WO2024017809A1

WO2024017809A1 - Method for the automated assembly of two parts, comprising automatic control using cameras

Info

Publication number: WO2024017809A1
Application number: PCT/EP2023/069738
Authority: WO
Inventors: Gilles CHABERT; François CHAUMETTE; Adolfo Suarez Roos
Original assignee: Institut De Recherche Technologique Jules Verne
Priority date: 2022-07-16
Filing date: 2023-07-16
Publication date: 2024-01-25
Also published as: FR3137859A1

Abstract

The invention relates to a method for the automated assembly of a stationary part (1) with a moving part (2) capable of being displaced relative to the stationary part by a robot. The method comprises the following steps of: determining reference points at the first end (3) of the stationary part (1) and at the second end (4) of the moving part; positioning at least one camera (5, 6, 7) such that the reference points of the two parts are in the camera's field of vision; applying a primary visual control loop based on images of the ends of the two parts to determine a first displacement instruction for the robot; and applying a secondary visual control loop comprising a computation using the principle of vector fields based on images of the ends of the two parts to generate a second displacement instruction for embedding the parts.

Description

DESCRIPTION

METHOD FOR AUTOMATED ASSEMBLY OF TWO PARTS INCLUDING SERVO CONTROL WITH CAMERAS

TECHNICAL FIELD OF THE INVENTION

[0001] The invention relates, in general, to the technical field of automated assembly processes of two parts by robotic systems and more particularly the precision assembly of parts such as beams comprising a mechanical connection of the tenon/clevis type at their end. It also aims at an assembly system implementing these processes.

[0002] The invention relates more specifically to an automated assembly process for aligning and embedding two beams of an aircraft.

[0003] This type of robotic system is also called a machine tool. By the term machine tool, we mean a mechanism composed of controlled digital axes. These may in particular be robotic gantries or industrial robots identified below under the term robot.

STATE OF PRIOR ART

[0004] Generally speaking, the structure of an aircraft is very complex, and it is often divided into several structural elements having large sections. For example, the fuselage of an aircraft is made up of several sheets supported by an internal structure comprising several beams assembled together. To be able to be assembled, these beams are first positioned in relation to each other with precision, then fitted into one another.

[0005] Aircraft manufacturers currently use global positioning of the modules integrating the beams to be assembled by a laser tracking type metrological system. The beams are not designed to be directly embedded. To achieve the mechanical connection, a male beam includes tenons at one of its ends intended to be inserted into yokes provided at one end of a female beam. One of the beams is movable relative to the other. [0006] The mechanical connection is made by alternating approach movements and, in the case of a “practical” adjustment, adjustment of the two beams. The tenons are remachined on site to adapt to the geometry of the yokes.

[0007] The assembly is carried out iteratively by the operators, who alternate between reading the relative positions of the beams to be assembled and moving the support supporting one of the beams. This manual movement requires the experience of the operator to overcome in particular the deformation of the tools, their alignment errors or mechanical clearances. This manual moving process is also very time-consuming.

[0008] Furthermore, it is common for certain types of aircraft that the final alignment of the bores of the tenons and yokes does not respect the tolerances. There may be 1mm spacing between beams. The tenons must then be pushed through.

[0009] We know the document CN110919654 which aims to resolve these problems and which discloses a robotic arm controlled by a camera. The camera produces images of the interface between two parts of an aircraft fuselage to be assembled which are transmitted to an image processing system which in return calculates a movement instruction which is transmitted to the robotic arm.

[0010] This document also discloses a robotic automatic assembly system for two aircraft beams whose mechanical connection consists of tenons and yokes. The system includes three cameras placed around the connection and means for executing a visual servo algorithm guiding the embedding movement.

[0011] However, these camera control systems are not precise over the entire trajectory and can lead to collisions or friction between the sheets, particularly during the embedding step which is delicate. It is indeed difficult to obtain a perfectly linear movement. STATEMENT OF THE INVENTION

[0012] The invention aims to remedy all or part of the disadvantages of the state of the art by proposing in particular an automated assembly process that is more precise and faster than those of the prior art.

[0013] To do this, according to a first aspect of the invention, a method of automated assembly of a fixed part with a moving part capable of being moved relative to the fixed part by a robot is proposed. The method comprises the following steps: determining reference points at a first end of the fixed part and at a second end of the moving part, positioning at least one camera so that the reference points of the two parts are in the visual field of the camera, the camera being fixed in relation to the fixed part, application of a primary visual control loop from images of the ends of the two parts taken by the camera to determine a first movement instruction of the robot to enable it to bring the moving part closer to the fixed part, application of a secondary visual control loop comprising a calculation using the principle of vector fields from the images of the ends of the two parts taken by the camera to generate a second movement instruction allowing the robot to embed the moving part in the fixed part, and fixing the two parts together.

[0014] According to one embodiment, the primary visual control loop comprises the following steps: taking an image of the ends of the two parts, determining a target image, and comparison between pixels of the target image and pixels of the image taken to generate the movement instruction based on a difference between said pixels.

[0015] According to another embodiment, the assembly method comprises an initial step in which the position and orientation of the camera relative to the fixed part are determined from observation of the end of the fixed part by the camera and via a digital optimization calculation.

[0016] According to another embodiment, a target vector (x, y) of the moving part is determined from the relative position between the fixed part and the camera and from the embedding configuration between the fixed part and the moving part, x and y being the coordinates of the target landmarks.

[0017] According to another embodiment, a measurement vector (x', y') is determined from the images taken by the camera, x' and y' being the coordinates of the reference points on the parts. The measurement vector (x’, y’) is compared to the target vector (x, y) to determine the distance between pixels. A speed profile is determined from the difference. A pseudo-inverse operation of the interaction matrix is applied to the speed profile to obtain Cartesian speeds and a multiplication by the inverse Jacobian matrix of the robot is applied to the Cartesian speeds to obtain a movement instruction.

[0018] According to another embodiment, the assembly process comprises, after the initial step, a step of presenting the parts in an open loop. A simple open loop is made during the presentation stage at the end of which the pieces are separated by a few centimeters.

[0019] The part presentation step is followed by a primary visual control loop of pre-embedding during a pre-embedding step at the end of which the parts are correctly aligned, that is to say say in a configuration where a simple translation remains to be done to obtain contactless embedding. A target vector (x, y) is determined during each of these steps. A secondary visual control loop is then produced during a step mounting in which the parts fit without contact until the bores are aligned.

[0020] According to another embodiment, to produce the secondary visual control loop, a first target vector S corresponding to a first position and a second target vector S2 corresponding to a second position are calculated during the pre-step. -embedding. A line [si, S2] in each camera image is drawn in pixel space. Images of the ends of the parts are taken by the camera to obtain a vector field f(s) in each camera image from vectors s measured by the cameras.

Preferably, a pixel speed profile is determined from the vector field f(s). A pseudo-inverse operation of the interaction matrix is applied to the pixel speed profile to obtain Cartesian speeds and a multiplication by the inverse Jacobian matrix of the robot is applied to the Cartesian speeds to obtain the approximation instruction making it possible to pilot the robot.

According to one embodiment, the vector field f(s) is constructed around the segment [si, S2] delimiting a Cartesian trajectory.

[0023] According to one embodiment, for the construction of the vector field f(s), the image space is divided into three zones, including: an exterior zone where f reduces s to a baseline formed by the line passing through if and S2, following a proportional law based on a deviation, or a distance, from the baseline, with a gain X; a corridor where f brings s back to the baseline while making it progress towards S2; and a braking zone where f converges s towards S2 with an average deceleration a along the baseline. According to another embodiment, the reference points comprise disc-shaped markers distributed around bores provided on the moving part and on the fixed part for fixing the two parts.

[0025] The invention also relates to a system for automated assembly of a fixed part with a moving part capable of being moved relative to the fixed part by a robot. The system implements the assembly process as defined previously.

[0026] The invention thus makes it possible to provide an automated assembly process that is more precise than those of the prior art and more particularly makes it possible to move the moving part along a more rectilinear trajectory while reducing the duration of the assembly operation. less than three minutes away.

[0027] It is also possible to extend this process to a curved path.

[0028] The proposed solution does not create collision or friction between the parts.

[0029] It also has a positioning repeatability of the order of

0.2mm.

[0030] In addition, the cameras can be placed approximately around their respective nominal positions at the same time as the assembly operation. Camera registration is carried out automatically.

[0031] If the moving part deviates from the assembly axis, the process simultaneously makes it possible to reduce the gap and move the moving part forward. The balance between these two actions can be adjusted empirically by adjusting a gain in order to avoid contact with the two parts.

The solution is generic and can be extended to other types of parts and for applications other than aircraft.

BRIEF DESCRIPTION OF THE FIGURES

Other characteristics and advantages of the invention will emerge on reading the description which follows, with reference to the appended figures, which illustrate: Figure 1: a view of a moving part moving relative to a fixed part during an assembly process, according to one embodiment of the invention; Figure 2: a view of the fixed part embedded in the moving part after the assembly process; Figure 3: a diagram representing the different operations applied during a primary visual control loop; Figure 4: a diagram representing the different operations applied during a secondary visual control loop; Figure 5: a view of a vector field comprising a vector segment [si, s2]; Figure 6: a schematic representation of the measurement space divided into three zones; Figure 7: a schematic representation of the decomposition of the vector s.

[0034] For greater clarity, identical or similar elements are identified by identical reference signs in all of the figures.

DETAILED DESCRIPTION OF AN EMBODIMENT

[0035] The invention relates to a method of automated assembly of a fixed part 1 with a moving part 2, as shown in Figure 1, capable of being moved relative to the fixed part 1 by a robot or a controller of speed.

[0036] By robot we mean a robotic system also called a machine tool. A machine tool can be a mechanism composed of servo-controlled digital axes. These may include robotic gantries or industrial robots or actuators.

[0037] In the example which follows, the movable part 2 is a female part comprising at least one yoke 11a, 11b, 11c extending in an axial direction parallel to the direction of advancement of the moving part 2. The yoke 11a, 11b, 11c comprises a bore 9 having an axis perpendicular to the axial direction X. In this example, the axial direction X is substantially horizontal.

[0038] Each yoke 11a, 11b, 11c also includes a housing 12.

The fixed part 1 is a male part comprising at least one tenon 10a, 10b, 10c extending in the axial direction The tenon 10a, 10b, 10c also comprises a bore 8 having an axis perpendicular to the axial direction X.

Alternatively, the moving part 2 can be a female part and the fixed part 1 can be a male part.

[0041] In the example of Figure 1 and Figure 2, the bores 8, 9 have a circular section but can have other shapes such as square or ovoid shapes.

Preferably, the movable part 2 comprises at least three yokes 11a, 11b, 11c and the fixed part 1 comprises at least three tenons 10a, 10b, 10c.

[0043] In the example of Figure 1 and Figure 2, the movable part 2 is a female part comprising five yokes lia, 11b, 11c including two first lateral yokes lia juxtaposed one above the other , two second side yokes 11b juxtaposed one above the other and a central yoke 11c positioned between the side yokes 11a, 11b.

[0044] The first two side yokes lia and the two second side yokes 11b each comprise a bore 9 which has a central axis perpendicular to the direction X and which extends in a direction Y.

The central yoke 11c comprises a central axis perpendicular to the direction X and which extends in a direction Z perpendicular to the directions X and Y.

[0046] By symmetry, the fixed part 1 is a male part comprising five tenons 10a, 10b, 10c extending in the axial direction X, including two first lateral tenons 10a juxtaposed one above the other, two second side tenons 10b juxtaposed one above the other and a central tenon 10c positioned between the side tenons 10a, 10b.

[0047] As illustrated in Figure 2, each tenon 10a, 10b, 10c of the fixed part 1 is intended to fit into one of the yokes 11a, 11b, 11c of the moving part 2 and more precisely in the housing 12 of the copes lia, 11b, 11c. The bores 9 of the yokes 11a, 11b, 11c and the bores 8 of the tenons 10a, 10b, 10c are then aligned. A fixing part can then be introduced into the bores 8, 9 to block the parts relative to each other.

In this example, the first end 3 of the fixed part 1 is progressively obscured by the second end 4 of the moving part 2. The moving part 2 only moves in translation.

[0049] In this example, the fixed parts 1 and mobile parts 2 are aircraft beams but the assembly process also applies to other types of parts.

According to a possible embodiment of the invention, the assembly method comprises a step of determining reference points at the first end 3 of the fixed part 1 and at the second end 4 of the moving part 2.

[0051] The principle consists of finding remarkable or identifiable points on parts 1, 2 so that a control based on image capture and processing can function.

Preferably, the reference points include disc-shaped markers distributed around each bore 9 provided on the moving part 2 and around each bore 8 provided on the fixed part 1.

[0053] In this example, the fixed 1 and movable 2 parts each comprise five bores 8, 9 and therefore five patterns each comprising eight disc-shaped markers distributed concentrically around the axis of each bore 8, 9. The patterns are identical and have a uniform color. [0054] The discs must have a precise and clean outline. They must not create excess thickness. They can be obtained by filling a colored substance with paint, resin, etc. in a knockout, then polishing the piece. In this example, there are therefore a total of 40 markers per piece.

[0055] The presence of markers is not a condition for success and should not appear as such. But it is preferable to add markers in order to have very high confidence in the measurements obtained by a visual process. The process works without artificial markers but this leads to greater complexity of image processing and less robustness to lighting conditions, without impacting the servo process itself.

[0056] Alternatively, the reference points can be the centers of the bores 8, 9.

[0057] The reference points of the moving part 2 must coincide with the reference points of the fixed part 1 during installation.

[0058] As a variant, it is not necessary for the reference points of the moving part 2 to coincide with the reference points of the fixed part 1.

The assembly method comprises a step of positioning at least one camera 5, 6, 7 so that the reference points of the two parts 1, 2 are in the visual field of the camera 5, 6, 7 The camera 5, 6, 7 is fixed relative to the fixed part 1.

[0060] It is possible to use a single camera 5, 6, 7 but it is preferable to use three as in the embodiment presented below because the depth is more sensitive to errors.

[0061] According to a preferred embodiment, a first camera 5 is positioned and oriented facing the bores 9 of the first two lateral yokes lia of the moving part 2 and facing the bores 8 of the first two lateral tenons 10a of the fixed part 1. A second camera 6 is positioned and oriented facing the bores 9 of the two second lateral yokes 11b of the moving part 2 and facing the bores 8 of the two second lateral tenons 10b of the fixed part 1. [0062] A third camera 7 is positioned and oriented facing the bore 9 of the central yoke 11c of the moving part 2 and facing the bores 8 of the central tenon 10c of the fixed part 1. The axis of the cameras 5 , 6, 7 is substantially perpendicular to the axial direction

[0063] For standard aircraft beams with bore diameters of a few centimeters, the cameras 5, 6, 7 can be 5, 6, 7 to 12 Megapixel cameras of the GV-5200SE-C-HQ model of the IDS company including M111FM16 lenses from the Tamron company. The intrinsic calibration of each camera 5, 6, 7 must be carried out rigorously (industrial calibration target) once the focus has been adjusted to obtain a clear image at approximately 30 cm distance. Each camera 5, 6, 7 is positioned approximately 30 cm from rooms 1, 2.

According to one embodiment, the assembly process comprises three stages of movement of the moving part 2 including a stage of presenting the parts 1, 2. The moving part 2 is “presented” facing the fixed part 1. The moving part 2 is in the field of vision of the cameras 5, 6, 7. The distance between the two parts 1, 2 in the axial direction X is a few centimeters.

[0065] The assembly method also comprises a pre-embedding step in which the movable part 2 is potentially moved along all axes until it is well aligned with the fixed part 1 and an embedding step in which the movable part 2 is fitted with the fixed part 1.

[0066] The assembly method comprises an initial step in which the position and orientation of the cameras 5, 6, 7 relative to the fixed part 1 are determined from observation of the end of the fixed part 1 by cameras 5, 6, 7 and by means of a digital optimization calculation of the least squares method type, for example. [0067] More precisely, during the initial step, each camera 5, 6, 7 observes the tenons 10a, 10b, 10c which face it (only one in the case of the third camera 7) and a treatment is applied image to get the centers of the markers.

[0068] Knowing the geometry of what the camera 5, 6, 7 observes, a position calculation algorithm is applied to deduce the relative position of the camera 5, 6, 7 relative to the fixed part 1. Preferably , the position calculation algorithm uses least squares optimization. This step is automatic but requires visual validation from the operator, for safety. Visual validation is done by noting the superposition in the image of the projected markers, that is to say where the markers are supposed to appear if the camera 5, 6, 7 is at the position calculated with the real markers.

The relative position of the fixed part 1 relative to the base of the robot is assumed to be known approximately. This is the case in practice because the fixed part 1 is located on a module or fixed support, which is referenced in the reference of a workshop.

[0070] For the presentation step, the moving part 2 is approached by the operator or by an open loop program towards a position sufficiently far from the fixed part 1 to avoid any risk of collision between the parts 1, 2 but sufficiently close so that the yokes lia, 11b, 11c of the moving part 2 enter the field of vision of the cameras 5, 6, 7.

[0071] For the pre-embedding step, a first primary visual control loop is applied from images of the ends of the two parts 1, 2 taken by the cameras 5, 6, 7 to determine a first setpoint of movement of a robot to enable it to correctly align the moving part 2 facing the fixed part 1.

[0072] The initial step makes it possible to produce the first primary visual control loop.

[0073] The initial step makes it possible to calculate a first target image if (or first setpoint in the image), as illustrated in Figure 3. The image is determined by virtually placing the fixed part 1 in the frame of the cameras 5 , 6, 7 using the position of cameras 5, 6, 7 and by simulating the images. The errors in estimating certain degrees of freedom of a camera are compensated by the combination of n images.

[0074] From the relative position of the cameras 5, 6, 7 relative to the fixed part

1, and from the embedding configuration of the fixed part 1 in relation to the moving part 2, it is possible to deduce the position of the cameras 5, 6, 7 in relation to the moving part

2.

[0075] From the pinhole model of the camera 5, 6, 7, it is possible to deduce the first target image if or target vector (xi, yi), xi and yi being the coordinates of the target landmark points during a step of calculating targets 13.

[0076] Then, an image of the end of the part 2 is taken to determine a measurement vector (x'i, y'i), x'i and y'i being the coordinates of the reference points on part 2 during a measurement step 14. A first measured image if i is obtained.

[0077] The measurement vector (x'i, y'i) is then compared to the target vector (xi, yi) to determine the difference between the pixels during a comparison step 15.

[0078] A speed profile is determined from the difference during a speed profile calculation operation 16.

[0079] The following proportional feedback law is used to calculate a desired speed s in the camera space: s = X (si - s'i), where X is a positive gain factor. However, only the direction of the velocity vector in image space is considered. The standard is calculated so that it follows a speed profile ensuring smooth and uniform acceleration until reaching a maximum speed, as well as uniform deceleration. However, close to the target, the constraint on deceleration is lifted to avoid making the control unstable: the vector is applied as is. [0080] An interaction matrix L _s is calculated. The interaction matrix is the name usually given to designate the Jacobian matrix linking the Cartesian kinematic torso to the pixel speeds.

[0081] A pseudo-inverse operation of the interaction matrix 17 is then applied to the speed profile to obtain Cartesian speeds v with the law: s = Ls.v.

[0082] A multiplication operation by the inverse Jacobian matrix of the robot (or actuators) 18 is applied to the Cartesian speeds to obtain a first movement setpoint comprising a movement speed of the robot and in particular a joint speed. The robot moves the moving part 2 towards the fixed part 1 according to the first movement instruction during a control step 19.

[0083] The embedding step generates a second target image S2 (or second setpoint in the image), corresponding to the final embedding position, as illustrated in Figure 4. The calculation of this target image follows the same process only for if.

The first and second vectors are obtained by concatenating the image instructions of the three cameras 5, 6, 7.

[0085] According to a variant, it is possible to position a camera in front of each bore. There are therefore in this case five cameras associated with five bores in the moving part (not shown).

[0086] In our example, the first and second target vectors therefore comprise a total of 80 components including the x and y coordinates of each of the 40 reference points.

The target vectors are manipulated in the standardized image plane (with z = 1 m). The stopping criterion applied is then a maximum gap between the two parts 1, 2 of 1.5 mm. At a distance from the cameras 5, 6, 7 not exceeding 40 cm, this error gives a pixel positioning error in space less than 0.6 mm. [0088] On the other hand, by averaging over the 40 pixels, the Cartesian precision obtained in practice is much better, of the order of 0.2 mm.

[0089] A secondary visual control loop comprising a calculation using the vector field principle is then applied during the embedding step, as illustrated in Figure 4, to improve linearity during this step which is delicate.

[0090] Alternatively, the secondary visual control loop can be used during another movement step.

[0091] This solution is based on 2 ideas. The first idea is to generate a control law for the robot explicitly in the form of a vector field f(s) in the space of images (or sensors). This vector field f(s) is an ad-hoc formula. By creating a vector field in image space, the key advantage of image-based servoing is maintained.

[0092] The second idea concerns the stability of the movement. In practice, the use of a formula based on errors as for the pre-embedding step (figure 3), in addition to the non-uniform speed, results in a zigzag movement of the robot around the assembly axis, with a high risk of collision.

[0093] The objective is to create a speed vector field f(s) from the measurements of the cameras 5, 6, 7 which respects the kinematics of the embedding.

[0094] The target (or expected) vectors si and S2 associated with these two expected positions are calculated in 2 steps.

[0095] First of all, an ideal Cartesian trajectory (segment [si, S2]) is constructed in the space of images. Then, the vector field f(s) is constructed around this Cartesian trajectory, as illustrated in Figure 5.

[0096] It is convenient for this to consider the fixed part 1 as a reference. The Cartesian trajectory of the moving part 2 is a pure translation from an initial position 1 to a final position 2. These positions are directly obtained from the geometry of the two parts 1, 2. [0097] Once a line is determined by the perspective projection, when the moving part 2 moves at constant speed from the first position to the second position, each pixel describes a segment in its own image. However, the speed of the pixel is not constant if its z coordinate in the frame of cameras 5, 6, 7 is not constant. This is why the z axis of the camera must necessarily be substantially parallel to the Z direction, that is to say orthogonal to the axial direction which means that the trajectory of the target vector s of all cameras 5, 6, 7 is very close to the segment. The idea is therefore to use this segment [si, S2] as the counterpart of the assembly axis in the image space of cameras 5, 6, 7.

[0098] Images of the ends of the parts 1, 2 are taken by each camera 5, 6, 7 to obtain vectors s measured during a measurement step 20. The vector field f(s) in each image of the cameras 5 , 6, 7 is then obtained from the vectors s measured by the cameras 5, 6, 7, during a vector field calculation operation f(s) 21 and as illustrated in Figure 5.

[0099] Figure 5 illustrates a field of vectors f(s) with the segment [si, S2] for a single pixel. In reality, it is a segment in the space of all pixels (40 in our example). The arrows represent the vector field f(s) for different vector values s measured by the cameras.

[00100] The vector field f(s) brings the points back to the target line [si, S2] and ensures their progress towards the target. Apart from the ends si and S2, the field is therefore parameterized by two distinct speeds: the one which controls the integration and the one which controls the correction of the differences. Each speed can be adjusted independently.

[00101] The following describes an example of constructing a vector field in more detail.

[00102] Let D be the assembly distance and Vo be the desired Cartesian speed. The corresponding (average) speed in the measurement space is

[00103] Due to the way in which the cameras are positioned, the real speed of s in the ideal trajectory deviates only slightly from its average value, and the deviation is thus well absorbed by the pseudo-inverse of the Jacobian matrix L _s , as described later.

[00104] The line passing through si and S2 is called “base line 26”, as illustrated in Figure 6, and do is the direction vector, which is voluntarily oriented from S2 towards si according to the following relationship

[00105] To construct the vector field, the sensor space is divided into three zones, including: an exterior zone Tl where f brings s back to the base line 26, following a proportional law based on the deviation (the distance per compared to the baseline 26) with a gain X, a corridor 28 where f brings s back to the baseline 26 while making it progress towards S2. The speed inside the corridor 28 has a constant standard: 11 f(s) 11 = vo, and a braking zone 29 where f makes s converge towards S2 with an average deceleration a along the base line 26.

[00106] The convergence is bounded by a decreasing exponential, either of rate a (which dominates the projection on the base line 26), or X (which dominates the projection orthogonal to the base line 26).

[00107] Thus, the vector field depends on 3 parameters: the desired speed vo in the corridor 28, the average deceleration a in the rupture zone 29, and the gain factor X modeling the force of attraction of the baseline 26. [00108] Braking zone 29 is represented by the gray butterfly in Figure 6.

51 the target S2 is exceeded (which can happen in practice), the braking zone 29 allows the system to move backwards. The recoil is represented by the thick arrow 30.

[00109] The field is constructed as illustrated in Figure 7. To begin, the vector s is decomposed into a scalar d and a vector e according to the following relationship: s =

52 + d.do + e

[00110] d, as "distance", represents the projection of s on the baseline 26 with S2 as origin, and e, as "error", represents the remainder. It is necessarily orthogonal to the base line 26. These parameters can be obtained quickly if the projection matrix on the base line 26 is calculated once and for all according to the following relationship: P = do.do ^T

[00111] In this case, d = do ^T P (s - S2) and e = (I - P) (s - S2).

[00112] A linear application with saturation v(d) is then defined. It represents the desired speed along baseline 26.

[00113] The vector field f(s) = f(d, e) is then defined, as illustrated in Figure 5.

[00114] Then, a pixel speed profile is determined from the vector field f(s), during a speed profile calculation operation 22.

[00115] A pseudo-inverse operation of the interaction matrix 23 is applied to the pixel speed profile to obtain Cartesian speeds.

[00116] A multiplication operation by the inverse Jacobian matrix of the robot 24 is then applied to the Cartesian speeds to obtain a reconciliation instruction making it possible to control the robot. The approximation instruction is expressed, among other things, in the form of speeds (the one which controls the integration and the one which controls the correction of the differences).

[00117] The robot moves the moving part 2 towards the fixed part 1 according to the approximation instruction during a control step 25. [00118] These different operations thus make it possible to carry out the embedding in a more linear manner with respect to the primary visual control loop. They also make it possible to avoid the numerous disadvantages of a discretized trajectory, in particular the jerky movement imposed by the convergence towards each intermediate point.

[00119] Unlike the primary control method, the measurement of the vectors is directly translated into a speed thanks to the ad hoc vector field f(s) ensuring both the reduction of the deviation (at the axis d 'embedding) and a speed of progression along the axis.

[00120] A movement speed is no longer simply deduced from a deviation which is compensated but all the desired movements are described explicitly from a given deviation, so that the kinematics of the embedding are well respected. This therefore gives a vector field in image space.

[00121] Alternatively, it is possible to apply a method with very slow embedding but rapid correction of the deviations. The field was constructed to be continuous at all points and therefore, in theory, not cause any sudden acceleration.

[00122] However, in practice, it is common for the system to slow down for safety reasons, due to a delay in the flow of images or errors linked to their processing. For this reason, the accelerations/decelerations are again properly managed by again applying a speed profile to the field of vectors f(s) at the output of the field.

[00123] The vector field f(s) is constructed using the fact that the projection of the Cartesian translation gives a straight line in the image of each pixel in 2 dimensions (2D). However, a Cartesian constant velocity translation will not result in a constant velocity trajectory in 2D.

[00124] Imposing a uniform speed on each pixel in 2D therefore results in a non-uniform Cartesian speed. Particularly, the speeds of the different pixels obtained do not result in the same Cartesian speeds. They are in fact incompatible, except in very special cases.

[00125] However, these two problems are negligible in practice because of the variation of the Cartesian speed and the decoupling of the pixels. The second problem is caught by the pseudo-inverse of the command.

[00126] Alternatively, the algorithm can construct a curved vector field, by exactly projecting the Cartesian speed vector onto each pixel. This calculation can be carried out dynamically at the point si or S2, by applying the camera model 5, 6, 7 from the estimated Cartesian position.

[00127] Naturally, the invention is described in the above by way of example. It is understood that those skilled in the art are able to carry out different variants of the invention without departing from the scope of the invention.

[00128] It is emphasized that all the characteristics, as they emerge for a person skilled in the art from the present description, the drawings and the attached claims, even if concretely they have only been described in relation to other specified features, both individually and in any combinations, may be combined with other features or groups of features disclosed herein, provided that this has not been expressly excluded or technical circumstances make such combinations impossible or meaningless.

Claims

CLAIMS Process for automated assembly of a fixed part (1) with a moving part (2) capable of being moved relative to the fixed part by a robot, characterized in that it comprises the following steps: determination of points of mark at a first end (3) of the fixed part (1) and at a second end (4) of the movable part (2), positioning of at least one camera (5, 6, 7) so that the points markings of the two parts (1, 2) are in the visual field of the camera (5, 6, 7), the camera (5, 6, 7) being fixed relative to the fixed part (1), application of a primary visual control loop from images of the ends (3, 4) of the two parts (1, 2) taken by the camera (5, 6, 7) to determine a first movement instruction of the robot to allow it to bring the moving part (2) closer to the fixed part (1), application of a secondary visual control loop comprising a calculation using the principle of vector fields from the images of the ends of the two parts (1, 2) taken by the camera (5, 6, 7) to generate a second movement instruction allowing the robot to embed the moving part (2) in the fixed part (1), and fixing the two parts (1, 2) together. Assembly method according to claim 1, characterized in that the primary visual control loop comprises the following steps: taking an image of the ends of the two parts (1, 2), determining a target image, and comparison between pixels of the target image and pixels of the image taken to generate the movement instruction based on a difference between said pixels.

3. Assembly method according to claim 2, characterized in that it comprises an initial step in which the position and orientation of the camera (5, 6, 7) relative to the fixed part (1) are determined from the observation of the end of the fixed part (1) by the camera (5, 6, 7) and by means of a digital optimization calculation.

4. Assembly method according to claim 3, characterized in that a target vector (x, y) of the moving part (2) is determined from the relative position between the fixed part (1) and the camera ( 5, 6, 7) and the embedding configuration between the fixed part (1) and the moving part (2), x ety being the coordinates of the target reference points.

5. Assembly method according to claim 4, characterized in that a measurement vector (x', y') is determined from the images taken by the camera (5, 6, 7), x' ety' being the coordinates of the reference points on the parts (1, 2), the measurement vector (x', y') being compared to the target vector (x, y) to determine the distance between the pixels, a speed profile being determined from the deviation, a pseudo-inverse operation of the interaction matrix being applied to the speed profile to obtain Cartesian speeds and a multiplication by the inverse Jacobian matrix of the robot being applied to the Cartesian speeds to obtain a movement instruction.

6. Assembly method according to any one of claims 3 to 5, characterized in that it comprises, after the initial step, a step of presenting the parts (1, 2) in an open loop, at the end of which the parts (1, 2) are spaced a few centimeters apart, the presentation step being followed by a primary visual pre-embedding control loop at the end of which the parts (1, 2) are face while being correctly aligned, a secondary visual control loop then being produced at the end of which the parts (1, 2) are correctly fitted together, a target vector (x, y) being determined during each of these steps .

7. Assembly method according to claim 6, characterized in that to produce the secondary visual control loop, a first target vector si corresponding to a first position and a second target vector S2 corresponding to a second position are calculated during the pre-embedding step, a straight line [si, S2] in each image of the cameras (5, 6, 7) being traced in the pixel space, images of the ends of the parts (1, 2) being taken by the camera (5, 6, 7) to obtain a vector field f(s) in each image of the cameras (5, 6, 7) to from vector(s) measured by the cameras (5, 6, 7). Assembly method according to claim 7, characterized in that a pixel speed profile is determined from the vector field f(s), a pseudo-inverse operation of the interaction matrix being applied to the profile of speed in pixels to obtain Cartesian speeds and a multiplication by the inverse Jacobian matrix of the robot being applied to the Cartesian speeds to obtain the approximation instruction allowing the robot to be controlled. Assembly method according to claim 7 or 8, characterized in that the vector field f(s) is constructed around the segment [si, S2] delimiting a Cartesian trajectory. Assembly method according to claims 7 to 9, characterized in that for the construction of the vector field f(s), the image space is divided into three zones, including: an exterior zone (27) where f reduces s to a base line (26) formed by the line passing through si and S2, following a proportional law based on a deviation, or a distance, relative to the base line (26), with a gain X; a corridor (28) where f brings s back to the baseline (26) while making it progress towards S2; and a braking zone (29) where f makes s converge towards S2 with an average deceleration a along the baseline 26.

11. Assembly method according to any one of claims 1 to 10, characterized in that the reference points comprise disc-shaped markers distributed around bores (8, 9) provided on the movable part (2) and on the fixed part (1) for fixing the two parts. 12. System for automated assembly of a fixed part (1) with a moving part (2) capable of being moved relative to the fixed part by a robot, characterized in that it implements the assembly process as defined according to any one of claims 1 to 11.