Method, apparatus, and electronic device of an autonomous mobile device

Abstract

Embodiments of the present disclosure disclose a method, device and electronic equipment of an autonomous mobile device. A specific implementation of the method comprises: performing the following control step: in response to detecting that a target autonomous navigation vehicle starts to move, determining a distance to be traveled for the target autonomous navigation vehicle to travel from a current position to an end position; according to the distance to be traveled, a preset maximum acceleration, a preset jerk and a preset maximum speed, planning a position trajectory of the target autonomous navigation vehicle by using an S-curve algorithm, and determining a speed to be traveled of the target autonomous navigation vehicle in a process of moving according to the position trajectory as a first speed; detecting whether the target autonomous navigation vehicle encounters an obstacle in the process of moving; if not, driving the target autonomous navigation vehicle according to the first speed, so that the target autonomous navigation vehicle moves according to the planned position trajectory. The implementation makes the autonomous navigation vehicle move more smoothly.

Description

Technical Field

[0001] This disclosure relates to the field of computer technology, and more specifically to methods, apparatus, and electronic devices for autonomous mobile devices. Background Technology

[0002] With the rapid development of e-commerce and new retail, Automated Guided Vehicles (AGVs) have been widely used. AGVs are transport vehicles equipped with electromagnetic or optical automatic navigation devices, capable of traveling along a predetermined navigation path, and possessing safety protection and various transfer functions. However, existing AGVs are prone to body shaking and vibration during start-up and stopping, which can cause liquids to spill when carrying cups or containers. Summary of the Invention

[0003] This disclosure is provided to briefly introduce the concepts, which will be described in detail in the subsequent Detailed Description section. This disclosure is not intended to identify key or essential features of the claimed technical solution, nor is it intended to limit the scope of the claimed technical solution.

[0004] This disclosure provides a method, apparatus, and electronic device for autonomous mobile devices, which adds the function of slow start and slow stop for autonomous navigation vehicles, making the movement of autonomous navigation vehicles smoother.

[0005] In a first aspect, embodiments of this disclosure provide a method for an autonomous mobile device, the method comprising: performing the following control steps: in response to detecting that a target autonomous navigation vehicle has started to move, determining the distance to be traveled by the target autonomous navigation vehicle from its current position to its destination position; planning the position trajectory of the target autonomous navigation vehicle using an S-curve algorithm based on the distance to be traveled, a preset maximum acceleration, a preset jerk, and a preset maximum speed, and determining the speed to be traveled by the target autonomous navigation vehicle during the movement according to the position trajectory as a first speed; detecting whether the target autonomous navigation vehicle encounters an obstacle during the movement; if not, driving the target autonomous navigation vehicle according to the first speed so that the target autonomous navigation vehicle moves according to the planned position trajectory.

[0006] Secondly, embodiments of this disclosure provide an apparatus for an autonomous mobile device, comprising: a first control unit, configured to drive the following modules to perform the following control steps: a determination module, configured to determine the distance to be traveled by the target autonomous navigation vehicle from its current position to its destination position in response to detecting that the target autonomous navigation vehicle has started to move; a planning module, configured to plan the position trajectory of the target autonomous navigation vehicle using an S-curve algorithm based on the distance to be traveled, a preset maximum acceleration, a preset jerk, and a preset maximum speed, and determine the speed to be traveled by the target autonomous navigation vehicle during the movement of the position trajectory as a first speed; a detection module, configured to detect whether the target autonomous navigation vehicle encounters an obstacle during the movement; and a transmission module, configured to drive the target autonomous navigation vehicle according to the first speed if the target autonomous navigation vehicle does not encounter an obstacle during the movement, so that the target autonomous navigation vehicle moves according to the planned position trajectory.

[0007] Thirdly, embodiments of this disclosure provide an electronic device, including: one or more processors; and a storage device for storing one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors implement the method of the autonomous mobile device as described in the first aspect.

[0008] Fourthly, embodiments of this disclosure provide a computer-readable medium having a computer program stored thereon that, when executed by a processor, implements the steps of the method of the autonomous mobile device as described in the first aspect.

[0009] The method, apparatus, and electronic device for autonomous mobility provided in this disclosure, in response to detecting that a target autonomous navigation vehicle has started to move, determine the distance the target autonomous navigation vehicle needs to travel from its current position to its destination position. Then, based on the distance to be traveled, a preset maximum acceleration, a preset jerk, and a preset maximum speed, an S-curve algorithm is used to plan the position trajectory of the target autonomous navigation vehicle, and a first speed is determined for the target autonomous navigation vehicle to move along the planned position trajectory. Next, it is detected whether the target autonomous navigation vehicle encounters an obstacle during its movement; if not, the target autonomous navigation vehicle is driven according to the first speed to move along the planned position trajectory. This method adds the function of gentle start and gentle stop for the autonomous navigation vehicle, making its movement smoother. Attached Figure Description

[0010] The above and other features, advantages, and aspects of the embodiments of this disclosure will become more apparent from the accompanying drawings and the following detailed description. Throughout the drawings, the same or similar reference numerals denote the same or similar elements. It should be understood that the drawings are schematic, and the originals and elements are not necessarily drawn to scale.

[0011] Figure 1 These are exemplary system architecture diagrams to which the various embodiments of this disclosure can be applied;

[0012] Figure 2 This is a flowchart of one embodiment of a method for an autonomous mobile device according to the present disclosure;

[0013] Figure 3 This is a flowchart of yet another embodiment of the method for an autonomous mobile device according to the present disclosure;

[0014] Figure 4 This is a schematic diagram of an application scenario of the method of the autonomous mobile device according to the present disclosure;

[0015] Figure 5 This is a flowchart of an embodiment of the method for determining the speed of a target autonomous navigation vehicle during deceleration in accordance with the present disclosure of the autonomous mobile device;

[0016] Figure 6 This is a schematic diagram of the structure of one embodiment of the autonomous mobile device according to the present disclosure;

[0017] Figure 7 This is a schematic diagram of the structure of a computer system suitable for implementing the embodiments of the present disclosure. Detailed Implementation

[0018] Embodiments of this disclosure will now be described in more detail with reference to the accompanying drawings. While some embodiments of this disclosure are shown in the drawings, it should be understood that this disclosure can be implemented in various forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided to provide a more thorough and complete understanding of this disclosure. It should be understood that the accompanying drawings and embodiments of this disclosure are for illustrative purposes only and are not intended to limit the scope of protection of this disclosure.

[0019] It should be understood that the steps described in the method embodiments of this disclosure may be performed in different orders and / or in parallel. Furthermore, the method embodiments may include additional steps and / or omit the steps shown. The scope of this disclosure is not limited in this respect.

[0020] The term "comprising" and its variations as used herein are open-ended inclusion, meaning "including but not limited to". The term "based on" means "at least partially based on". The term "one embodiment" means "at least one embodiment"; the term "another embodiment" means "at least one additional embodiment"; the term "some embodiments" means "at least some embodiments". Definitions of other terms will be given in the description below.

[0021] It should be noted that the concepts of "first" and "second" mentioned in this disclosure are used only to distinguish different devices, modules or units, and are not used to limit the order of functions performed by these devices, modules or units or their interdependencies.

[0022] It should be noted that the terms "a" and "a plurality of" used in this disclosure are illustrative rather than restrictive, and those skilled in the art should understand that, unless otherwise expressly indicated in the context, they should be understood as "one or more".

[0023] The names of messages or information exchanged between multiple devices in the embodiments of this disclosure are for illustrative purposes only and are not intended to limit the scope of such messages or information.

[0024] Figure 1 An exemplary system architecture 100 is shown, illustrating an embodiment of the method of autonomous mobile device to which the present application can be applied.

[0025] like Figure 1 As shown, the system architecture 100 may include an autonomous navigation vehicle 101, a network 102, and a server 103 that supports the autonomous navigation vehicle 101. The autonomous navigation vehicle 101 may include an in-vehicle intelligent device 104 and a driver 105. The network 102 serves as the medium for providing a communication link between the in-vehicle intelligent device 104 and the server 103. The network 102 may include various connection types, such as wired or wireless communication links, GPS, or fiber optic cables, etc.

[0026] The vehicle-mounted intelligent device 104 is equipped with a control system for the autonomous navigation vehicle 101. The control system can send control information (e.g., wheel speed) to the drive unit 105 to control the movement of the autonomous navigation vehicle 101. The vehicle-mounted intelligent device 104 can interact with the server 103 via the network 102 to receive control information and other information.

[0027] The autonomous navigation vehicle 101 can also be equipped with various sensors, such as obstacle sensors, cameras, gyroscopes, and accelerometers. It should be noted that the autonomous navigation vehicle 101 can also be equipped with various other types and functions of sensors besides those listed above, which will not be elaborated upon here.

[0028] The in-vehicle intelligent device 104 can execute the following control steps: First, in response to detecting that the autonomous navigation vehicle 101 has started to move, it determines the distance that the autonomous navigation vehicle 101 needs to travel from its current position to its destination position; then, based on the aforementioned distance to be traveled, a preset maximum acceleration, a preset jerk, and a preset maximum speed, it plans the position trajectory of the autonomous navigation vehicle 101 using an S-curve algorithm, and determines the speed to be traveled by the autonomous navigation vehicle 101 during its movement along the planned position trajectory as a first speed; then, it detects whether the autonomous navigation vehicle 101 encounters any obstacles during its movement; if not, it drives the driver 105 of the autonomous navigation vehicle 101 according to the aforementioned first speed, so that the autonomous navigation vehicle 101 moves along the planned position trajectory.

[0029] The in-vehicle intelligent device 104 can be either hardware or software. When the in-vehicle intelligent device 104 is hardware, it can be an electronic device that supports information interaction. When the in-vehicle intelligent device 104 is software, it can be installed in the aforementioned electronic device. It can be implemented as multiple software programs or software modules (e.g., to provide distributed services), or it can be implemented as a single software program or software module. No specific limitations are made here.

[0030] Server 103 can be a server that provides various services, such as a server that sends speed information to the in-vehicle intelligent device 104 installed on the autonomous navigation vehicle 101. Server 103 can perform the following control steps: First, in response to detecting that the autonomous navigation vehicle 101 has started to move, determine the distance that the autonomous navigation vehicle 101 needs to travel from its current position to its destination position; then, based on the aforementioned distance to be traveled, a preset maximum acceleration, a preset jerk, and a preset maximum speed, use an S-curve algorithm to plan the position trajectory of the autonomous navigation vehicle 101, and determine the speed to be traveled by the autonomous navigation vehicle 101 during the process of moving according to the planned position trajectory as a first speed; then, detect whether the autonomous navigation vehicle 101 encounters an obstacle during the movement; if not, drive the driver 105 of the autonomous navigation vehicle 101 according to the aforementioned first speed, so that the autonomous navigation vehicle 101 moves according to the planned position trajectory.

[0031] It should be noted that server 103 can be either hardware or software. When server 103 is hardware, it can be implemented as a distributed server cluster consisting of multiple servers, or as a single server. When server 103 is software, it can be implemented as multiple software programs or software modules (e.g., used to provide distributed services), or as a single software program or software module. No specific limitations are made here.

[0032] It should be noted that the method of the autonomous mobile device provided in this application embodiment can be executed by the server 103. In this case, the device of the autonomous mobile device can be set in the server 103.

[0033] It should also be noted that the method for the autonomous mobile device provided in this application embodiment can also be executed by the in-vehicle intelligent device 104. In this case, the autonomous mobile device can be installed in the in-vehicle intelligent device 104. In this case, the system architecture 100 may not include the network 102 and the server 103.

[0034] It should be understood that Figure 1 The number of autonomous navigation vehicles, in-vehicle intelligent devices, drives, networks, and servers shown is merely illustrative. Depending on implementation needs, any number of autonomous navigation vehicles, in-vehicle intelligent devices, drives, networks, and servers can be included.

[0035] Continue to refer to Figure 2 The diagram illustrates a flow 200 of an embodiment of a method for an autonomous mobile device according to the present disclosure. The method of the autonomous mobile device can perform the following control steps:

[0036] Step 201: In response to detecting that the target autonomous navigation vehicle has started to move, determine the distance that the target autonomous navigation vehicle needs to travel from its current position to its destination position.

[0037] In this embodiment, the execution subject of the autonomous mobile device method (e.g. Figure 1 The server or in-vehicle intelligent device shown can detect whether the target autonomous navigation vehicle has started moving. If so, the distance the target autonomous navigation vehicle needs to travel from its current location to its destination can be determined. The target autonomous navigation vehicle can be an autonomous navigation vehicle to be controlled. The distance to be traveled can be the length of a path selected from multiple traversable paths from the current location to the destination.

[0038] Step 202: Based on the distance to be traveled, the preset maximum acceleration, the preset jerk, and the preset maximum speed, the S-curve algorithm is used to plan the position trajectory of the target autonomous navigation vehicle, and the speed to be traveled during the movement of the target autonomous navigation vehicle according to the position trajectory is determined as the first speed.

[0039] In this embodiment, based on the distance to be traveled, the preset maximum acceleration, the preset jerk, and the preset maximum speed determined in step 201, the execution entity can use the S-curve algorithm to plan the position trajectory of the target autonomous navigation vehicle and determine the speed to be traveled by the target autonomous navigation vehicle during its movement along the position trajectory as the first speed. Jerk, also known as jerk or force rate of change, is the rate of change of acceleration over time.

[0040] Here, the S-curve algorithm divides the entire movement process into seven segments. The first stage is usually an acceleration segment, the second stage is usually a uniform acceleration segment, the third stage is usually a deceleration segment, the fourth stage is usually a constant speed segment, the fifth stage is usually an acceleration-deceleration segment, the sixth stage is usually a uniform deceleration segment, and the seventh stage is usually a deceleration-deceleration segment. The relationship between the travel distance, speed, acceleration, and jerk can be expressed by the following formulas (1), (2), and (3):

[0041]

[0042]

[0043]

[0044] Where S(t) represents the distance between the arrival position and the starting position (current position) of the autonomous navigation vehicle at travel time t, V(t) represents the velocity of the autonomous navigation vehicle at travel time t, a(t) represents the acceleration of the autonomous navigation vehicle at travel time t, J represents the jerk, t represents the time from the starting time, and a max T1 represents the maximum acceleration; T2 represents the duration of the first stage; T3 represents the duration of the first three stages; T4 represents the duration of the first four stages; T5 represents the duration of the first five stages; T6 represents the duration of the first six stages; T7 represents the duration of the first seven stages; S1 represents the distance traveled by the autonomous vehicle in the first stage; S2 represents the distance traveled by the autonomous vehicle in the first two stages; S3 represents the distance traveled by the autonomous vehicle in the first three stages; S4 represents the distance traveled by the autonomous vehicle in the first four stages; S5 represents the distance traveled by the autonomous vehicle in the first five stages. The driving distance is represented by S6, V0, V1, V2, V3, V4, V5, and V6.

[0045] It should be noted that the duration of the first stage is usually equal to the duration of the third stage, and the duration of the fifth stage is usually equal to the duration of the seventh stage.

[0046] In this embodiment, the execution entity can use the distance to be traveled and the preset maximum speed as limiting conditions, and use the preset maximum acceleration and preset jerk to solve the above formulas (1), (2) and (3) to obtain the values ​​of T1 to T7. Through the values ​​of T1 to T7, the speed to be traveled of the above target autonomous navigation vehicle at each time can be obtained.

[0047] Step 203: Detect whether the target autonomous navigation vehicle encounters obstacles during its movement.

[0048] In this embodiment, the execution entity can detect whether the target autonomous vehicle encounters obstacles during its movement. The obstacles can be objects that affect the movement of the target autonomous vehicle along its selected path. The target autonomous vehicle can be equipped with sensors (e.g., laser sensors, vision sensors, infrared sensors, and ultrasonic sensors). The target autonomous vehicle can transmit the sensor information detected by the sensors to the execution entity in real time. The execution entity can then analyze the received sensor information to determine whether the target autonomous vehicle has encountered obstacles during its movement.

[0049] As an example, the sensor information mentioned above may include the distance between the target autonomous vehicle and the obstacle. If the sensor information indicates that the distance between the target autonomous vehicle and the obstacle is unknown, it can be said that the target autonomous vehicle did not encounter an obstacle during its movement. If the distance between the target autonomous vehicle and the obstacle is less than a preset distance threshold, it can be said that the target autonomous vehicle encountered an obstacle during its movement.

[0050] If the aforementioned executing entity detects that the target autonomous navigation vehicle does not encounter any obstacles during its movement, then step 204 can be executed.

[0051] Step 204: In response to detecting that the target autonomous navigation vehicle has not encountered any obstacles during its movement, the target autonomous navigation vehicle will be driven according to the first speed so that the target autonomous navigation vehicle moves according to the planned position trajectory.

[0052] In this embodiment, if it is detected in step 203 that the target autonomous navigation vehicle does not encounter any obstacles during its movement, the execution entity can drive the target autonomous navigation vehicle according to the first speed so that the target autonomous navigation vehicle moves according to the planned position trajectory.

[0053] It should be noted that the aforementioned implementing entity can send the current first speed to the aforementioned target autonomous navigation vehicle in real time.

[0054] As an example, if the aforementioned executing entity is the in-vehicle intelligent device of the aforementioned target autonomous navigation vehicle, the aforementioned in-vehicle intelligent terminal, upon receiving the first speed corresponding to the current moment, can convert the first speed into the vehicle's motor speed, thereby controlling the aforementioned target autonomous navigation vehicle to move according to the planned position trajectory.

[0055] As another example, if the execution entity is a server, the server can send the first speed to the vehicle-mounted intelligent terminal of the target autonomous navigation vehicle. Upon receiving the first speed corresponding to the current moment, the vehicle-mounted intelligent terminal can convert the first speed into the vehicle's motor speed, thereby controlling the target autonomous navigation vehicle to move according to the planned location trajectory.

[0056] The method provided in the above embodiments of this disclosure applies the S-curve algorithm to the path planning of autonomous navigation vehicles, adding the function of slow start and slow stop of autonomous navigation vehicles, while also ensuring the time requirements for start and stop, achieving a stable start and stop effect, and making the movement of autonomous navigation vehicles more smooth.

[0057] Further reference Figure 3 This illustrates a flow 300 of another embodiment of a method for an autonomous mobile device. Flow 300 of the method for an autonomous mobile device includes the following steps:

[0058] Step 301, execute the following control steps: In response to the detection that the target autonomous navigation vehicle has started to move, determine the distance the target autonomous navigation vehicle needs to travel from its current position to its destination position; based on the distance to be traveled, the preset maximum acceleration, the preset jerk, and the preset maximum speed, plan the position trajectory of the target autonomous navigation vehicle using the S-curve algorithm, and determine the speed to be traveled by the target autonomous navigation vehicle during its movement along the position trajectory as the first speed; detect whether the target autonomous navigation vehicle encounters an obstacle during its movement; if not, drive the target autonomous navigation vehicle according to the first speed so that the target autonomous navigation vehicle moves along the planned position trajectory.

[0059] In this embodiment, step 301 may include sub-steps 3011, 3012, 3013, and 3014. Wherein:

[0060] Step 3011: In response to detecting that the target autonomous navigation vehicle has started to move, determine the distance to be traveled by the target autonomous navigation vehicle from the current position to the destination position.

[0061] Step 3012: Based on the distance to be traveled, the preset maximum acceleration, the preset jerk, and the preset maximum speed, the S-curve algorithm is used to plan the position trajectory of the target autonomous navigation vehicle, and the speed to be traveled during the movement of the target autonomous navigation vehicle according to the position trajectory is determined as the first speed.

[0062] Step 3013: Detect whether the target autonomous navigation vehicle encounters obstacles during its movement.

[0063] Step 3014: In response to detecting that the target autonomous navigation vehicle has not encountered any obstacles during its movement, the target autonomous navigation vehicle is driven according to the first speed so that it moves according to the planned position trajectory.

[0064] In this embodiment, sub-steps 3011-3014 can be executed in a similar manner to steps 201-204, and will not be described again here.

[0065] Step 302: In response to the detection that the target autonomous navigation vehicle encounters an obstacle during its movement, the driving speed of the target autonomous navigation vehicle is planned using the S-curve algorithm, and the driving speed of the target autonomous navigation vehicle during the deceleration process is determined as the second speed.

[0066] In this embodiment, if it is detected in step 3013 that the target autonomous navigation vehicle encounters an obstacle during its movement, then the executing entity of the autonomous movement device method (e.g., Figure 1 The server or vehicle-mounted intelligent device shown can use the S-curve algorithm to plan the driving speed of the aforementioned target autonomous navigation vehicle and determine the driving speed of the aforementioned target autonomous navigation vehicle during the deceleration process as the second speed.

[0067] Here, when the aforementioned autonomous navigation vehicle encounters an obstacle during its movement, it needs to decelerate. The aforementioned execution entity can use the distance between the aforementioned autonomous navigation vehicle and the obstacle at the current moment, the aforementioned target speed, the aforementioned maximum acceleration and the aforementioned jerk, and use the last four terms of the following formulas (2) and (3) to solve for the values ​​of T3 to T7. Through the values ​​of T3 to T7, the expected speed of the aforementioned autonomous navigation vehicle at each moment can be obtained.

[0068]

[0069]

[0070] Step 303: Drive the target autonomous navigation vehicle according to the second speed so that the target autonomous navigation vehicle moves at the planned speed.

[0071] In this embodiment, the execution entity can drive the target autonomous navigation vehicle according to the second speed obtained in step 302, so that the target autonomous navigation vehicle moves at the planned driving speed.

[0072] It should be noted that the aforementioned implementing entity can send the second speed corresponding to the current moment to the aforementioned target autonomous navigation vehicle in real time.

[0073] As an example, if the aforementioned executing entity is the in-vehicle intelligent device of the aforementioned target autonomous navigation vehicle, the aforementioned in-vehicle intelligent terminal, upon receiving the second speed corresponding to the current moment, can convert the second speed into the vehicle's motor speed, thereby controlling the aforementioned target autonomous navigation vehicle to move according to the planned position trajectory.

[0074] As another example, if the execution entity is a server, the server can send the second speed to the vehicle-mounted intelligent terminal of the target autonomous navigation vehicle. Upon receiving the second speed corresponding to the current moment, the vehicle-mounted intelligent terminal can convert the second speed into the vehicle's motor speed, thereby controlling the target autonomous navigation vehicle to move according to the planned location trajectory.

[0075] Step 304: Determine whether the current speed of the target autonomous navigation vehicle is less than or equal to the target speed. If the current speed of the target autonomous navigation vehicle is less than or equal to the target speed, then continue to execute control step 301.

[0076] In this embodiment, the executing entity can determine whether the current speed of the target autonomous navigation vehicle is less than or equal to the target speed. The target speed can be a pre-set speed that ensures the autonomous navigation vehicle will not collide with obstacles; for example, it can be 0.

[0077] If the current speed of the target autonomous navigation vehicle is less than or equal to the target speed, the execution entity can continue to execute control step 301, i.e., sub-steps 3011-3014. In other words, after the speed is reduced to the target speed, the S-curve algorithm can be used to plan the position trajectory of the target autonomous navigation vehicle, and the corresponding speed to be traveled can be sent to the target autonomous navigation vehicle.

[0078] from Figure 3 It can be seen from this that, with Figure 2Compared to the corresponding embodiments, the flow 300 of the autonomous mobile device method in this embodiment embodies the step of planning the driving speed of the autonomous navigation vehicle using an S-curve algorithm to control the autonomous navigation vehicle when encountering obstacles. Therefore, the solution described in this embodiment adds a gentle stopping function when the autonomous navigation vehicle needs to decelerate upon encountering obstacles, resulting in a smoother stop for the autonomous navigation vehicle.

[0079] See also Figure 4 , Figure 4 This is a schematic diagram illustrating an application scenario of the autonomous mobile device method according to this embodiment. Figure 4In the application scenario, server 401 detects that autonomous navigation vehicle 402 has started moving from its current position A, and can determine the distance 403 that autonomous navigation vehicle 402 needs to travel from its current position A to its destination position D. Then, server 401 can use the S-curve algorithm to plan the position trajectory of autonomous navigation vehicle 402 based on the distance 403, the preset maximum acceleration 404, the preset jerk 405, and the preset maximum speed 406, and determine the speed 407 that autonomous navigation vehicle 402 needs to travel along the position trajectory. Here, server 401 can use the distance 403 and the maximum speed 406 as constraints, and use the maximum acceleration 404 and jerk 405 to solve the above formulas (1), (2), and (3) to obtain the values ​​from T1 to T7. Using the values ​​from T1 to T7, the speed 402 needs to travel at each moment can be obtained. Then, server 401 can detect whether autonomous navigation vehicle 402 encounters obstacles during its movement. Here, server 401 detects that autonomous vehicle 402 has not encountered any obstacles during its movement from point A to point B. Server 401 can send a first speed 407 to autonomous vehicle 402 so that autonomous vehicle 402 moves according to the planned trajectory. When autonomous vehicle 402 reaches point B, server 401 detects an obstacle in front of autonomous vehicle 402. Server 401 can use the S-curve algorithm to plan the speed of autonomous vehicle 402 and determine the speed of autonomous vehicle 402 during deceleration as the second speed 408. Here, server 401 can use the current speed 409, target speed 410, maximum acceleration 404, and jerk 405, and the last four terms in formulas (2) and (3) above to determine the speed of the target autonomous vehicle during deceleration. Afterwards, server 401 can send the second speed 408 to autonomous vehicle 402 so that autonomous vehicle 402 moves according to the planned speed. Then, it can be determined whether the current speed of the autonomous navigation vehicle 402 is less than or equal to the target speed 410. If, when the autonomous navigation vehicle 402 reaches point C, it is detected that the current speed of the autonomous navigation vehicle 402 is less than the target speed 410, the S-curve algorithm can be used again to plan the position trajectory of the autonomous navigation vehicle 402 so that the autonomous navigation vehicle 402 moves according to the planned position trajectory.

[0080] Further reference Figure 5 , Figure 5 This is a flowchart 500 of an embodiment of the method for determining the speed of a target autonomous navigation vehicle during deceleration, according to the autonomous mobile device of this disclosure. Figure 5As shown, in this embodiment, the step of determining the speed of the target autonomous navigation vehicle during deceleration includes:

[0081] Step 501: Obtain the current speed of the target autonomous navigation vehicle.

[0082] In this embodiment, the execution subject of the autonomous mobile device method (e.g. Figure 1 The server or in-vehicle intelligent device shown can obtain the current speed of the target autonomous navigation vehicle. The target autonomous navigation vehicle can be an autonomous navigation vehicle to be controlled. The executing entity can obtain the current speed of the target autonomous navigation vehicle from its in-vehicle intelligent device.

[0083] Step 502: Determine the difference between the current speed and the target speed.

[0084] In this embodiment, the executing entity can determine the difference between the current speed and the target speed. The target speed can be a pre-set speed that ensures the autonomous navigation vehicle will not collide with obstacles; for example, it can be 0.

[0085] As an example, if the current speed is 3 meters per second (m / s) and the target speed is 0 meters per second, the difference is 3.

[0086] Step 503: Based on the difference, maximum acceleration, and jerk, determine the number of deceleration steps and the duration of each deceleration interval for the target autonomous navigation vehicle during the deceleration process.

[0087] In this embodiment, based on the difference determined in step 502, the aforementioned maximum acceleration, and the aforementioned jerk, the executing entity can determine the number of deceleration steps and the duration of each deceleration interval for the target autonomous navigation vehicle during the deceleration process. The aforementioned number of deceleration steps can refer to the number of deceleration intervals, i.e., the number of movement stages.

[0088] Step 504: Using the number of deceleration steps and the duration of each deceleration interval, determine the driving speed of the target autonomous navigation vehicle during the deceleration process as the second speed.

[0089] In this embodiment, the execution entity can use the number of deceleration steps and the duration of each deceleration interval determined in step 503 to determine the driving speed of the target autonomous navigation vehicle during the deceleration process as the second speed. Using the number of deceleration steps and the duration of each deceleration interval, the execution entity can determine the driving speed of the target autonomous navigation vehicle during the deceleration process using the last four terms of the following formula (2).

[0090]

[0091] In some optional implementations, the execution entity can determine the number of deceleration steps and the duration of each deceleration interval of the target autonomous vehicle during deceleration based on the difference, the maximum acceleration, and the jerk as follows: The execution entity can determine the ratio of the square of the maximum acceleration to the jerk as a first ratio, and determine whether the difference is greater than or equal to the first ratio. If the difference is less than the first ratio, the execution entity can set the number of deceleration steps of the target autonomous vehicle during deceleration to two, that is, there are two deceleration intervals, usually an acceleration / deceleration segment (i.e., the fifth stage in formula (2)) and a deceleration segment (i.e., the seventh stage in formula (2)). Then, the ratio of the maximum acceleration to the jerk can be determined as the duration of each deceleration interval.

[0092] In some optional implementations, the execution entity can determine the number of deceleration steps and the duration of each deceleration interval of the target autonomous vehicle during the deceleration process based on the difference, the maximum acceleration, and the jerk as follows: The execution entity can determine the ratio of the square of the maximum acceleration to the jerk as the first ratio, and determine whether the difference is greater than or equal to the first ratio. If the difference is greater than or equal to the first ratio, the execution entity can set the number of deceleration steps of the target autonomous vehicle during the deceleration process to three, that is, there are three deceleration intervals at this time, which are usually an acceleration / deceleration segment (i.e., the fifth stage in the above formula (2)), a uniform deceleration segment (i.e., the sixth stage in the above formula (2)) and a deceleration segment (i.e., the seventh stage in the above formula (2)).

[0093] Then, the aforementioned executing entity can determine the square root of the product of the aforementioned difference and the aforementioned jerk, and use the aforementioned square root value to update the aforementioned maximum acceleration, that is, the updated maximum acceleration can be determined using the following formula (4):

[0094]

[0095] Among them, a max The updated maximum acceleration is represented by J, and the jerk is represented by V. error It represents the difference between the current speed and the target speed.

[0096] Then, the aforementioned executing entity can determine the ratio of the updated maximum acceleration to the aforementioned acceleration as the duration of the first and third deceleration intervals, that is, the duration of the first and third deceleration intervals can be determined using the following formula (5):

[0097]

[0098] Among them, amax The maximum acceleration after the update is represented by J, the jerk is represented by T1, the duration of the first deceleration interval is represented by T3, and the duration of the third deceleration interval is represented by T3.

[0099] Then, the aforementioned executing entity can use the ratio of the aforementioned difference to the aforementioned maximum acceleration as the second ratio, and can determine the duration of the aforementioned second deceleration interval by the difference between the aforementioned second ratio and the duration of the aforementioned first deceleration interval. That is, the duration of the second deceleration interval can be determined using the following formula (6):

[0100]

[0101] Among them, V error a represents the difference between the current velocity and the target velocity. max T1 represents the maximum acceleration after the update, T2 represents the duration of the first deceleration interval, and T2 represents the duration of the second deceleration interval.

[0102] It should be noted that the time of the first deceleration interval precedes the time of the second deceleration interval, and the time of the second deceleration interval precedes the time of the third deceleration interval. That is, the target autonomous navigation vehicle decelerates in the order of the first, second, and third deceleration intervals.

[0103] Further reference Figure 6 As an implementation of the methods shown in the above figures, this disclosure provides an embodiment of an autonomous mobile device, which is similar to... Figure 2 Corresponding to the method embodiments shown, this device can be specifically applied to various electronic devices.

[0104] like Figure 6As shown, the autonomous mobile device 600 of this embodiment includes a first control unit 601, which includes a determination module 6011, a planning module 6012, a detection module 6013, and a drive module 6014. The first control unit 601 drives the following modules to perform the following control steps: the determination module 6011 determines the distance the target autonomous navigation vehicle needs to travel from its current position to its destination position in response to the detection that the target autonomous navigation vehicle has started moving; the planning module 6012 plans the position trajectory of the target autonomous navigation vehicle using an S-curve algorithm based on the distance to be traveled, a preset maximum acceleration, a preset jerk, and a preset maximum speed, and determines the speed to be traveled during the movement of the target autonomous navigation vehicle according to the position trajectory as a first speed; the detection module 6013 detects whether the target autonomous navigation vehicle encounters obstacles during its movement; and the drive module 6014 drives the target autonomous navigation vehicle according to the first speed if the target autonomous navigation vehicle does not encounter obstacles during its movement, so that the target autonomous navigation vehicle moves according to the planned position trajectory.

[0105] In this embodiment, the specific processing of the determination module 6011, planning module 6012, detection module 6013, and driving module 6014 in the first control unit 601 of the autonomous mobile device 600 can be referred to Figure 2 The corresponding steps are 201, 202, 203 and 204 in the embodiment.

[0106] In some alternative implementations, the autonomous mobile device 600 may further include a second control unit (not shown in the figure). This second control unit is used to, in response to detecting that the target autonomous vehicle encounters an obstacle during movement, plan the speed of the target autonomous vehicle using an S-curve algorithm, determine the speed of the target autonomous vehicle during deceleration as a second speed; drive the target autonomous vehicle according to the second speed to make it move at the planned speed; determine whether the current speed of the target autonomous vehicle is less than or equal to the target speed; if so, continue executing the control steps.

[0107] In some optional implementations, the second control unit is further configured to plan the speed of the target autonomous vehicle using an S-curve algorithm through the following steps, and determine the speed of the target autonomous vehicle during deceleration as the second speed: obtaining the current speed of the target autonomous vehicle; determining the difference between the current speed and the target speed; determining the number of deceleration steps and the duration of each deceleration interval of the target autonomous vehicle during deceleration based on the difference, the maximum acceleration, and the jerk; and determining the speed of the target autonomous vehicle during deceleration as the second speed using the number of deceleration steps and the duration of each deceleration interval.

[0108] In some optional implementations, the second control unit is further configured to determine the number of deceleration steps and the duration of each deceleration interval of the target autonomous vehicle during the deceleration process based on the difference, maximum acceleration, and jerk, by: determining the ratio of the square of the maximum acceleration to the jerk as a first ratio; determining whether the difference is greater than or equal to the first ratio; if not, setting the number of deceleration steps of the target autonomous vehicle during the deceleration process to two, and determining the ratio of the maximum acceleration to the jerk as the duration of each deceleration interval.

[0109] In some optional implementations, the second control unit is further configured to determine the number of deceleration steps and the duration of each deceleration interval of the target autonomous vehicle during deceleration based on the difference, maximum acceleration, and jerk, by: determining the ratio of the square of the maximum acceleration to the jerk as a first ratio; determining whether the difference is greater than or equal to the first ratio; if so, setting the number of deceleration steps of the target autonomous vehicle during deceleration to three; determining the square root of the product of the difference and the jerk; updating the maximum acceleration using the square root; determining the updated ratio of the maximum acceleration to the jerk as the duration of the first and third deceleration intervals; and determining the ratio of the difference to the maximum acceleration as a second ratio; determining the difference between the second ratio and the duration of the first deceleration interval as the duration of the second deceleration interval, wherein the duration of the first deceleration interval precedes the duration of the second deceleration interval, and the duration of the second deceleration interval precedes the duration of the third deceleration interval.

[0110] The following is for reference. Figure 7 It illustrates an electronic device suitable for implementing embodiments of the present disclosure (e.g., Figure 1 A structural diagram of the 700 (server or in-vehicle intelligent device). Figure 7 The electronic device shown is merely an example and should not be construed as limiting the functionality and scope of the embodiments of this disclosure.

[0111] like Figure 7As shown, the electronic device 700 may include a processing unit (e.g., a central processing unit, a graphics processor, etc.) 701, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 702 or a program loaded from a storage device 708 into a random access memory (RAM) 703. The RAM 703 also stores various programs and data required for the operation of the electronic device 700. The processing unit 701, ROM 702, and RAM 703 are interconnected via a bus 704. An input / output (I / O) interface 705 is also connected to the bus 704.

[0112] Typically, the following devices can be connected to I / O interface 705: input devices 706 including, for example, touchscreens, touchpads, keyboards, mice, cameras, microphones, accelerometers, gyroscopes, etc.; output devices 707 including, for example, liquid crystal displays (LCDs), speakers, vibrators, etc.; storage devices 708 including, for example, magnetic tapes, hard disks, etc.; and communication devices 709. Communication device 709 allows electronic device 700 to communicate wirelessly or wiredly with other devices to exchange data. Although Figure 7 An electronic device 700 with various devices is shown; however, it should be understood that it is not required to implement or possess all of the devices shown. More or fewer devices may be implemented or possessed alternatively. Figure 7 Each box shown can represent a device or multiple devices as needed.

[0113] Specifically, according to embodiments of this disclosure, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of this disclosure include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via a communication device 709, or installed from a storage device 708, or installed from a ROM 702. When the computer program is executed by a processing device 701, it performs the functions defined in the methods of embodiments of this disclosure. It should be noted that the computer-readable medium described in embodiments of this disclosure can be a computer-readable signal medium or a computer-readable storage medium, or any combination of the two. A computer-readable storage medium can be, for example,—but not limited to—an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of computer-readable storage media may include, but are not limited to: electrical connections having one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. In embodiments of this disclosure, a computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in connection with an instruction execution system, apparatus, or device. In embodiments of this disclosure, a computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A computer-readable signal medium may also be any computer-readable medium other than a computer-readable storage medium, which can send, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device. Program code contained on a computer-readable medium may be transmitted using any suitable medium, including but not limited to: wires, optical fibers, RF (radio frequency), etc., or any suitable combination thereof.

[0114] In some implementations, clients and servers can communicate using any currently known or future-developed network protocol such as HTTP (Hypertext Transfer Protocol) and can interconnect with digital data communication (e.g., communication networks) of any form or medium. Examples of communication networks include local area networks (“LANs”), wide area networks (“WANs”), the Internet (e.g., the Internet of Things), and peer-to-peer networks (e.g., ad hoc peer-to-peer networks), as well as any currently known or future-developed networks.

[0115] The aforementioned computer-readable medium may be included in the aforementioned electronic device; or it may exist independently and not assembled into the electronic device.

[0116] The aforementioned computer-readable medium carries one or more programs. When the electronic device executes one or more of these programs, the electronic device performs the following control steps: in response to detecting that the target autonomous navigation vehicle has started to move, it determines the distance the target autonomous navigation vehicle needs to travel from its current position to its destination position; based on the distance to be traveled, a preset maximum acceleration, a preset jerk, and a preset maximum speed, it plans the position trajectory of the target autonomous navigation vehicle using an S-curve algorithm, and determines the speed to be traveled by the target autonomous navigation vehicle during its movement along the position trajectory as a first speed; it detects whether the target autonomous navigation vehicle encounters an obstacle during its movement; if not, it drives the target autonomous navigation vehicle according to the first speed so that the target autonomous navigation vehicle moves along the planned position trajectory.

[0117] Computer program code for performing the operations of this disclosure can be written in one or more programming languages ​​or a combination thereof, including but not limited to object-oriented programming languages ​​such as Java, Smalltalk, and C++, as well as conventional procedural programming languages ​​such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0118] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this disclosure. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0119] The units or modules described in the embodiments of this disclosure can be implemented in software or hardware. The names of the units or modules do not necessarily limit the specific unit or module; for example, a detection module can also be described as "a module for detecting whether a target autonomous navigation vehicle encounters obstacles during its movement."

[0120] The functions described above in this document can be performed, at least in part, by one or more hardware logic components. For example, exemplary types of hardware logic components that can be used, without limitation, include: Field Programmable Gate Arrays (FPGAs), Application-Specific Integrated Circuits (ASICs), Application Standard Products (ASSPs), System-on-Chip (SoCs), Complex Programmable Logic Devices (CPLDs), and so on.

[0121] In the context of this disclosure, a machine-readable medium can be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, apparatus, or device. A machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium can be, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0122] The above description is merely a preferred embodiment of this disclosure and an explanation of the technical principles employed. Those skilled in the art should understand that the scope of this disclosure is not limited to technical solutions formed by specific combinations of the above-described technical features, but should also cover other technical solutions formed by arbitrary combinations of the above-described technical features or their equivalents without departing from the above-described concept. For example, technical solutions formed by substituting the above features with (but not limited to) technical features disclosed in this disclosure that have similar functions.

[0123] Furthermore, while the operations are described in a specific order, this should not be construed as requiring these operations to be performed in the specific order shown or in a sequential order. In certain environments, multitasking and parallel processing may be advantageous. Similarly, while several specific implementation details are included in the above discussion, these should not be construed as limiting the scope of this disclosure. Certain features described in the context of individual embodiments may also be implemented in combination in a single embodiment. Conversely, various features described in the context of a single embodiment may also be implemented individually or in any suitable sub-combination in multiple embodiments.

[0124] Although the subject matter has been described using language specific to structural features and / or methodological logic, it should be understood that the subject matter defined in the appended claims is not necessarily limited to the specific features or actions described above. Rather, the specific features and actions described above are merely illustrative examples of implementing the claims.

Claims

1. A method for an autonomous mobile device, characterized in that, include: The following control steps are performed: In response to detecting that the target autonomous navigation vehicle has started to move, the distance to be traveled by the target autonomous navigation vehicle from its current position to its destination position is determined; Based on the distance to be traveled, the preset maximum acceleration, the preset jerk, and the preset maximum speed, the S-curve algorithm is used to plan the position trajectory of the target autonomous navigation vehicle, and the speed to be traveled during the movement of the target autonomous navigation vehicle according to the position trajectory is determined as the first speed. Detect whether the target autonomous navigation vehicle encounters obstacles during its movement; If not, then the target autonomous navigation vehicle is driven according to the first speed so that the target autonomous navigation vehicle moves according to the planned position trajectory; In response to the detection that the target autonomous navigation vehicle encounters an obstacle during its movement, the S-curve algorithm is used to plan the driving speed of the target autonomous navigation vehicle, and the driving speed of the target autonomous navigation vehicle during the deceleration process is determined as the second speed. Based on the second speed, the target autonomous navigation vehicle is driven to move at the planned speed; it is determined whether the current speed of the target autonomous navigation vehicle is less than or equal to the target speed. If so, continue with the control steps described above; as well as The step of using the S-curve algorithm to plan the speed of the target autonomous navigation vehicle and determining the speed of the target autonomous navigation vehicle during deceleration as the second speed includes: Obtain the current speed of the target autonomous navigation vehicle; Determine the difference between the current speed and the target speed; Based on the difference, the maximum acceleration, and the jerk, the number of deceleration steps and the duration of each deceleration interval of the target autonomous vehicle during the deceleration process are determined, including: determining the ratio of the square of the maximum acceleration to the jerk as a first ratio; determining whether the difference is greater than or equal to the first ratio; if not, then setting the number of deceleration steps of the target autonomous vehicle during the deceleration process to two, and determining the ratio of the maximum acceleration to the jerk as the duration of each deceleration interval; Using the number of deceleration steps and the duration of each deceleration interval, the driving speed of the target autonomous navigation vehicle during the deceleration process is determined as the second speed.

2. The method according to claim 1, characterized in that, The step of determining the number of deceleration steps and the duration of each deceleration interval of the target autonomous navigation vehicle during the deceleration process based on the difference, the maximum acceleration, and the jerk includes: The ratio of the square of the maximum acceleration to the acceleration is determined as a first ratio, and it is determined whether the difference is greater than or equal to the first ratio. If so, the deceleration steps of the target autonomous navigation vehicle during deceleration are set to three. The square root of the square root of the product of the difference and the acceleration is determined. The maximum acceleration is updated using the square root value. The ratio of the updated maximum acceleration to the acceleration is determined as the duration of the first and third deceleration intervals. The ratio of the difference to the maximum acceleration is used as the second ratio. The difference between the second ratio and the duration of the first deceleration interval is determined as the duration of the second deceleration interval. The duration of the first deceleration interval precedes the duration of the second deceleration interval, and the duration of the second deceleration interval precedes the duration of the third deceleration interval.

3. A device for an autonomous mobile device, characterized in that, include: The first control unit is used to drive the following modules to perform the following control steps: the determination module is used to determine the distance to be traveled by the target autonomous navigation vehicle from its current position to the destination position in response to the detection that the target autonomous navigation vehicle has started to move; The planning module is used to plan the position trajectory of the target autonomous navigation vehicle using an S-curve algorithm based on the distance to be traveled, the preset maximum acceleration, the preset jerk, and the preset maximum speed, and to determine the speed to be traveled by the target autonomous navigation vehicle during the movement of the position trajectory as the first speed. The detection module is used to detect whether the target autonomous navigation vehicle encounters obstacles during its movement; The drive module is used to drive the target autonomous navigation vehicle according to the first speed if the target autonomous navigation vehicle does not encounter any obstacles during its movement, so that the target autonomous navigation vehicle moves according to the planned position trajectory. The second control unit is used to respond to the detection that the target autonomous navigation vehicle encounters an obstacle during its movement, and to plan the driving speed of the target autonomous navigation vehicle using an S-curve algorithm, and determine the driving speed of the target autonomous navigation vehicle during the deceleration process as the second speed. Based on the second speed, the target autonomous vehicle is driven to move at a planned speed; it is determined whether the current speed of the target autonomous vehicle is less than or equal to the target speed; if so, the control steps continue; and The second control unit is further configured to plan the travel speed of the target autonomous navigation vehicle using an S-curve algorithm through the following steps, and determine the travel speed of the target autonomous navigation vehicle during deceleration as the second speed: Obtain the current speed of the target autonomous navigation vehicle; Determine the difference between the current speed and the target speed; Based on the difference, the maximum acceleration, and the jerk, the number of deceleration steps and the duration of each deceleration interval of the target autonomous vehicle during the deceleration process are determined, including: determining the ratio of the square of the maximum acceleration to the jerk as a first ratio; determining whether the difference is greater than or equal to the first ratio; if not, then setting the number of deceleration steps of the target autonomous vehicle during the deceleration process to two, and determining the ratio of the maximum acceleration to the jerk as the duration of each deceleration interval; Using the number of deceleration steps and the duration of each deceleration interval, the driving speed of the target autonomous navigation vehicle during the deceleration process is determined as the second speed.

4. The apparatus according to claim 3, characterized in that, The second control unit is further configured to determine, based on the difference, the maximum acceleration, and the jerk, the number of deceleration steps and the duration of each deceleration interval of the target autonomous vehicle during the deceleration process through the following steps: The ratio of the square of the maximum acceleration to the acceleration is determined as a first ratio, and it is determined whether the difference is greater than or equal to the first ratio. If so, the deceleration steps of the target autonomous navigation vehicle during deceleration are set to three. The square root of the square root of the product of the difference and the acceleration is determined. The maximum acceleration is updated using the square root value. The ratio of the updated maximum acceleration to the acceleration is determined as the duration of the first and third deceleration intervals. The ratio of the difference to the maximum acceleration is used as the second ratio. The difference between the second ratio and the duration of the first deceleration interval is determined as the duration of the second deceleration interval. The duration of the first deceleration interval precedes the duration of the second deceleration interval, and the duration of the second deceleration interval precedes the duration of the third deceleration interval.

5. An electronic device, characterized in that, include: One or more processors; Storage device, on which one or more programs are stored, When the one or more programs are executed by the one or more processors, the one or more processors implement the method as described in any one of claims 1-2.

6. A computer-readable medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it implements the method as described in any one of claims 1-2.

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