manipulator (1) to avoid collisions with the environment.

28. Method for continuously deriving a three-dimensional environmental model of the environment of a large manipulator (1) with a mast stand (3) rotatable about a vertical axis by means of a rotary drive (2) and arranged on a frame (4), a foldable articulated mast (5) comprising two or more mast segments (6a, b, c, d, e), wherein the mast segments (6a, b, c, d, e) are pivotally connected to the respective adjacent mast stand (3) or mast segment (6a, b, c, d, e) via hinge joints (7a, b, c, d, e) by means of a pivot drive (8a, b, c, d, e) and at least one environmental detection sensor (40a, b, c, d, e, f, g; 41) arranged on the articulated mast (5) for acquiring environmental information of the large manipulator (1 ) is trained, the procedure comprising the following steps: - Unfolding the folding mast (5) - continuous acquisition of environmental information provided by the at least one environmental sensing sensor (40a, b, c, d, e, f, g, h, i, j; 41 ) during the unfolding of the folding mast (5) - Determining the trajectory (B) of the at least one environmental sensing sensor (40a, b, c, d, e, f, g, h, i, j; 41 ) during the unfolding of the folding mast (5), - continuous derivation of a three-dimensional environment model of the large manipulator (1 ) based on the acquired environment information and the trajectory (B) of the at least one environment detection sensor (40a, b, c, d, e, f, g, h, i, j; 41 ).

29. Method according to claim 27, characterized in that the environmental information provided by the at least one environmental sensing sensor (40a, b, c, d, e, f, g, h, i, j; 41) is used to determine the trajectory (B) of the at least one environmental sensing sensor (40a, b, c, d, e, f, g, h, i, j; 41).

30. Method according to one of claims 28 or 29, wherein the three-dimensional environment model is continuously supplemented and / or updated during the movement of the articulated mast (5). -Summary-

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