An escalator autonomous avoidance warning method for robots

Abstract

The present invention discloses an escalator autonomous avoidance warning method for a robot, and relates to the field of robot automatic control. It includes: predetermining the positions of all escalators within the robot's range of activity, setting a dangerous area for each escalator, and recording it as a semantic map configuration; when the robot moves, obtaining image data and laser data of the robot's movement direction, fusing the image data and laser data to obtain the escalator detection result; judging whether the stop operation condition is met according to the semantic map configuration and the detection result, and if so, stopping the movement of the robot and alarming. In the case that the robot loses its position, the method provided by the present invention can rely on the fusion of image data and laser data to promptly and accurately issue a warning, stop the robot movement, and prevent the robot from entering the escalator danger zone.

Description

Technical Field

[0001] The invention relates to the field of robot automatic control, and in particular to an escalator autonomous avoidance warning method for a robot. Background Art

[0002] At present, with the development of robot technology, robots are increasingly used in logistics transportation, shopping mall guidance, short-distance delivery and other fields. In the daily work of robots, automatic obstacle avoidance has always been the main research direction. Taking robots operating in shopping malls as an example, escalators are often extremely dangerous. If the robot loses its positioning and mistakenly enters the escalator area, or is pushed into the area by someone, the robot may fall into the escalator or block the escalator exit, posing a safety hazard.

[0003] However, the existing obstacle avoidance solutions only set the escalator area as a dangerous area or a virtual wall to prohibit the robot from entering, thereby avoiding danger. However, in special circumstances such as the robot's positioning is lost, deviation occurs, or it is pushed or bumped by people, it is still possible to enter the dangerous area. Summary of the invention

[0004] The technical problem to be solved by the present invention is to address the deficiencies in the prior art and to provide an escalator autonomous avoidance and warning method for a robot, which can effectively avoid the dangerous area of ​​the escalator and prevent dangerous situations. Moreover, based on the fusion of sensor data such as images and lasers, a danger warning can be issued in time when the robot is about to drive into the escalator area, and the machine can be stopped to avoid further losses.

[0005] The technical solution of the present invention to solve the above technical problems is as follows:

[0006] An escalator autonomous avoidance warning method for a robot, comprising:

[0007] Predetermine the positions of all escalators within the robot's activity range, and set a danger zone for each escalator, which is recorded as a semantic map configuration;

[0008] When the robot moves, image data and laser data of the movement direction of the robot are acquired, and the image data and the laser data are fused to obtain a detection result of the escalator;

[0009] It is determined whether a stop operation condition is met according to the semantic map configuration and the detection result. If the condition is met, the movement of the robot is stopped and an alarm is issued.

[0010] Another technical solution of the present invention to solve the above technical problems is as follows:

[0011] A storage medium stores instructions, and when a computer reads the instructions, the computer executes the automatic escalator autonomous avoidance warning method for a robot as described in the above technical solution.

[0012] Another technical solution of the present invention to solve the above technical problems is as follows:

[0013] An escalator autonomous avoidance warning device for a robot, comprising:

[0014] Memory for storing computer programs;

[0015] The processor is used to execute the computer program to implement the automatic escalator autonomous avoidance warning method for the robot as described in the above technical solution.

[0016] The beneficial effects of the present invention are as follows: the autonomous avoidance warning method provided by the present invention can automatically avoid the dangerous area of ​​the escalator through positioning and image data when the robot is working normally, and in the case of losing positioning, it can rely on the fusion of image data and laser data to promptly and accurately issue a warning, stop the robot movement, and prevent the robot from entering the dangerous area of ​​the escalator.

[0017] Advantages of additional aspects of the present invention will be given in part in the following description, and in part will be obvious from the following description, or will be learned through practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 A flow chart of an embodiment of an escalator autonomous avoidance warning method according to the present invention;

[0019] Figure 2 A schematic diagram of a dangerous area provided for an embodiment of the escalator autonomous avoidance warning method of the present invention;

[0020] Figure 3 A schematic diagram of a stop operation condition judgment flow chart provided for other embodiments of the escalator autonomous avoidance warning method of the present invention;

[0021] Figure 4 A schematic diagram of the robot orientation provided for other embodiments of the escalator autonomous avoidance warning method of the present invention;

[0022] Figure 5 A structural framework diagram provided for an embodiment of the automatic escalator autonomous avoidance warning device of the present invention. DETAILED DESCRIPTION

[0023] The principles and features of the present invention are described below in conjunction with the accompanying drawings. The examples given are only used to explain the present invention but not to limit the scope of the present invention.

[0024] like Figure 1 As shown, it is a flow chart of an embodiment of the escalator autonomous avoidance warning method of the present invention. The present invention is implemented based on the camera, laser transmitter, laser receiver and processor of the robot. The camera captures the image in the running direction of the robot, the laser transmitter emits laser, and the laser receiver receives laser, so as to obtain laser data. Then, the processor processes and fuses the image data and laser data, so as to perform the escalator autonomous avoidance warning. The method includes:

[0025] S1, predetermine the locations of all escalators within the robot's range of activity, and set a danger zone for each escalator, which is recorded as a semantic map configuration.

[0026] like Figure 2 As shown, an exemplary schematic diagram of a danger zone is given, in which an example of two side-by-side escalators is given, the width of the escalator is w, and an elliptical danger zone is set with the midpoint of the escalator entrance as the center, the width w of the escalator extending 1 meter as the short axis, and 3 meters as the long axis.

[0027] Preferably, in order to enable the robot to avoid obstacles better, a rectangular virtual wall may be set around the dangerous area to surround the dangerous area and prevent the robot from entering the virtual wall.

[0028] It should be understood that in actual operation, the range of the virtual wall must at least cover the dangerous area set in the algorithm, that is, Figure 2 The elliptical area in the figure. Those skilled in the art can set the specific range of the danger zone according to actual needs, and can also set danger zones of different shapes. For example, Figure 2 The range within the virtual wall is set as the danger zone.

[0029] Alternatively, when there are multiple escalators, the short axis distance may be determined as follows:

[0030]

[0031] Among them, short is the short axis distance, n is the number of escalators, and wi is the width of the i-th escalator.

[0032] It should be noted that during the movement of the robot, it will first check whether its position is within the danger zone of the escalator. If it is already in the danger zone, an alarm will be directly sounded and the machine will be stopped to prevent further movement from causing it to fall off the escalator. If it is not in the danger zone, the existing detection model will be used to check whether the camera data has any detection results of the escalator. If not, the robot can continue to move forward. If the image data detects an escalator, it will be determined whether the detection result meets the stopping conditions. Only when the detection result meets certain conditions will an early warning be issued and the robot will be stopped. Otherwise, it is considered that it does not pose a danger and the robot can continue to move.

[0033] During the movement of the robot, since the early warning of the escalator uses positioning information, it is necessary to record the actual location information of the escalator in the global map in the configuration file in advance, such as the floor and location, and record it as a semantic map configuration for use by the early warning algorithm.

[0034] For example, the early warning algorithm can include two global cache variables, lost and danger, to record the number of times the corresponding event occurs. Lost means that the robot loses its position, and danger means that the robot is in a dangerous area. For example, Figure 3 In the process shown, reset refers to the clearing operation of cache variables, and reset all means clearing both the lost and danger caches.

[0035] S2, when the robot moves, the image data and laser data of the robot's moving direction are obtained, and the image data and laser data are fused to obtain the detection result of the escalator.

[0036] It should be noted that the image data and laser data obtained by the robot can be fused to obtain the rough position of the escalator as auxiliary information for the robot to avoid and warn. Since the camera only captures images, it is difficult to accurately locate the escalator. By fusing the image data with the laser data, the escalator can be accurately located.

[0037] The specific fusion method can be set according to actual needs, for example Figure 4 As shown, the path of the laser can be drawn in the image, and the laser data can be overlapped with the image data to assist in determining the position of the escalator.

[0038] Optionally, a pre-trained escalator detection model can be used to obtain the escalator detection results on the image, the approximate direction angles of the left and right boundaries of the escalator, and the minimum or median of the laser distance values ​​within the left and right direction angles as the approximate position of the escalator. The corresponding angle of the laser beam is the direction angle of the escalator, and the more accurate position of the escalator can be obtained by fusion. Based on this information, when the robot loses its positioning and is about to fall into the dangerous area of ​​the escalator, it can give accurate avoidance and warning signals in time.

[0039] The escalator detection model can be obtained by inputting a large number of images containing escalators into a deep neural network for training. The training process belongs to the existing technology and will not be described in detail here.

[0040] S3, judging whether the stopping condition is met according to the semantic map configuration and the detection results, if so, stopping the movement of the robot and giving an alarm.

[0041] It should be noted that in the algorithm, the detection results of the robot camera data can be used as input, and then various constraints are used to determine whether the stopping conditions are met.

[0042] For example, when the robot detects an escalator on the current floor through the camera, it can check whether the floor where the robot is located contains the escalator semantic map configuration. If there is no escalator on the current floor in the configuration file, perform the "reset all" operation, clear the lost and danger caches, and check whether there is an escalator configuration in the entire building. If so, the robot may have located the wrong floor, report an early warning and stop moving. If there is no escalator configuration in the entire building, it is considered that the camera data has been misdetected and the robot continues to move.

[0043] It should be understood that the specific stopping conditions can be set according to actual needs. For example, when the movement direction of the robot and the orientation angle of the escalator are within a certain range, the stopping conditions can be considered to be met; for example, when the laser distance is less than a certain value, the stopping conditions can be considered to be met.

[0044] The autonomous avoidance warning method provided in this embodiment can automatically avoid the dangerous area of ​​the escalator through positioning and image data when the robot is working normally. In the event of lost positioning, it can rely on the fusion of image data and laser data to promptly and accurately issue a warning, stop the robot movement, and prevent the robot from entering the dangerous area of ​​the escalator.

[0045] Optionally, in some possible implementations, the image data and the laser data are fused to obtain the detection result of the escalator, specifically including:

[0046] fusing the laser data into corresponding frames of the image data to obtain a fused image;

[0047] The fused image is used as input to a preset detection model to determine whether there is an escalator in the fused image, and if so, determine the direction angles of the left and right boundaries of the escalator in the fused image;

[0048] Intercept the laser distance values ​​within the direction angles of the left and right boundaries, and take the minimum or median value as the rough position of the escalator;

[0049] The angle of the corresponding laser beam is used as the orientation angle of the escalator, and the orientation angle is combined with the rough position to obtain the precise orientation of the escalator.

[0050] like Figure 4 As shown, an exemplary robot orientation diagram is given. In the figure, the robot's movement direction is toward the wall and the escalator 1, but the robot turns left at this time. The left-bent dotted line represents the actual movement trajectory of the robot. It will not actually hit the wall. The robot's movement direction is not within the left and right boundary angles of the escalator, and there is no risk of entering the escalator.

[0051] Optionally, in some possible implementations, judging whether the stop running condition is met according to the semantic map configuration and the detection result, and if so, stopping the movement of the robot and giving an alarm, specifically includes:

[0052] Obtain the positioning information of the robot, and determine whether the robot is in a dangerous area based on the positioning information and semantic map configuration. If so, stop the movement and sound an alarm. If not, determine whether an escalator is detected based on the detection results. If an escalator is detected, determine whether the stopping conditions are met based on the detection results. If so, stop the movement of the robot and sound an alarm.

[0053] It should be noted that when the robot loses its positioning, or is pushed and moved by people, it may have been in a dangerous area. At this time, the positioning information can be used to determine whether it is currently in a dangerous area and stop movement in time to avoid further damage.

[0054] If no escalator is detected, the motion continues.

[0055] like Figure 3 The figure shows an exemplary stop condition judgment flow chart. Figure 3 Describe the optional judgment conditions.

[0056] Optionally, in some possible implementations, judging whether the stopping condition is met according to the detection result, and if so, stopping the movement of the robot and giving an alarm, specifically includes:

[0057] Determine whether the confidence of the detection result is greater than the preset confidence threshold. If so, determine whether there is an escalator within the left and right angle range of the detection result in the semantic map configuration. If not, process the current frame of the image data and determine whether the stop operation conditions are met based on the processing results. If so, stop the robot's movement and sound an alarm.

[0058] It should be noted that the preset confidence threshold can be set according to actual needs, for example, it can be set to 0.8.

[0059] If the confidence does not meet the threshold condition, it is considered that the distance is too far or a false detection occurs, and the "Reset All" operation is performed and the movement continues.

[0060] If the confidence meets the threshold condition, the robot's global positioning and semantic map configuration are combined to determine whether an escalator should appear in front of the robot. At this time, the robot's image detection results will be checked to see if they are consistent with the actual direction of the escalator. Figure 4 As shown in the figure, the multiple thin dashed lines emitted by the robot represent lasers, and the two thick dashed lines represent the left and right boundary directions of the escalator in the image detection result. If a certain escalator position in the semantic configuration ( Figure 4 If the dots on escalator 1 and escalator 2 in the semantic configuration are included in the left and right angle range of the detection result, the detection result is considered to be consistent with the actual direction of the escalator, the lost cache is reset, and the next conditional judgment is performed. If none of the escalators in the semantic configuration is included in the angle range of the detection result, the robot has a high probability of losing its position, then the current frame of the image data can be processed to determine whether the stop operation condition is met based on the processing result.

[0061] Optionally, in some possible implementations, the current frame of the image data is processed, and whether the stop running condition is met is determined according to the processing result. If the condition is met, the movement of the robot is stopped and an alarm is sounded, specifically including:

[0062] The current frame of the image data is inserted into the preset lost buffer. When the frame length in the lost buffer exceeds the preset length threshold, the robot positioning is considered lost, the robot movement is stopped and an alarm is sounded.

[0063] It should be noted that the preset length threshold can be set according to actual needs, for example, it can be set to 4 frames.

[0064] Optionally, in some possible embodiments, if there is an escalator within the left and right angle range of the detection result in the semantic map configuration, it is determined based on the laser data whether the laser distance is less than the first preset distance; if it is less than, it is determined whether the movement direction of the robot is within the left and right angle range of the inspection result; if it is, it is determined whether the robot is moving; if it is moving, it is determined based on the image data whether the laser distance difference between the current frame and the previous frame is less than the preset difference; if it is less than, it is determined based on the laser data whether the laser distance is less than the second preset distance; if it is less than, it is determined based on the laser data whether the laser distance is showing a decreasing trend; if it is showing a decreasing trend, the movement of the robot is stopped and an alarm is sounded.

[0065] It should be understood that the second preset distance is smaller than the first preset distance. The first preset distance and the second preset distance can be set according to actual needs, for example, the first preset distance can be 10 meters, and the second preset distance can be 2 meters.

[0066] The preset difference can be set according to actual needs, for example, it can be 500 mm.

[0067] It should be noted that when the image detection data is fused with the laser data to obtain the approximate position of the escalator, if the escalator is going down, the laser will sometimes penetrate all the way through, and the fused laser distance value will be infinite. In order to reduce the interference of abnormal data on the algorithm, it is necessary to eliminate it. By setting a first preset distance, laser frames with a distance exceeding a certain threshold are selected to be eliminated, such as 10 meters. The contents of the two caches, lost and danger, remain unchanged to cope with the sporadic nature of abnormal data.

[0068] In addition, when the robot is just passing by the edge of the escalator, the escalator may be detected due to the wide horizontal viewing angle of the camera. However, the detection results at this time should not be added to the global cache, otherwise more false alarms will occur. Figure 4 As shown in the figure, the solid straight line is the movement direction of the robot, and the dotted curve is the actual movement trajectory of the robot. It can be seen from the figure that the robot only passes through the escalator area when moving, and there is no trend of going straight to the escalator entrance, so this situation needs to be filtered out. This implementation method checks whether the movement direction of the robot is consistent with the direction detected by the image, such as Figure 4 As shown in the figure, when the actual movement direction angle of the robot is not within the left and right boundary angles of the image detection, it is considered not dangerous, the frame is skipped, and the danger cache is reset. If the image detection angle includes the movement direction, the next step of judgment is performed.

[0069] Due to the characteristics of the laser sensor, the laser transmitter will have a slight distance jitter when generating the laser beam. In this implementation, the determination of whether the robot has a tendency to move toward the escalator is mainly based on the laser distance. Therefore, in order to further reduce the interference caused by data jitter, the data obtained when the robot is stationary needs to be eliminated. If the robot does not move, the frame is skipped and the global cache remains unchanged.

[0070] Alternatively, the mobility of the robot can be obtained based on the instantaneous velocity or encoder data.

[0071] In addition, during the movement of the robot, moving obstacles such as human legs will interfere with the laser ranging. The movement of pedestrians may cause the laser distance value to fluctuate violently, which will have a great impact on the judgment algorithm. Figure 4 As shown, the small dots represent obstacles such as human legs. With the appearance of obstacles, the laser distance will drop sharply, which will affect the judgment of the escalator position. In order to reduce this interference, this embodiment will retain the laser information of the past multiple frames on the basis of calculating the laser distance of the current frame. When the difference in laser distance between the previous and next frames exceeds a certain threshold, such as 500 mm, it is considered that the laser data is disturbed by moving obstacles such as human legs and jitters occur, and the laser of this frame is skipped, and the danger cache is reset to avoid bringing the interference of human legs to the next frame.

[0072] It should be understood that under normal circumstances, after adding the virtual wall, the robot cannot reach the dangerous area of ​​the escalator, but when the robot loses its positioning, it will mistakenly enter the dangerous area. Due to the loss of positioning, the robot will be very close to the escalator. Therefore, a second preset distance can be set. If the laser distance is less than a certain threshold, such as 2 meters, it can be considered that the robot may have entered the extremely dangerous area of ​​the escalator, but only observing a single frame of data may be caused by interference from moving obstacles. Therefore, it is necessary to check the trend between the current frame laser and the past multi-frame laser distance. If the laser distance shows a decreasing trend, it is considered that the robot is walking straight towards the escalator from a distance, and is now in an extremely dangerous area, an alarm is issued and the movement stops. If the laser distance is not less than the set threshold, or there is no decreasing trend in the multi-frame laser distance, the danger cache is reset and the robot continues to move forward.

[0073] It should be noted that the above-mentioned various stop motion conditions can be added, deleted, modified and combined according to actual needs, and will not be described one by one here.

[0074] Optionally, in some possible implementations, after setting a dangerous area for each escalator, the method further includes:

[0075] Set up virtual walls based on the extent of the danger zone.

[0076] Optionally, in some possible implementations, the range of the virtual wall is greater than the range of the danger zone.

[0077] It can be understood that in some embodiments, part or all of the above-mentioned embodiments may be included.

[0078] The present invention also provides a storage medium, in which instructions are stored. When a computer reads the instructions, the computer executes the automatic escalator autonomous avoidance warning method for a robot as disclosed in any of the above embodiments.

[0079] like Figure 5 As shown, the present invention also provides an escalator autonomous avoidance warning device for a robot, comprising:

[0080] Memory 1, used for storing computer programs;

[0081] Processor 2 is used to execute a computer program to implement the automatic escalator autonomous avoidance warning method for a robot as disclosed in any of the above embodiments.

[0082] The reader should understand that in the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "examples", "specific examples", or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine different embodiments or examples described in this specification and the features of different embodiments or examples without contradiction.

[0083] In the several embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the method embodiments described above are only illustrative, for example, the division of steps is only a logical function division, and there may be other division methods in actual implementation, such as multiple steps can be combined or integrated into another step, or some features can be ignored or not executed.

[0084] If the above method is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions to enable a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the methods of each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk and other media that can store program codes.

[0085] The above are only specific embodiments of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can easily think of various equivalent modifications or replacements within the technical scope disclosed by the present invention, and these modifications or replacements should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention shall be based on the protection scope of the claims.

Claims

1. An escalator autonomous avoidance warning method for a robot, characterized in that: include: Predetermine the positions of all escalators within the robot's activity range, and set a danger zone for each escalator, which is recorded as a semantic map configuration; When the robot moves, image data and laser data of the movement direction of the robot are acquired, and the image data and the laser data are fused to obtain a detection result of the escalator; Determine whether a stop operation condition is met according to the semantic map configuration and the detection result, and if so, stop the movement of the robot and give an alarm; The image data and the laser data are fused to obtain the detection result of the escalator, which specifically includes: fusing the laser data into corresponding frames of the image data to obtain a fused image; The fused image is input into a preset detection model to determine whether there is an escalator in the fused image, and if so, determine the direction angles of the left and right boundaries of the escalator in the fused image; Intercept the laser distance values ​​within the direction angles of the left and right boundaries, and take the minimum or median value as the rough position of the escalator; The angle of the corresponding laser beam is used as the orientation angle of the escalator, and the orientation angle is merged with the rough position to obtain the precise orientation of the escalator.

2. The escalator autonomous avoidance warning method for a robot according to claim 1, characterized in that: Determining whether a stop operation condition is met according to the semantic map configuration and the detection result, and if so, stopping the movement of the robot and giving an alarm, specifically including: The positioning information of the robot is obtained, and whether the robot is in a danger zone is determined according to the positioning information and the semantic map configuration; if the robot is in the danger zone, the robot stops moving and issues an alarm; if the robot is not in the danger zone, the robot determines whether an escalator is detected according to the detection result; if an escalator is detected, the robot determines whether a stopping condition is met according to the detection result; if so, the robot stops moving and issues an alarm.

3. The escalator autonomous avoidance warning method for a robot according to claim 2, characterized in that: Determine whether the stop operation condition is met according to the detection result, and if so, stop the movement of the robot and alarm, specifically including: Determine whether the confidence of the detection result is greater than a preset confidence threshold; if so, determine whether there is an escalator in the semantic map configuration within the left and right angle range of the detection result; if not, process the current frame of the image data; determine whether the stopping condition is met based on the processing result; if so, stop the movement of the robot and sound an alarm.

4. The escalator autonomous avoidance warning method for a robot according to claim 3, characterized in that: Processing the current frame of the image data, judging whether the stop running condition is met according to the processing result, and if so, stopping the movement of the robot and giving an alarm, specifically including: The current frame of the image data is inserted into a preset lost buffer. When the frame length in the lost buffer exceeds a preset length threshold, it is determined that the robot positioning is lost, the movement of the robot is stopped and an alarm is sounded.

5. The escalator autonomous avoidance warning method for a robot according to claim 3, characterized in that: If there is an escalator within the left and right angle range of the detection result in the semantic map configuration, it is determined whether the laser distance is less than the first preset distance based on the laser data. If it is less than, it is determined whether the movement direction of the robot is within the left and right angle range of the detection result. If it is, it is determined whether the robot is moving. If it is moving, it is determined whether the difference in laser distance between the current frame and the previous frame is less than the preset difference based on the image data. If it is less than, it is determined whether the laser distance is less than the second preset distance based on the laser data. If it is less than, it is determined whether the laser distance is showing a decreasing trend based on the laser data. If it is showing a decreasing trend, the movement of the robot is stopped and an alarm is issued.

6. The escalator autonomous avoidance warning method for a robot according to any one of claims 1 to 5, characterized in that: After setting the danger zone for each escalator, the method further comprises: A virtual wall is set according to the range of the dangerous area.

7. The escalator autonomous avoidance warning method for a robot according to claim 6, characterized in that: The range of the virtual wall is larger than the range of the dangerous area.

8. A storage medium, characterized in that: The storage medium stores instructions, and when a computer reads the instructions, the computer executes the automatic escalator autonomous avoidance warning method for a robot as described in any one of claims 1 to 7.

9. An escalator autonomous avoidance warning device for a robot, characterized in that: include: Memory for storing computer programs; A processor is used to execute the computer program to implement the escalator autonomous avoidance warning method for a robot as described in any one of claims 1 to 7.

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