Patent Application
20190031469
Apparatuses, methods, and devices consistent with the present disclosure relate to the field of robots, and in particular, to a story monitoring method when a robot takes an elevator, an electronic device, and a computer storage medium.
With the development of intelligent navigation, more robots are developed. When performing indoor autonomous navigation, a robot usually needs to take an elevator to go to another story. After entering the elevator, the robot needs to record a story that the elevator is on, so as to prepare for an operation of exiting the elevator subsequently. In conventional art, the robot communicates with the elevator by using Bluetooth or another communications module, and invokes a current location interface of the elevator, to obtain current location information of the elevator. However, to implement this manner, a communications device or the like needs to be installed in the elevator. For an elevator in which a communications device is not installed, communication cannot be performed. Consequently, information of a story that the elevator is on cannot be obtained.
According to one or more exemplary embodiments of this application, a story monitoring method when a robot takes an elevator and an electronic device are provided.
According to one or more exemplary embodiments, a story monitoring method when a robot takes an elevator, including:
obtaining gravity acceleration of a robot in a static state in an elevator and transient acceleration of the robot in a moving state in the elevator, a starting story number, and a story height of each story;
subtracting the gravity acceleration of the robot in the static state from the transient acceleration of the robot in the moving state to obtain an acceleration change waveform of the robot;
comparing the acceleration change waveform by using an acceleration waveform classifier of the elevator, to obtain an acceleration waveform classifier to which the acceleration change waveform belongs, obtaining a configured state machine and a conversion relationship between different movement statuses in the state machine, determining a moving direction of the elevator according to the conversion relationship and a next acceleration waveform classifier adjacent to an acceleration static waveform classifier, and obtaining a movement status of the elevator at each moment according to a correspondence between the acceleration waveform classifier and a movement status of the elevator and the moving direction of the elevator;
obtaining transient acceleration and a total time of the elevator in a complete movement status, obtaining an instantaneous speed of the elevator according to the transient acceleration, and then obtaining actual displacement of the elevator according to the instantaneous speed and the total time of the elevator, the complete movement status including a process of a static state, to an accelerating state, to a uniform speed state, to a decelerating state, and to a static state; and
obtaining a story that the elevator is on after a complete movement status according to the actual displacement of the elevator, the starting story number, and the story height of each story.
According to one or more exemplary embodiments, a story monitoring apparatus when a robot takes an elevator, including:
a data obtaining module configured to obtain gravity acceleration of a robot in a static state in an elevator and transient acceleration of the robot in a moving state in the elevator, a starting story number, and a story height of each story;
an estimation module configured to subtract the gravity acceleration of the robot in the static state from the transient acceleration of the robot in the moving state to obtain an acceleration change waveform of the robot;
a status detection module configured to: compare the acceleration change waveform by using an acceleration waveform classifier of the elevator, to obtain an acceleration waveform classifier to which the acceleration change waveform belongs, obtain a configured state machine and a conversion relationship between different movement statuses in the state machine, determine a moving direction of the elevator according to the conversion relationship and a next acceleration waveform classifier adjacent to an acceleration static waveform classifier, and obtain a movement status of the elevator at each moment according to a correspondence between the acceleration waveform classifier and a movement status of the elevator and the moving direction of the elevator;
a displacement calculation module configured to: obtain transient acceleration and a total time of the elevator in a complete movement status, obtain an instantaneous speed of the elevator according to the transient acceleration, and then obtain actual displacement of the elevator according to the instantaneous speed and the total time of the elevator, the complete movement status including a process from a static state, to an accelerating state, to a uniform speed state, to a decelerating state, and to a static state; and
a story monitoring module configured to obtain a story that the elevator is on after a complete movement status according to the actual displacement of the elevator, the starting story number, and the story height of each story.
Details of one or more embodiments of the present disclosure are provided in the following accompanying drawings and descriptions. Other features, objectives, and advantages of the present disclosure become clear in the specification, the accompanying drawings, and the claims.
To describe the technical solutions in the embodiments of the present disclosure or in the existing technology more clearly, the following briefly describes the accompanying drawings required for describing the embodiments or the existing technology. Apparently, the accompanying drawings in the following description show merely some embodiments of the present disclosure, and a person of ordinary skill in the art may still derive other drawings from these accompanying drawings without creative efforts.
To make the objectives, technical solutions, and advantages of the present disclosure clearer and more comprehensible, the following further describes the present disclosure in detail with reference to the accompanying drawings and exemplary embodiments. It should be understood that the specific embodiments described herein are merely used to explain the present disclosure but are not intended to limit the present disclosure.
It can be understood that, terms such as “a first” and “a second” used in the present disclosure may be used to describe various components, but the components are not limited by the terms. The terms are merely intended for distinguishing the first component from another component. For example, without departing from the scope of the present disclosure, a first client may be referred to as a second client, and similarly, a second client may be referred to as a first client. The first client and the second client are both clients, but are not a same client.
Step 302: Obtain gravity acceleration of a robot in a static state in an elevator and transient acceleration of the robot in a moving state in the elevator, a starting story number, and a story height of each story.
In this exemplary embodiment, the acceleration sensor in the robot can detect transient acceleration of the robot on an axis z when the robot is in the moving state as the elevator moves. Acceleration of the robot on three axes x, y, and z may be obtained by using the acceleration sensor. The starting story number may be set by a user of the robot. For example, if the robot is on the third story when starting to take the elevator, the starting story number of the robot is set to 3. For the story height of each story, the robot may be placed in the elevator in advance, and the elevator stops on each story when moving, to calculate displacement and record the story height of each story.
The gravity acceleration of the robot in the static state may be obtained by calculating an average gravity acceleration value of multiple gravity acceleration values of the robot in the static state in the elevator that are detected by using the acceleration sensor of the robot. The average gravity acceleration value is used as the gravity acceleration of the robot in the static state.
In an exemplary embodiment, the story monitoring method when a robot takes an elevator is applied to the electronic device shown in
In this exemplary embodiment, a transient acceleration value of the robot in the moving state is detected by using the acceleration sensor of the robot.
In an exemplary embodiment, the story monitoring method when a robot takes an elevator is applied to the electronic device shown in
In this exemplary embodiment, the step of comparing the acceleration change waveform by using an acceleration waveform classifier of the elevator, to obtain an acceleration waveform classifier to which the acceleration change waveform belongs includes: comparing a waveform of the acceleration waveform classifier of the elevator with the acceleration change waveform; obtaining a waveform of the acceleration waveform classifier whose distance to the acceleration change waveform is the shortest; and using the acceleration waveform classifier whose distance is the shortest as the acceleration waveform classifier to which the acceleration change waveform belongs.
Specifically, the acceleration waveform classifier of the elevator is an acceleration waveform classifier obtained by performing training on acceleration waveform data that is prerecorded when the robot is in the elevator during ascending and descending.
A speed status in the configured state machine includes: being static, ascending at an accelerating speed, ascending at a uniform speed, ascending at a decelerating speed, descending at an accelerating speed, descending at a uniform speed, and descending at a decelerating speed; and the conversion relationship between the different statuses includes conversion between adjacent movement statuses from being static, to ascending at an accelerating speed, to ascending at a uniform speed, and to ascending at a decelerating speed, and conversion between adjacent movement statuses from being static, to descending at an accelerating speed, to descending at a uniform speed, and to descending at a decelerating speed, as shown in
An obtained next acceleration waveform classifier adjacent to an acceleration static waveform classifier is DOWN_START, DOWN_BEING, and DOWN_END. According to the conversion relationship between different movement statuses in the state machine of the elevator, being static can convert only to descending at an accelerating speed or ascending at an accelerating speed. Therefore, the next acceleration waveform classifier adjacent to the static waveform classifier is DOWN_START, DOWN_BEING, and DOWN_END, and the moving direction of the elevator is downward.
An obtained next acceleration waveform classifier adjacent to an acceleration static waveform classifier is UP_START, UP_BEING, and UP_END. According to the conversion relationship between different movement statuses in the state machine of the elevator, being static can convert only to descending at an accelerating speed or ascending at an accelerating speed. Therefore, the next acceleration waveform classifier adjacent to the static waveform classifier is UP_START, UP_BEING, and UP_END, and the moving direction of the elevator is upward.
Referring back to
In this exemplary embodiment, according to the acceleration law vi=v0+at, the instantaneous speed of the elevator may be calculated by means of an initial speed, the transient acceleration, and a time period, and then the actual displacement of the elevator is calculated according to a relationship s=∫vidt between a speed and displacement. The movement status refers to a speed status.
Referring back to
In this exemplary embodiment, the story that the elevator is on is obtained according to the actual displacement s of the elevator, the starting story number n, and the story height of each story.
According to the foregoing story monitoring method when a robot takes an elevator, gravity acceleration of the robot in a static state in the elevator and transient acceleration of the robot in a moving state in the elevator are obtained, to obtain an acceleration change waveform; an acceleration waveform classifier of the elevator is used to compare the acceleration change waveform, to obtain an acceleration waveform classifier to which the acceleration change waveform belongs; a movement status of the elevator at each moment is obtained according to a correspondence between the acceleration waveform classifier and a movement status of the elevator; and then transient acceleration and a total time of the elevator in a complete movement status are obtained, to calculate the actual displacement. The story that the elevator is on, that is, the story that the robot is on, is obtained according to the actual displacement, the starting story number, and the story height of each story, thereby implementing monitoring stories that the robot is on when the robot takes various elevators.
In an exemplary embodiment, before the obtaining gravity acceleration of a robot in a static state in an elevator and transient acceleration of the robot in a moving state, a starting story number, and a story height of each story, the foregoing story monitoring method when a robot takes an elevator further includes: placing the robot in the elevator, and recording an acceleration waveform of the elevator during ascending and descending; cutting the recorded acceleration waveform into multiple different acceleration state sample training sets; cutting the recorded acceleration waveform into multiple different acceleration state sample training sets; and obtaining displacement of each story, and marking the story height of each story.
In this exemplary embodiment, the acceleration waveform is cut into seven different acceleration state sample training sets. The acceleration waveform classifier is obtained by training samples in the sample training sets by means of linear regression. In a process of obtaining a story height of each story, each time the elevator moves to a story, the elevator stops to record displacement of the story, to obtain the story height of each story.
According to one or more exemplary embodiments, a status in a state machine configured for an elevator includes: being static, ascending at an accelerating speed, ascending at a uniform speed, ascending at a decelerating speed, descending at an accelerating speed, descending at a uniform speed, and descending at a decelerating speed. A conversion relationship between the different movement statuses includes conversion between adjacent movement statuses from being static, to ascending at an accelerating speed, to ascending at a uniform speed, and to ascending at a decelerating speed, and conversion between adjacent movement statuses from being static, to descending at an accelerating speed, to descending at a uniform speed, and to descending at a decelerating speed. During ascending, being static can convert only to ascending at an accelerating speed, ascending at an accelerating speed converts to ascending at a uniform speed, ascending at a uniform speed converts to ascending at a decelerating speed, and ascending at a decelerating speed converts to being static. During descending, being static can convert only to descending at an accelerating speed, descending at an accelerating speed converts to descending at a uniform speed, descending at a uniform speed converts to descending at a decelerating speed, and descending at a decelerating speed converts to being static. As shown in
A correspondence between the acceleration waveform classifiers and movement statuses of the elevator may be:
Descending at an accelerating speed corresponds to DOWN_START, DOWN_BEING, and DOWN_END.
Descending at a uniform speed corresponds to NORMAL_BEING.
Descending at a decelerating speed corresponds to UP_START, UP_BEING, and UP_END.
Ascending at an accelerating speed corresponds to UP_START, UP_BEING, and UP_END.
Ascending at a uniform speed corresponds to NORMAL_BEING.
Ascending at a decelerating speed corresponds to DOWN_START, DOWN_BEING, and DOWN_END.
Being static corresponds to NORMAL_BEING.
An acceleration change waveform is classified according to an acceleration waveform classifier, to obtain an acceleration waveform classifier to which the acceleration change waveform belongs. Different acceleration waveform classifiers to which different acceleration change waveforms belong are compared according to the correspondence between movement statuses and acceleration classifiers, to obtain corresponding movement statuses.
In an exemplary embodiment, after the step of comparing the acceleration change waveform by using an acceleration waveform classifier of the elevator, to obtain an acceleration waveform classifier to which the acceleration change waveform belongs, and a movement status of the elevator at each moment according to a correspondence between the acceleration waveform classifier and a movement status of the elevator, the story monitoring method when a robot takes an elevator further includes: detecting whether the movement status of the elevator at each moment satisfies a conversion relationship between different configured states; and if the conversion relationship between different configured movement statuses is satisfied, converting, by the movement status of the elevator, from a movement status in the configured state machine to a next movement status.
A speed status in the configured state machine includes: being static, ascending at an accelerating speed, ascending at a uniform speed, ascending at a decelerating speed, descending at an accelerating speed, descending at a uniform speed, and descending at a decelerating speed; and the conversion relationship between the different statuses includes conversion between adjacent movement statuses from being static, to ascending at an accelerating speed, to ascending at a uniform speed, and to ascending at a decelerating speed, and conversion between adjacent movement statuses from being static, to descending at an accelerating speed, to descending at a uniform speed, and to descending at a decelerating speed.
In this exemplary embodiment, for the conversion relationship between the configured different statuses, for example, descending at a uniform speed can convert only to descending at a decelerating speed, and cannot convert to being static. When a movement status of the elevator is descending at a uniform speed, if it is detected that the movement status of the elevator is descending at a decelerating speed after an acceleration waveform classifier to which an acceleration change waveform belongs is obtained by means of comparison according to the acceleration waveform classifier, the movement status in the state machine converts to descending at a decelerating speed. Based on the state machine, the movement status of the elevator itself can be maintained, so as to avoid that the entire detection is affected by some peak errors, thereby improving robustness of the entire detection.
The following describes a specific implementation process of the foregoing story monitoring method when a robot takes an elevator with reference to a specific application scenario. For example, a starting story number when the robot takes the elevator is 3, and a story height of each story is 3 m. The robot is in the elevator. Gravity acceleration in a static state is 9.8 N/m2. When the elevator moves, acceleration of the elevator in a moving state is monitored by using an acceleration sensor installed in the robot. An acceleration change waveform is obtained by calculating a difference between the acceleration and the gravity acceleration. The acceleration change waveform is compared with an acceleration waveform classifier, to determine an acceleration waveform classifier to which the acceleration change waveform belongs. Then, a movement status of the elevator is obtained according to a correspondence between the acceleration waveform classifier and a movement status of the elevator. Next, an acceleration value at each moment and a total time of the elevator in a complete movement status is obtained, so as to calculate actual displacement of the elevator. For example, the actual displacement of the elevator is 12 m. A value obtained by dividing 12 m by 3 m is 4, the starting story number is 3, and therefore a current story number obtained by adding 3 and 4 is 7.
The data obtaining module 802 is configured to obtain gravity acceleration of the robot in a static state in the elevator and transient acceleration of the robot in a moving state in the elevator, a starting story number, and a story height of each story.
In this exemplary embodiment, an acceleration sensor in the robot can detect transient acceleration of the robot on an axis z when the robot is in the moving state as the elevator moves. Acceleration of the robot on three axes x, y, and z may be obtained by using the acceleration sensor. The starting story number may be set by a user of the robot. For example, if the robot is on the third story when starting to take the elevator, the starting story number of the robot is set to 3. For the story height of each story, the robot may be placed in the elevator in advance, and the elevator stops on each story when moving, to calculate displacement and record the story height of each story.
The data obtaining module 802 is further configured to calculate an average gravity acceleration value of multiple gravity acceleration values that are of the robot in the static state in the elevator and that are detected by using the acceleration sensor of the robot. The average gravity acceleration value is used as the gravity acceleration of the robot in the static state.
The estimation module 804 is configured to subtract the gravity acceleration of the robot in the static state from the transient acceleration of the robot in the moving state to obtain an acceleration change waveform of the robot.
The status detection module 806 is configured to: compare the acceleration change waveform by using an acceleration waveform classifier of the elevator, to obtain an acceleration waveform classifier to which the acceleration change waveform belongs, obtain a configured state machine and a conversion relationship between different movement statuses in the state machine, determine a moving direction of the elevator according to the conversion relationship and a next acceleration waveform classifier adjacent to an acceleration static waveform classifier, and obtain a movement status of the elevator at each moment according to a correspondence between the acceleration waveform classifier and a movement status of the elevator and the moving direction of the elevator.
In this exemplary embodiment, the status detection module 806 compares a waveform of the acceleration waveform classifier of the elevator with the acceleration change waveform; obtains a waveform of the acceleration waveform classifier whose distance to the acceleration change waveform is the shortest; and uses the acceleration waveform classifier whose distance is the shortest as the acceleration waveform classifier to which the acceleration change waveform belongs.
Specifically, the acceleration waveform classifier of the elevator is an acceleration waveform classifier obtained by performing training on acceleration waveform data that is prerecorded when the robot is in the elevator during ascending and descending.
The displacement calculation module 808 is configured to: obtain transient acceleration and a total time of the elevator in a complete movement status, obtain an instantaneous speed of the elevator according to the transient acceleration, and then obtain actual displacement of the elevator according to the instantaneous speed and the total time of the elevator, the complete movement status including a process of a static state, to an accelerating state, to a uniform speed state, to a decelerating state, and to a static state.
In this exemplary embodiment, according to the acceleration law vi=v0+at, the instantaneous speed of the elevator may be calculated by means of an initial speed, the transient acceleration, and a time period, and then the actual displacement of the elevator is calculated according to a relationship s=∫vidt between a speed and displacement. The movement status refers to a speed status.
The story monitoring module 810 is configured to obtain a story that the elevator is on after a complete movement status according to the actual displacement of the elevator, the starting story number, and the story height of each story.
According to the foregoing story monitoring apparatus when a robot takes an elevator, gravity acceleration of the robot in a static state in the elevator and transient acceleration of the robot in a moving state in the elevator are obtained, to obtain an acceleration change waveform; an acceleration waveform classifier of the elevator is used to compare the acceleration change waveform, to obtain an acceleration waveform classifier to which the acceleration change waveform belongs; a movement status of the elevator at each moment is obtained according to a correspondence between the acceleration waveform classifier and a movement status of the elevator; and then transient acceleration and a total time of the elevator in a complete movement status are obtained, to calculate the actual displacement. The story that the elevator is on, that is, the story that the robot is on, is obtained according to the actual displacement, the starting story number, and the story height of each story, thereby implementing monitoring stories that the robot is on when the robot takes various elevators.
The recording module 812 is configured to: before gravity acceleration of the robot in a static state in the elevator and transient acceleration of the robot in a moving state in the elevator, a starting story number, and a story height of each story are obtained, place the robot in the elevator, and record an acceleration waveform of the elevator during ascending and descending.
The training set establishment module 814 is configured to cut the recorded acceleration waveform into multiple different acceleration state sample training sets.
The classifier training module 816 is configured to obtain an acceleration waveform classifier by performing training according to the sample training set.
The marking module 818 is configured to obtain displacement of each story and mark the story height of each story.
The detection module 820 is configured to: after an acceleration change waveform is compared by using an acceleration waveform classifier of the elevator, to obtain an acceleration waveform classifier to which the acceleration change waveform belongs, and a movement status of the elevator at each moment is obtained according to a correspondence between the acceleration waveform classifier and a movement status of the elevator, detect whether the movement status of the elevator at each moment satisfies a conversion relationship between different configured states.
The status updating module 822 is configured to: if the conversion relationship between different configured movement statuses is satisfied, convert, by the movement status of the elevator, from a movement status in the configured state machine to a next movement status.
A status in the configured state machine includes: being static, ascending at an accelerating speed, ascending at a uniform speed, ascending at a decelerating speed, descending at an accelerating speed, descending at a uniform speed, and descending at a decelerating speed; and the conversion relationship between the different statuses includes conversion between adjacent movement statuses from being static, to ascending at an accelerating speed, to ascending at a uniform speed, and to ascending at a decelerating speed, and conversion between adjacent movement statuses from being static, to descending at an accelerating speed, to descending at a uniform speed, and to descending at a decelerating speed.
In another exemplary embodiment, the story monitoring apparatus when a robot takes an elevator may include any possible combination of the data obtaining module 802, the estimation module 804, the status detection module 806, the displacement calculation module 808, and the story monitoring module 810, and the recording module 812, the training set establishment module 814, the classifier training module 816, the marking module 818, the detection module 820, and the status updating module 822.
A person of ordinary skill in the art may understand that all or some of the processes of the methods in the foregoing embodiments may be implemented by a computer program instructing relevant hardware. The program may be stored in a non-volatile computer-readable storage medium. When the program runs, the processes of the foregoing method embodiments may be included. The storage medium may be a magnetic disc, an optical disc, a read-only memory (ROM), or the like.
The foregoing embodiments show only several implementations of the present disclosure and are described in detail, but they should not be construed as a limitation to the patent scope of the present disclosure. It should be noted that, a person of ordinary skill in the technology may make various changes and improvements without departing from the ideas of the present disclosure, which shall fall within the protection scope of the present disclosure. Therefore, the protection scope of the patent of the present disclosure shall be subject to the claims.
| Number | Date | Country | Kind |
|---|---|---|---|
| 201610296629.4 | May 2016 | CN | national |
This application is a National Stage of International Application No. PCT/CN2017/082970, filed on May 4, 2017, which claims priority to Chinese Patent Application No. 201610296629.4, entitled “STORY MONITORING METHOD AND APPARATUS WHEN ROBOT TAKES ELEVATOR”, filed on May 5, 2016 in the State Intellectual Property Office, which is incorporated herein by reference in its entirety.
| Filing Document | Filing Date | Country | Kind |
|---|---|---|---|
| PCT/CN2017/082970 | 5/4/2017 | WO | 00 |
