CN115884479B - Steering method, device and equipment of lighting lamp and storage medium - Google Patents
Steering method, device and equipment of lighting lamp and storage medium Download PDFInfo
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Abstract
The invention discloses a turning method, a device, equipment and a storage medium of a lighting lamp, wherein the method comprises the following steps: controlling a microwave radar to scan the environment to obtain a microwave signal reflected from the environment; detecting data points formed when a user moves in the environment according to the microwave signals; performing a random sample consensus operation on the data points to fit a first path formed by the movement of the user in the environment; clustering data points into a plurality of clusters along a first path; filtering out data points at edges of the plurality of clusters; fusing the filtered remaining data points in the clusters into an area formed by the movement of the user in the environment; the lighting fixture is turned so that the lighting direction of the lighting fixture is directed toward the area. The lamp control device meets the requirements of users on lamps, reduces the frequency of manual control of the lighting lamp by the users, improves the convenience of controlling the lighting lamp, and reduces the time delay of controlling the lighting lamp.
Description
Technical Field
The present invention relates to the technical field of lighting devices, and in particular, to a method, an apparatus, a device, and a storage medium for turning a lighting device.
Background
The lighting lamp is one of household appliances commonly used by users, a plurality of lighting lamps are provided with rotatable bases, the users can manually control the lighting lamp to turn according to own requirements through control modes such as a remote controller and sound control, and the operation of the control modes is complicated, so that the control delay is high.
Disclosure of Invention
The invention provides a steering method, a steering device, steering equipment and a storage medium of a lighting lamp, which are used for solving the problem of how to reduce the delay of steering control of the lighting lamp.
According to an aspect of the invention, there is provided a steering method of a lighting fixture provided with a microwave radar, the method comprising:
controlling the microwave radar to scan the environment to obtain microwave signals reflected from the environment;
detecting data points formed when a user moves in the environment according to the microwave signals;
performing a random sample consensus operation on the data points to fit a first path formed by the user's movement in the environment;
clustering the data points into a plurality of clusters along the first path;
filtering out the data points at the edges of a plurality of the clusters;
fusing the data points with the rest filtered out in the clusters into a region formed by the movement of the user in the environment;
And rotating the lighting lamp so that the lighting direction of the lighting lamp faces the area.
Optionally, the clustering the data points into a plurality of clusters along the first path includes:
configuring a target value adapted to the first path;
initializing clusters with the number of target values, wherein each cluster is provided with a center point;
calculating a first distance between the data point and each of the center points;
partitioning the data points into the clusters where the first distance is minimum;
calculating an average of the data points in each of the clusters to update the center point of the cluster;
judging whether the change amplitude of the central point in updating is smaller than or equal to a preset first threshold value or not; if not, returning to execute the calculation of the first distance between the data point and each center point; if yes, calculating a second distance between each center point and the first path;
judging whether the second distances are smaller than or equal to a preset second threshold value; if yes, determining that the cluster converges; if not, the target value is regulated, and the cluster with the initialization quantity being the target value is returned to be executed.
Optionally, the configuring the target value adapted to the first path includes:
measuring a length of the first path;
multiplying the length by a preset coefficient to obtain a reference value;
generating a path range containing the reference value;
initializing a lower limit value of the path range to a target value.
Optionally, the adjusting the target value includes:
judging whether the target value is smaller than the upper limit value of the path range; if yes, adding a preset step length on the basis of the current target value to serve as a new target value.
Optionally, said filtering out said data points at edges of a plurality of said clusters comprises:
screening two adjacent clusters from all the clusters;
connecting the center points in two adjacent clusters for each pair of two adjacent clusters to fit a second path formed by the movement of the user in the environment;
calculating a third distance between each of the data points and the second path;
judging whether the third distance is smaller than or equal to a preset third threshold value; if yes, the data points are reserved; if not, filtering the data points.
Optionally, the fusing the data points filtered out of the rest of the clusters into an area formed by the movement of the user in the environment includes:
Adding a voronoi diagram to said data points in said plurality of clusters that are filtered out of the remainder, said voronoi diagram comprising a plurality of cells, each of said cells containing one of said data points, said cells having a plurality of edges;
screening out the data points positioned at two sides of the same edge as point pairs adjacent to each other in position aiming at filtering out the rest data points in a plurality of clusters;
and connecting the vertexes into a triangular grid by taking the data points of the point pairs as vertexes so as to form a region formed by the movement of the user in the environment.
Optionally, the rotating the lighting fixture to orient the lighting direction of the lighting fixture toward the area includes:
counting the number of the data points in each cluster, which are used for filtering the rest;
screening out the n clusters with the largest quantity as target clusters;
determining a target point as the center of gravity of the region, wherein the fourth distances between the target point and the center point of each target cluster are equal;
and rotating the lighting lamp until the lighting direction of the lighting lamp coincides with the gravity center.
According to another aspect of the present invention, there is provided a steering device of a lighting fixture provided with a microwave radar, the device comprising:
The environment scanning module is used for controlling the microwave radar to scan the environment and obtaining microwave signals reflected from the environment;
the data point detection module is used for detecting data points formed when a user moves in the environment according to the microwave signals;
a path formation module for performing a random sample consensus operation on the data points to fit a first path formed by the user moving in the environment;
a point clustering module for clustering the data points into a plurality of clusters along the first path;
a point filtering module for filtering out the data points at the edges of a plurality of the clusters;
the mobile region fusion module is used for fusing the data points which are filtered and remain in the clusters into a region formed by the movement of the user in the environment;
and the lamp rotating module is used for rotating the lighting lamp so that the lighting direction of the lighting lamp faces the area.
Optionally, the point clustering module is further configured to:
configuring a target value adapted to the first path;
initializing clusters with the number of target values, wherein each cluster is provided with a center point;
calculating a first distance between the data point and each of the center points;
Partitioning the data points into the clusters where the first distance is minimum;
calculating an average of the data points in each of the clusters to update the center point of the cluster;
judging whether the change amplitude of the central point in updating is smaller than or equal to a preset first threshold value or not; if not, returning to execute the calculation of the first distance between the data point and each center point; if yes, calculating a second distance between each center point and the first path;
judging whether the second distances are smaller than or equal to a preset second threshold value; if yes, determining that the cluster converges; if not, the target value is regulated, and the cluster with the initialization quantity being the target value is returned to be executed.
Optionally, the point clustering module is further configured to:
measuring a length of the first path;
multiplying the length by a preset coefficient to obtain a reference value;
generating a path range containing the reference value;
initializing a lower limit value of the path range to a target value.
Optionally, the point clustering module is further configured to:
judging whether the target value is smaller than the upper limit value of the path range; if yes, adding a preset step length on the basis of the current target value to serve as a new target value.
Optionally, the point filtering module is further configured to:
screening two adjacent clusters from all the clusters;
connecting the center points in two adjacent clusters for each pair of two adjacent clusters to fit a second path formed by the movement of the user in the environment;
calculating a third distance between each of the data points and the second path;
judging whether the third distance is smaller than or equal to a preset third threshold value; if yes, the data points are reserved; if not, filtering the data points.
Optionally, the mobile region fusion module is further configured to:
adding a voronoi diagram to said data points in said plurality of clusters that are filtered out of the remainder, said voronoi diagram comprising a plurality of cells, each of said cells containing one of said data points, said cells having a plurality of edges;
screening out the data points positioned at two sides of the same edge as point pairs adjacent to each other in position aiming at filtering out the rest data points in a plurality of clusters;
and connecting the vertexes into a triangular grid by taking the data points of the point pairs as vertexes so as to form a region formed by the movement of the user in the environment.
Optionally, the lamp rotation module is further configured to:
counting the number of the data points in each cluster, which are used for filtering the rest;
screening out the n clusters with the largest quantity as target clusters;
determining a target point as the center of gravity of the region, wherein the fourth distances between the target point and the center point of each target cluster are equal;
and rotating the lighting lamp until the lighting direction of the lighting lamp coincides with the gravity center.
According to another aspect of the present invention, there is provided an electronic apparatus including:
at least one processor; and
a memory communicatively coupled to the at least one processor; wherein,,
the memory stores a computer program executable by the at least one processor to enable the at least one processor to perform the method of turning a lighting fixture according to any one of the embodiments of the present invention.
According to another aspect of the present invention, a computer readable storage medium is provided, which stores a computer program for causing a processor to implement the steering method of the lighting fixture according to any embodiment of the present invention when executed.
In the embodiment, controlling a microwave radar to scan the environment to obtain a microwave signal reflected from the environment; detecting data points formed when a user moves in the environment according to the microwave signals; performing a random sample consensus operation on the data points to fit a first path formed by the movement of the user in the environment; clustering data points into a plurality of clusters along a first path; filtering out data points at edges of the plurality of clusters; fusing the filtered remaining data points in the clusters into an area formed by the movement of the user in the environment; the lighting fixture is turned so that the lighting direction of the lighting fixture is directed toward the area. Under the constraint of a first path formed by fitting a user moving in the environment, a plurality of clusters are obtained for data points formed by the user moving in the environment, so that the distribution of the path formed by the user moving in the environment can be experienced to a certain extent, the area formed by the user moving in the environment is further expanded, the direction of the illumination lamp is controlled, the illumination light is provided for the user, the requirement of the user for using the lamp is met, the frequency of manually controlling the illumination lamp by the user is reduced, the convenience of controlling the illumination lamp is improved, and the delay of controlling the illumination lamp is reduced.
In addition, as the activities of the user in the environment of the building space are stable, the area formed by the movement of the user in the environment of the building space gradually tends to be stable along with time during the duration of the activities, the illumination direction of the illumination lamp belongs to a stable state within a certain time, the frequency of adjusting the illumination direction of the illumination lamp is reduced, and the interference to the user caused by frequent adjustment of the illumination direction of the illumination lamp is avoided.
It should be understood that the description in this section is not intended to identify key or critical features of the embodiments of the invention or to delineate the scope of the invention. Other features of the present invention will become apparent from the description that follows.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for the description of the embodiments will be briefly described below, and it is apparent that the drawings in the following description are only some embodiments of the present invention, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a flowchart of a method for turning a lighting fixture according to a first embodiment of the present invention;
Fig. 2 is a schematic structural diagram of a steering device of a lighting fixture according to a second embodiment of the present invention;
fig. 3 is a schematic structural diagram of an electronic device according to a third embodiment of the present invention.
Detailed Description
In order that those skilled in the art will better understand the present invention, a technical solution in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in which it is apparent that the described embodiments are only some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the present invention without making any inventive effort, shall fall within the scope of the present invention.
It should be noted that the terms "first," "second," and the like in the description and the claims of the present invention and the above figures are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that the embodiments of the invention described herein may be implemented in sequences other than those illustrated or otherwise described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
Example 1
Fig. 1 is a flowchart of a turning method of a lighting fixture according to an embodiment of the present invention, where the embodiment may be adapted to detect points formed when a user moves according to a microwave radar, and cluster the points to correspondingly control the turning situation of the lighting fixture. As shown in fig. 1, the method includes:
and 101, controlling the microwave radar to scan the environment, and obtaining a microwave signal reflected from the environment.
In this embodiment, the lighting lamp may be in the form of a desk lamp, a spotlight, etc., and may be installed in a living room, bedroom, etc. building space, where the lighting lamp is configured with a microwave radar for non-contact detection, tracking and positioning of one or more objects by electromagnetic waves, the working frequency of the microwave radar is between 3MHz and 300GHz, and the wavelength is between 100m and 1 mm.
The antenna of the microwave radar emits a microwave signal in the form of microwaves, which move at the speed of light, and when the microwave signal hits an object, the microwave signal changes and is reflected back to the microwave radar. The microwave signal arriving at the antenna of the microwave radar contains information about the detected object.
In the running process of the lighting lamp, the microwave radar can be continuously controlled to emit multi-frame microwave signals to the environment of the building space, and the microwave radar can continuously receive multi-frame original microwave signals reflected back by the environment of the building space, so that the environment of the building space is scanned.
In general, a user starts a lighting lamp in a building space, and performs activities such as reading books, watching televisions, yoga, playing games and the like by relying on light emitted by the lighting lamp, then the user is in the building space with a high probability, most of other objects except the user are static, most of the user is in dynamic state, most of limbs swing to a certain extent, and most of the whole body moves to a certain extent, so that each frame of microwave signal can be detected and tracked by taking the user as a target, and by means of a target detection network, a dynamic tracking model (such as a CV (constant velocity, long threo) model, a CA (constant acceleration) model, a first-order time correlation model (Singer model) and the like, the user in the environment of the building space can be detected, the position of the user in the coordinate system can be recorded by taking the lighting lamp (microwave radar) as an origin, and the data points formed when the user moves in the environment of the building space can be obtained.
Further, the structure of the target detection network is not limited to the artificially designed neural network, but can be optimized by a model quantization method, searched by a NAS (Neural Architecture Search, neural network structure search) method, or the like, which is not limited thereto in this embodiment.
In a specific implementation, the target detection network may be one-stage and two-stage.
two-stage belongs to the segment-to-segment, and the target detection operation is completed in two steps, wherein the first step is to use various convolutional neural networks as backbones of the target detection network, extract features from the original image data, perform rough classification (distinguishing foreground and background) and rough positioning (anchor) according to the features, and acquire candidate areas, and the second step is to classify the candidate areas (i.e. whether people exist) in a classification network of the target detection network.
Illustratively, the target detection operations of two-stage may include R-CNN (Region-CNN, region-based convolutional neural network), fast R-CNN (Fast Region convolutional neural network), fast R-CNN (Faster Region convolutional neural network), R-FCN (Region-based fully convolutional network, region-based convolutional network), and so on.
The one-stage belongs to an end-to-end type, which means that the target detection operation is completed in one step, candidate areas are not searched independently, image data are input into an integral network, and the generated detection result simultaneously contains the position and the category information of the person.
Illustratively, the one-stage object detection operation may include SSD (Single Shot Multibox Detector, single step multi-frame detection), YOLO (You Only Look Once, unified real-time object detection), and so on.
Generally, the two-stage has higher detection accuracy but slightly lower detection speed, and the one-stage has higher detection speed but slightly lower detection accuracy, so that a person skilled in the art can select one-stage or two-stage according to factors such as the resource of the self-learning detection device, the real-time requirement of detection, and the like, and the embodiment is not limited to this.
In the building space such as living room, bedroom, put furniture home appliances such as sofa, dining table and the like and household appliances such as television, air conditioner and the like, these furniture and home appliances are comparatively fixed in position, and the user relies on these furniture or avoids these furniture when moving in the environment of these building space, therefore, the user usually forms the route that has certain regularity when moving in the environment of these building space.
After a period of detection, a number of data points may be accumulated, and a RANSAC (RANdom SAmple Consensus ) operation may be performed on these data points, which may iteratively estimate parameters of a mathematical model from a set of observations (i.e., all data points) including extra-local points (i.e., data points on non-paths), thereby fitting a first path formed by a user moving in the environment of the building space.
The RANSAC is an uncertain algorithm, a reasonable result is obtained by a certain probability, the probability can be improved by improving the iteration times, the first path formed by fitting the movement of the user in the environment is used for providing a basis for clustering, the requirement on precision is low, and the requirement on delay is high, so that the iteration times can be moderately reduced to reduce the delay, and at the moment, the first path has a certain similarity with the path actually moved by the user.
Further, the basic assumption of RANSAC is:
(1) The data consists of "intra-office points";
(2) An "outlier" is data that cannot fit the model;
(3) The data in addition belongs to noise.
The reasons for the generation of the off-site points are: extreme values of noise; an erroneous measurement method; false assumptions about data.
RANSAC also makes the following assumptions: given a set of (usually small) intra-office points, there is a process by which model parameters can be estimated; and the model can be interpreted or applied to the local points.
In a specific implementation, the input to RANSAC is a set of observations (i.e., all data points), a parameterized model that can interpret or adapt to the observations, some trusted parameters.
RANSAC achieves this goal by iteratively selecting a random subset of the data. The selected subset is assumed to be an intra-office point and verified by:
1. a small set of intra-office points is randomly assumed to be initial values. A model is then fitted with the local points, the model being adapted to the assumed local points, and all unknown parameters being calculated from the assumed local points.
2. All other data were tested with the model obtained in 1 and if a point was suitable for the estimated model, it was considered to be also an intra-local point, expanding the intra-local point.
3. If there are enough points to be classified as hypothetical local points, then the estimated model is reasonable enough.
4. The model is re-estimated with all hypothesized intra-local points, since this model is estimated only at the initial hypothesized intra-local points, and needs to be updated after the subsequent expansion.
5. The model is evaluated by estimating the error rate of the local points and the model.
The whole process is iterated once, the process is repeatedly executed for fixed times, and if the model of the last time is not rejected because of too few local points; better than the existing model.
The method is limited by furniture and household appliances, the real moving path of the user is usually long and narrow, if the data points are directly aggregated into the moving range of the user, all the data points need to be accommodated in a larger range, and clusters in the larger range can cover other areas besides the real moving path of the user, so that the accuracy is low.
In this embodiment, the idea of managing the path segments and reducing the deviation can be utilized to segment the path actually moved by the user into a plurality of segments, and the data points are clustered in a local range, that is, under the limitation of the first path, the data points are clustered into a plurality of clusters respectively by using a clustering algorithm such as K-Means (K-Means), spectral clustering (Spectral Clustering), hierarchical clustering (Hierarchical Clustering), and the like, and the limitation can mean that the plurality of clusters are distributed around the first path as much as possible, so as to simulate the path actually moved by the user as much as possible.
In one embodiment of the present invention, step 104 may include the steps of:
step S41, configuring a target value adapted to the first path.
The user can perform different activities in different environments to form different paths for real movement, correspondingly, the first paths formed by fitting the movement of the user in the environments are different, and for different first paths, the target values matched with the first paths can be configured initially, wherein the target values are the number of clustered clusters, and a foundation is provided for the clustered clusters to be distributed around the first path as much as possible.
In a specific implementation, the length of the first path may be measured, and the length is multiplied by a preset coefficient to obtain the reference value, where the coefficient is usually an empirical value and belongs to a default super parameter.
And (3) taking the reference value as a midpoint, expanding a certain numerical value upwards and downwards to generate a path range containing the reference value, wherein the path range represents a reasonable range in which the number of clusters of the clusters is positioned, and initializing the lower limit value of the path range as a target value.
Step S42, initializing clusters with the number being the target value.
When clustering data points, a value of K (K is a positive integer) may be set, K clusters are initialized in a multidimensional space, each cluster has a center point, a value of the center point belongs to a variable, the values of the center points may be set randomly at first, or K points which are as far as possible from each other may be selected as the center points, or the data points may be clustered by a coarse clustering algorithm such as a hierarchical clustering algorithm or a Canopy algorithm (threshold clustering algorithm) to obtain K clusters, and then a point (such as the center point of the cluster or the closest point to the center of the cluster) is selected from each cluster as the center point.
In this embodiment, the K values belong to variables, and the selection of the K values has a significant influence on clusters of clusters, and clusters obtained from different K values are different. At the beginning, the K value can be initialized according to the condition of the first path, and then, whether the K value is adjusted or not can be determined according to the clustered clusters, and the clustering can be performed again.
Step S43, calculating a first distance between the data point and each center point.
Each cluster typically comprises a number of iterations, in each of which a first distance between a data point and a respective center point may be calculated for the respective data point and the respective cluster using euclidean distance, cosine distance, etc.
Step S44, the data points are divided into clusters with the minimum first distance.
In each iteration, each data point is traversed in turn, the first distance between the data point and the center of each cluster is compared, and the cluster with the smallest first distance is selected as the cluster to which the data point belongs, so that the data point is marked into the cluster with the smallest first distance.
In step S45, in each cluster, an average value of the data points is calculated to update the center point of the cluster.
In each iteration, each cluster is traversed in turn, and in each cluster, the average of all data points in the cluster is calculated and assigned as the new value for the center point of the cluster.
Step S46, judging whether the change amplitude of the central point in updating is smaller than or equal to a preset first threshold value; if not, returning to the execution step S43; if yes, go to step S47.
For the same cluster, the difference between the center point before updating and the center point after updating can be calculated as the change amplitude at the time of updating, and the change amplitude at the time of updating is compared with a preset first threshold value.
If the magnitude of change at the time of update is less than or equal to the first threshold, indicating that the change in the center point update is small, the cluster convergence of this cluster can be confirmed.
If the change amplitude in updating is larger than the first threshold, the change of the updating of the central point is larger, the cluster of the cluster at the time can be confirmed to be not converged, the next iteration is carried out, and the steps S43-S46 are re-executed until the cluster of the cluster at the time is converged.
Step S47, calculating a second distance between each center point and the first path.
Upon convergence of the clusters of this cluster, each center point may be projected onto the first path in order to calculate a second distance (e.g., euclidean distance) between each center point and the first path.
Step S48, judging whether the second distances are smaller than or equal to a preset second threshold value; if yes, go to step S49; if not, step S50 is performed.
Step S49, determining cluster convergence.
Step S50, adjusting the target value, and returning to step S42.
At the end of each iteration, a second distance between each center point and the first path is compared with a preset second threshold.
If all the second distances are smaller than or equal to the second threshold value, the clusters are close to the first path, and each cluster is distributed on the first path because the clusters are not overlapped, so that the end of clustering can be confirmed, and each cluster is converged.
If the at least one second distance is greater than the second threshold value, the at least one cluster is far away from the first path, and each cluster is not distributed on the first path, at this time, the target value is readjusted, so as to adjust the K value, the next clustering is performed, and the steps S42-S48 are re-performed until the clustering is finished.
For example, if the previously initialized target value is the lower limit value of the path range, it may be determined whether the target value is smaller than the upper limit value of the path range when the target value is adjusted; if yes, adding a preset step length (such as 1) on the basis of the current target value to serve as a new target value.
Typically, a user's activity has an aggregate nature, i.e., data points that the user forms during the activity are aggregated together, but may form sparse data points that may be scattered across locations due to other factors (e.g., pickup, drinking, other user traffic, etc.).
In this embodiment, in order to reduce the influence of sparse data points, the data points at the edges of a plurality of clusters may be filtered out with the distribution of each cluster as a reference.
In a specific implementation, two adjacent clusters in position can be screened out from all clusters, central points in the two adjacent clusters are connected for each pair of the two adjacent clusters so as to fit a second path formed by the movement of a user in the environment (namely, a line segment formed after the central points are connected in sequence), the central points of the adjacent clusters are connected in sequence to obtain the second path, the correction of the first path is performed, the situation of more real user activities can be simulated, and the similarity between the paths and the paths actually moved by the user is improved.
Each data point is projected onto the second path to calculate a third distance (e.g., euclidean distance) between each data point and the second path.
Judging whether the third distance is smaller than or equal to a preset third threshold value; if so, the data point can be kept close to the second path, i.e. the data point is left unfiltered; if not, the data point is far from the second path, and belongs to the edge of a certain cluster, and the data point can be filtered.
And 106, fusing the filtered remaining data points in the clusters into an area formed by the movement of the user in the environment.
For filtering out the remaining data points in multiple clusters, geometric algorithms (such as minenclosingtriange () function, minEnclosingCircle () function, etc. in OpenCV (a cross-platform computer vision and machine learning software library) may be used to fit the data points to areas of regular or irregular shape as areas formed by the user's movement in the environment of the building space.
In one example, a Voronoi diagram (Voronoi diagram), also known as a taisen polygon or Dirichlet diagram, is added to the filtered remaining data points in the plurality of clusters, which comprises a set of consecutive polygons (also known as cell cells) made up of perpendicular bisectors connecting two adjacent point lines, i.e., the Voronoi diagram comprises a plurality of cells, each cell containing one data point, the cells having a plurality of edges.
In the voronoi diagram, the euclidean distance between any two face key points p and q is denoted as dist (p, q).
Let p= { P 1 , p 2 ,…,p n And is any n distinct data points on the plane, i.e., the base points. The so-called P-corresponding Voronoi diagram is a sub-region division of a plane-the whole plane is thus divided into n cells, which have the property:
Any data point q is located at data point p i Corresponding toIn a unit if and only if for any p j ∈P j J.noteq.i, all have dist (q, p i )＜dist(q, p j ). At this time, the Voronoi diagram corresponding to P is referred to as Vor (P).
"Vor (P)" or "Voronoi diagram" indicates the edges and vertices that make up the sub-region division. In Vor (P), with base point P i The corresponding cell is denoted as V (p i ) Called AND p i Corresponding Voronoi cells.
Then, aiming at filtering out the rest data points in a plurality of clusters, screening out the data points positioned at two sides of the same edge as the adjacent point pairs; the data points of the point pairs are used as vertexes, and the vertexes are connected into a triangular grid to form an area formed by the movement of a user in the environment in the building space.
In this example, the area formed by the user moving in the environment in the building space is drawn in the form of triangle mesh, and an API (Application Programming Interface ) for rendering 2D (two-dimensional) vector graphics or a rendering engine can be applied to implement hardware acceleration and reduce latency.
In general, activities performed by a user in the environment of a building space are relatively stable, and an area formed by the movement of the user in the environment of the building space gradually tends to be stable with time during the duration of the activities.
In this embodiment, the lighting fixture is provided with a rotatable mounting seat (especially a cradle head), when the area formed by the movement of the user in the environment of the building space is stable, the mounting seat (especially the cradle head) can be driven to rotate, so as to drive the lighting fixture (especially the bulb) to rotate, so that the lighting direction of the lighting fixture (i.e. the direction of the light emitted by the bulb) faces the area formed by the movement of the user in the environment of the building space, the lighting range of the lighting fixture is at least partially overlapped with the area formed by the movement of the user in the environment of the building space, and light is provided for the activities performed by the user in the environment of the building space.
The area formed by the movement of the user in the environment of the building space can be in a regular or irregular shape, the bulbs of the lighting fixtures are different in number and arrangement, the lighting fixtures are provided with light-transmitting or light-non-transmitting lamp covers, and the factors influence the relationship between the lighting direction of the lighting fixtures and the area formed by the movement of the user in the environment of the building space to a certain extent, so that the lighting fixtures can be driven to rotate according to the factors, and the lighting direction of the lighting fixtures faces the area.
For the area with a regular state and a smaller area, a point with geometric meaning such as the center, the gravity center and the like can be searched from the area, and the lighting lamp is rotated so that the lighting direction of the lighting lamp coincides with the point, so that light is comprehensively provided for activities performed by a user in the environment of a building space.
For the area with a larger area in an irregular state, the number of data points which are remained in each cluster can be counted, n clusters with the largest number (n is a positive integer) are screened out and used as target clusters, the number of the data points in a single cluster can reflect the intensity of the user activity to a certain extent, and then the target clusters are usually local parts with denser user activity.
And determining a target point, wherein the target point is used as the center of gravity of the area, and the fourth distances between the target point and the center points of all target clusters are equal, so that the center of gravity is the center of gravity of the activities of the user, and at the moment, the illumination lamp can be rotated until the illumination direction of the illumination lamp coincides with the center of gravity, so that the maximum light is provided for the local areas where the activities of the user in the environment of the building space are denser as much as possible.
In the embodiment, controlling a microwave radar to scan the environment to obtain a microwave signal reflected from the environment; detecting data points formed when a user moves in the environment according to the microwave signals; performing a random sample consensus operation on the data points to fit a first path formed by the movement of the user in the environment; clustering data points into a plurality of clusters along a first path; filtering out data points at edges of the plurality of clusters; fusing the filtered remaining data points in the clusters into an area formed by the movement of the user in the environment; the lighting fixture is turned so that the lighting direction of the lighting fixture is directed toward the area. Under the constraint of a first path formed by fitting a user moving in the environment, a plurality of clusters are obtained for data points formed by the user moving in the environment, so that the distribution of the path formed by the user moving in the environment can be experienced to a certain extent, the area formed by the user moving in the environment is further expanded, the direction of the illumination lamp is controlled, the illumination light is provided for the user, the requirement of the user for using the lamp is met, the frequency of manually controlling the illumination lamp by the user is reduced, the convenience of controlling the illumination lamp is improved, and the delay of controlling the illumination lamp is reduced.
In addition, as the activities of the user in the environment of the building space are stable, the area formed by the movement of the user in the environment of the building space gradually tends to be stable along with time during the duration of the activities, the illumination direction of the illumination lamp belongs to a stable state within a certain time, the frequency of adjusting the illumination direction of the illumination lamp is reduced, and the interference to the user caused by frequent adjustment of the illumination direction of the illumination lamp is avoided.
Example two
Fig. 2 is a schematic structural diagram of a steering device of a lighting fixture according to a second embodiment of the present invention, where the lighting fixture is provided with a microwave radar, and the device includes:
an environment scanning module 201, configured to control the microwave radar to scan an environment, and obtain a microwave signal reflected from the environment;
a data point detection module 202 for detecting data points formed when a user moves in the environment according to the microwave signal;
a path formation module 203 for performing a random sample consensus operation on the data points to fit a first path formed by the user moving in the environment;
a point clustering module 204 for clustering the data points into a plurality of clusters along the first path;
A point filtering module 205 for filtering out the data points at the edges of a plurality of the clusters;
a moving region fusing module 206, configured to fuse the data points filtered out and remaining in the clusters into a region formed by the user moving in the environment;
a lamp rotation module 207 for rotating the lighting lamp such that the lighting direction of the lighting lamp is directed towards the area.
In one embodiment of the present invention, the point clustering module 204 is further configured to:
configuring a target value adapted to the first path;
initializing clusters with the number of target values, wherein each cluster is provided with a center point;
calculating a first distance between the data point and each of the center points;
partitioning the data points into the clusters where the first distance is minimum;
calculating an average of the data points in each of the clusters to update the center point of the cluster;
judging whether the change amplitude of the central point in updating is smaller than or equal to a preset first threshold value or not; if not, returning to execute the calculation of the first distance between the data point and each center point; if yes, calculating a second distance between each center point and the first path;
Judging whether the second distances are smaller than or equal to a preset second threshold value; if yes, determining that the cluster converges; if not, the target value is regulated, and the cluster with the initialization quantity being the target value is returned to be executed.
In one embodiment of the present invention, the point clustering module 204 is further configured to:
measuring a length of the first path;
multiplying the length by a preset coefficient to obtain a reference value;
generating a path range containing the reference value;
initializing a lower limit value of the path range to a target value.
In one embodiment of the present invention, the point clustering module 204 is further configured to:
judging whether the target value is smaller than the upper limit value of the path range; if yes, adding a preset step length on the basis of the current target value to serve as a new target value.
In one embodiment of the present invention, the point filtering module 205 is further configured to:
screening two adjacent clusters from all the clusters;
connecting the center points in two adjacent clusters for each pair of two adjacent clusters to fit a second path formed by the movement of the user in the environment;
calculating a third distance between each of the data points and the second path;
Judging whether the third distance is smaller than or equal to a preset third threshold value; if yes, the data points are reserved; if not, filtering the data points.
In one embodiment of the present invention, the mobile zone fusion module 206 is further configured to:
adding a voronoi diagram to said data points in said plurality of clusters that are filtered out of the remainder, said voronoi diagram comprising a plurality of cells, each of said cells containing one of said data points, said cells having a plurality of edges;
screening out the data points positioned at two sides of the same edge as point pairs adjacent to each other in position aiming at filtering out the rest data points in a plurality of clusters;
and connecting the vertexes into a triangular grid by taking the data points of the point pairs as vertexes so as to form a region formed by the movement of the user in the environment.
In one embodiment of the invention, the fixture rotation module 207 is further configured to:
counting the number of the data points in each cluster, which are used for filtering the rest;
screening out the n clusters with the largest quantity as target clusters;
determining a target point as the center of gravity of the region, wherein the fourth distances between the target point and the center point of each target cluster are equal;
And rotating the lighting lamp until the lighting direction of the lighting lamp coincides with the gravity center.
The steering device of the lighting lamp provided by the embodiment of the invention can execute the steering method of the lighting lamp provided by any embodiment of the invention, and has the corresponding functional modules and beneficial effects of executing the steering method of the lighting lamp.
Example III
Fig. 3 shows a schematic diagram of the structure of an electronic device 10 that may be used to implement an embodiment of the invention. Electronic devices are intended to represent various forms of digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. Electronic equipment may also represent various forms of mobile devices, such as personal digital processing, cellular telephones, smartphones, wearable devices (e.g., helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are meant to be exemplary only, and are not meant to limit implementations of the inventions described and/or claimed herein.
As shown in fig. 3, the electronic device 10 includes at least one processor 11, and a memory, such as a Read Only Memory (ROM) 12, a Random Access Memory (RAM) 13, etc., communicatively connected to the at least one processor 11, in which the memory stores a computer program executable by the at least one processor, and the processor 11 may perform various appropriate actions and processes according to the computer program stored in the Read Only Memory (ROM) 12 or the computer program loaded from the storage unit 18 into the Random Access Memory (RAM) 13. In the RAM 13, various programs and data required for the operation of the electronic device 10 may also be stored. The processor 11, the ROM 12 and the RAM 13 are connected to each other via a bus 14. An input/output (I/O) interface 15 is also connected to bus 14.
Various components in the electronic device 10 are connected to the I/O interface 15, including: an input unit 16 such as a keyboard, a mouse, etc.; an output unit 17 such as various types of displays, speakers, and the like; a storage unit 18 such as a magnetic disk, an optical disk, or the like; and a communication unit 19 such as a network card, modem, wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information/data with other devices via a computer network, such as the internet, and/or various telecommunication networks.
The processor 11 may be a variety of general and/or special purpose processing components having processing and computing capabilities. Some examples of processor 11 include, but are not limited to, a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), various specialized Artificial Intelligence (AI) computing chips, various processors running machine learning model algorithms, digital Signal Processors (DSPs), and any suitable processor, controller, microcontroller, etc. The processor 11 performs the various methods and processes described above, such as the turning method of the lighting fixture.
In some embodiments, the method of steering a lighting fixture may be implemented as a computer program tangibly embodied on a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program may be loaded and/or installed onto the electronic device 10 via the ROM 12 and/or the communication unit 19. When the computer program is loaded into the RAM 13 and executed by the processor 11, one or more steps of the above-described method of steering a lighting fixture may be performed. Alternatively, in other embodiments, the processor 11 may be configured to perform the method of steering the lighting fixture by any other suitable means (e.g. by means of firmware).
Various implementations of the systems and techniques described here above may be implemented in digital electronic circuitry, integrated circuit systems, field Programmable Gate Arrays (FPGAs), application Specific Integrated Circuits (ASICs), application Specific Standard Products (ASSPs), systems On Chip (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and/or combinations thereof. These various embodiments may include: implemented in one or more computer programs, the one or more computer programs may be executed and/or interpreted on a programmable system including at least one programmable processor, which may be a special purpose or general-purpose programmable processor, that may receive data and instructions from, and transmit data and instructions to, a storage system, at least one input device, and at least one output device.
A computer program for carrying out methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus, such that the computer programs, when executed by the processor, cause the functions/acts specified in the flowchart and/or block diagram block or blocks to be implemented. The computer program may execute entirely on the machine, partly on the machine, as a stand-alone software package, partly on the machine and partly on a remote machine or entirely on the remote machine or server.
In the context of the present invention, a computer-readable storage medium may be a tangible medium that can contain, or store a computer program for use by or in connection with an instruction execution system, apparatus, or device. The computer readable storage medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. Alternatively, the computer readable storage medium may be a machine readable signal medium. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
To provide for interaction with a user, the systems and techniques described here can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to a user; and a keyboard and a pointing device (e.g., a mouse or a trackball) through which a user can provide input to the electronic device. Other kinds of devices may also be used to provide for interaction with a user; for example, feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form, including acoustic input, speech input, or tactile input.
The systems and techniques described here can be implemented in a computing system that includes a background component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front-end component (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such background, middleware, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: local Area Networks (LANs), wide Area Networks (WANs), blockchain networks, and the internet.
The computing system may include clients and servers. The client and server are typically remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. The server can be a cloud server, also called a cloud computing server or a cloud host, and is a host product in a cloud computing service system, so that the defects of high management difficulty and weak service expansibility in the traditional physical hosts and VPS service are overcome.
Example IV
Embodiments of the invention also provide a computer program product comprising a computer program which, when executed by a processor, implements a method of steering a lighting fixture as provided by any of the embodiments of the invention.
Computer program product in the implementation, the computer program code for carrying out operations of the present invention may be written in one or more programming languages, including an object oriented programming language such as Java, smalltalk, C ++ and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to an external computer (for example, through the Internet using an Internet service provider).
It should be appreciated that various forms of the flows shown above may be used to reorder, add, or delete steps. For example, the steps described in the present invention may be performed in parallel, sequentially, or in a different order, so long as the desired results of the technical solution of the present invention are achieved, and the present invention is not limited herein.
The above embodiments do not limit the scope of the present invention. It will be apparent to those skilled in the art that various modifications, combinations, sub-combinations and alternatives are possible, depending on design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the scope of the present invention.
Claims (10)
1. A method of steering a lighting fixture, the lighting fixture being provided with a microwave radar, the method comprising:
controlling the microwave radar to scan the environment to obtain microwave signals reflected from the environment;
detecting data points formed when a user moves in the environment according to the microwave signals;
performing a random sample consensus operation on the data points to fit a first path formed by the user's movement in the environment;
Clustering the data points into a plurality of clusters along the first path;
filtering out the data points at the edges of a plurality of the clusters;
fusing the data points with the rest filtered out in the clusters into a region formed by the movement of the user in the environment;
and rotating the lighting lamp so that the lighting direction of the lighting lamp faces the area.
2. The method of claim 1, wherein the clustering the data points into a plurality of clusters along the first path comprises:
configuring a target value adapted to the first path;
initializing clusters with the number of target values, wherein each cluster is provided with a center point;
calculating a first distance between the data point and each of the center points;
partitioning the data points into the clusters where the first distance is minimum;
calculating an average of the data points in each of the clusters to update the center point of the cluster;
judging whether the change amplitude of the central point in updating is smaller than or equal to a preset first threshold value or not; if not, returning to execute the calculation of the first distance between the data point and each center point; if yes, calculating a second distance between each center point and the first path;
Judging whether the second distances are smaller than or equal to a preset second threshold value; if yes, determining that the cluster converges; if not, the target value is regulated, and the cluster with the initialization quantity being the target value is returned to be executed.
3. The method of claim 2, wherein the configuring the target value for adaptation to the first path comprises:
measuring a length of the first path;
multiplying the length by a preset coefficient to obtain a reference value;
generating a path range containing the reference value;
initializing a lower limit value of the path range to a target value.
4. A method according to claim 3, wherein said adjusting said target value comprises:
judging whether the target value is smaller than the upper limit value of the path range; if yes, adding a preset step length on the basis of the current target value to serve as a new target value.
5. The method of claim 2, wherein said filtering out said data points at edges of a plurality of said clusters comprises:
screening two adjacent clusters from all the clusters;
connecting the center points in two adjacent clusters for each pair of two adjacent clusters to fit a second path formed by the movement of the user in the environment;
Calculating a third distance between each of the data points and the second path;
judging whether the third distance is smaller than or equal to a preset third threshold value; if yes, the data points are reserved; if not, filtering the data points.
6. The method of any of claims 1-5, wherein the fusing the data points remaining from the filtering in the plurality of clusters into an area formed by the user moving in the environment comprises:
adding a voronoi diagram to said data points in said plurality of clusters that are filtered out of the remainder, said voronoi diagram comprising a plurality of cells, each of said cells containing one of said data points, said cells having a plurality of edges;
screening out the data points positioned at two sides of the same edge as point pairs adjacent to each other in position aiming at filtering out the rest data points in a plurality of clusters;
and connecting the vertexes into a triangular grid by taking the data points of the point pairs as vertexes so as to form a region formed by the movement of the user in the environment.
7. The method of any one of claims 1-5, wherein the rotating the light fixture to orient a lighting direction of the light fixture toward the area comprises:
Counting the number of the data points in each cluster, which are used for filtering the rest;
screening out the n clusters with the largest quantity as target clusters;
determining a target point as the center of gravity of the region, wherein the fourth distances between the target point and the center point of each target cluster are equal;
and rotating the lighting lamp until the lighting direction of the lighting lamp coincides with the gravity center.
8. A steering device for a lighting fixture, the lighting fixture being provided with a microwave radar, the device comprising:
the environment scanning module is used for controlling the microwave radar to scan the environment and obtaining microwave signals reflected from the environment;
the data point detection module is used for detecting data points formed when a user moves in the environment according to the microwave signals;
a path formation module for performing a random sample consensus operation on the data points to fit a first path formed by the user moving in the environment;
a point clustering module for clustering the data points into a plurality of clusters along the first path;
a point filtering module for filtering out the data points at the edges of a plurality of the clusters;
the mobile region fusion module is used for fusing the data points which are filtered and remain in the clusters into a region formed by the movement of the user in the environment;
And the lamp rotating module is used for rotating the lighting lamp so that the lighting direction of the lighting lamp faces the area.
9. An electronic device, the electronic device comprising:
at least one processor; and
a memory communicatively coupled to the at least one processor; wherein,,
the memory stores a computer program executable by the at least one processor to enable the at least one processor to perform the method of turning a lighting fixture of any one of claims 1-7.
10. A computer readable storage medium, characterized in that the computer readable storage medium stores a computer program for causing a processor to implement the steering method of a lighting fixture as claimed in any one of claims 1-7 when executed.
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| US20180340788A1 (en) * | 2015-10-19 | 2018-11-29 | Nokia Technologies Oy | A navigation apparatus and associated methods |
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| CN107719347A (en) * | 2017-09-30 | 2018-02-23 | 北京小米移动软件有限公司 | Portable lighting method, apparatus and storage medium |
| CN111372363A (en) * | 2020-04-09 | 2020-07-03 | 珠海格力电器股份有限公司 | Control method and device of lamp, storage medium and lamp |
| WO2022142948A1 (en) * | 2020-12-29 | 2022-07-07 | 深圳市普渡科技有限公司 | Dynamic target tracking and positioning method and apparatus, and device and storage medium |
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