CN111580530B - Positioning method, positioning device, autonomous mobile equipment and medium - Google Patents
Positioning method, positioning device, autonomous mobile equipment and medium Download PDFInfo
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Abstract
The embodiment of the invention discloses a positioning method, a positioning device, autonomous mobile equipment and a medium. The method comprises the following steps: acquiring estimated pose information of the autonomous mobile equipment in real time to serve as a first initial pose; according to the first initial pose, performing first accurate positioning on the autonomous mobile equipment by adopting a synchronous positioning and mapping SLAM algorithm; and if determining that the first accurate positioning of the autonomous mobile equipment fails, based on the estimated pose information, adopting at least one positioning algorithm to perform re-positioning on the autonomous mobile equipment so as to update the first initial pose, returning to execute accurate positioning on the autonomous mobile equipment according to the first initial pose by adopting a SLAM algorithm. By the technical scheme of the invention, the positioning stability of the autonomous mobile equipment can be improved.
Description
Technical Field
The embodiment of the invention relates to the technical field of intelligent robots, in particular to a positioning method, a positioning device, autonomous mobile equipment and a medium.
Background
With the development of intelligent robot technology, from the last 70 th century, AGVs (automated Guided vehicles) gradually become one of the key technologies of flexible production lines and modern storage systems, and because of their characteristics of high automation degree, safety, flexibility and the like, AGVs have been widely applied in automated production processes such as intelligent manufacturing and the like and in logistics fields. An AGV, also commonly referred to as an AGV cart, is a transport vehicle equipped with an electromagnetic or optical automatic navigation device, capable of traveling along a predetermined navigation path, and having safety protection and various transfer functions.
Through actual investigation, manufacturing enterprise is comparatively harsh to AGV's requirement, because needs AGV can the accurate butt joint board that targets in the production process, faces realistic problems such as heavy load, operating space are narrow simultaneously, and the overwhelming majority of AGV can not satisfy the requirement on the market, consequently, how improve AGV's positioning stability, location accuracy etc. become the problem that waits to solve when using AGV in the production line urgently.
In the prior art, a single positioning algorithm is mainly adopted to provide positioning support for the AGV, and once the algorithm fails, the AGV frequently fails in positioning and reports errors, so that the positioning stability of the AGV is poor.
Disclosure of Invention
The embodiment of the invention provides a positioning method, a positioning device, autonomous mobile equipment and a medium, which are used for improving the positioning stability of the autonomous mobile equipment.
In a first aspect, an embodiment of the present invention provides a positioning method applied to an autonomous mobile device, including:
acquiring estimated pose information of the autonomous mobile equipment in real time to serve as a first initial pose;
according to the first initial pose, performing first accurate positioning on the autonomous mobile equipment by adopting a synchronous positioning and mapping SLAM algorithm;
and if determining that the first accurate positioning of the autonomous mobile equipment fails, based on the estimated pose information, adopting at least one positioning algorithm to perform re-positioning on the autonomous mobile equipment so as to update the first initial pose, returning to execute accurate positioning on the autonomous mobile equipment according to the first initial pose by adopting a SLAM algorithm.
Further, based on the estimated pose information, repositioning the autonomous mobile device using at least one positioning algorithm to update the first initial pose, comprising:
taking the estimated pose information as a second initial pose, and performing second accurate positioning on the autonomous mobile equipment by adopting a self-adaptive Monte Carlo positioning AMCL algorithm according to the second initial pose;
and if the second accurate positioning of the autonomous mobile equipment is determined to be successful, using the position and posture information of the autonomous mobile equipment obtained through positioning as the updated first initial position and posture.
Further, after taking the estimated pose information as a second initial pose and performing a second precise positioning on the autonomous mobile device by using an AMCL algorithm according to the second initial pose, the method further includes:
if the second accurate positioning of the autonomous mobile equipment is determined to fail, performing third accurate positioning on the autonomous mobile equipment by adopting a global positioning algorithm according to the estimated pose information;
and if the third accurate positioning of the autonomous mobile equipment is determined to be successful, the pose information of the autonomous mobile equipment obtained by positioning is used as the updated second initial pose, and the AMCL algorithm is adopted to perform the second accurate positioning of the autonomous mobile equipment according to the second initial pose.
Further, after the autonomous mobile device is located by using a global positioning algorithm according to the estimated pose information, the method further includes:
and if the third accurate positioning of the autonomous mobile equipment is determined to fail, performing positioning failure alarm prompting.
Further, acquiring the estimated pose information of the autonomous mobile device in real time includes:
acquiring data information acquired by at least one laser radar arranged on the autonomous mobile equipment in real time;
and acquiring estimated pose information of the autonomous mobile equipment by adopting a milemeter pose estimation method according to the data information.
Further, according to the first initial pose, performing first accurate positioning on the autonomous mobile device by using a SLAM algorithm, including:
according to the first initial pose, carrying out first accurate positioning on the autonomous mobile equipment by adopting an SLAM algorithm, and constructing a real-time map;
correspondingly, after the first accurate positioning of the autonomous mobile device is performed by using the SLAM algorithm according to the first initial pose, the method further includes:
if the first accurate positioning of the autonomous mobile equipment is determined to be successful, planning a traveling route of the autonomous mobile equipment according to the position and posture information of the autonomous mobile equipment obtained through positioning and the real-time map, and driving the autonomous mobile equipment to move according to the traveling route.
Further, after the first accurate positioning is performed on the autonomous mobile device by using the SLAM algorithm according to the first initial pose and a real-time map is constructed, the method further includes:
and if the map updating condition is determined to be met, optimizing the error accumulated in the real-time map construction process by adopting a nonlinear least square method so as to update the real-time map.
In a second aspect, an embodiment of the present invention further provides a positioning apparatus applied to an autonomous mobile device, where the apparatus includes:
the pose acquisition module is used for acquiring estimated pose information of the autonomous mobile equipment in real time to serve as a first initial pose;
the SLAM positioning module is used for carrying out first accurate positioning on the autonomous mobile equipment by adopting an SLAM algorithm according to the first initial pose;
a first updating module, configured to, if it is determined that the first precise positioning of the autonomous mobile apparatus fails, perform a re-positioning of the autonomous mobile apparatus using at least one positioning algorithm based on the estimated pose information to update the first initial pose, and return to performing a precise positioning of the autonomous mobile apparatus using a SLAM algorithm according to the first initial pose.
Further, the first updating module includes:
the AMCL positioning sub-module is used for taking the estimated pose information as a second initial pose and performing second accurate positioning on the autonomous mobile equipment by adopting a self-adaptive Monte Carlo positioning AMCL algorithm according to the second initial pose;
and the first pose updating submodule is used for taking the pose information of the autonomous mobile equipment obtained by positioning as the updated first initial pose if the second accurate positioning of the autonomous mobile equipment is determined to be successful.
Further, the first updating module further includes:
a global positioning sub-module, configured to, after taking the estimated pose information as a second initial pose and performing second accurate positioning on the autonomous mobile device by using an AMCL algorithm according to the second initial pose, perform third accurate positioning on the autonomous mobile device by using a global positioning algorithm according to the estimated pose information if it is determined that the second accurate positioning on the autonomous mobile device fails;
and the second pose updating submodule is used for taking the pose information of the autonomous mobile equipment obtained by positioning as the updated second initial pose if the third accurate positioning of the autonomous mobile equipment is determined to be successful, returning to execute the second accurate positioning of the autonomous mobile equipment by adopting an AMCL algorithm according to the second initial pose.
Further, the first updating module further includes:
and the alarm prompting submodule is used for performing positioning failure alarm prompting if determining that the third accurate positioning of the autonomous mobile equipment fails after the autonomous mobile equipment is positioned by adopting a global positioning algorithm according to the estimated pose information.
Further, the pose acquisition module is specifically configured to:
acquiring data information acquired by at least one laser radar arranged on the autonomous mobile equipment in real time;
and acquiring estimated pose information of the autonomous mobile equipment by adopting a milemeter pose estimation method according to the data information.
Further, the SLAM location module is specifically configured to:
according to the first initial pose, carrying out first accurate positioning on the autonomous mobile equipment by adopting an SLAM algorithm, and constructing a real-time map;
correspondingly, the device further comprises:
and the motion control module is used for planning a traveling route of the autonomous mobile equipment according to the position and pose information of the autonomous mobile equipment obtained by positioning and the real-time map and driving the autonomous mobile equipment to move according to the traveling route if the autonomous mobile equipment is determined to be successfully positioned by adopting a SLAM algorithm according to the first initial position and the first accurate positioning of the autonomous mobile equipment.
Further, the apparatus further comprises:
and the map optimization module is used for optimizing the error accumulated in the real-time map construction process by adopting a nonlinear least square method to update the real-time map if the map update condition is met after the autonomous mobile equipment is accurately positioned by adopting an SLAM algorithm according to the first initial pose and the real-time map is constructed.
In a third aspect, an embodiment of the present invention further provides an autonomous mobile apparatus, where the autonomous mobile apparatus includes:
one or more processors;
a memory for storing one or more programs;
when executed by the one or more processors, cause the one or more processors to implement a positioning method applied to an autonomous mobile device as in any of the embodiments of the invention.
In a fourth aspect, the present invention further provides a computer-readable storage medium, on which a computer program is stored, where the computer program is executed by a processor to implement the positioning method applied to an autonomous mobile apparatus according to any one of the embodiments of the present invention.
According to the embodiment of the invention, the estimated pose information of the autonomous mobile equipment is acquired in real time to serve as the first initial pose, the SLAM algorithm is adopted to carry out first accurate positioning on the autonomous mobile equipment according to the first initial pose, if the first accurate positioning on the autonomous mobile equipment is determined to fail, at least one positioning algorithm is adopted to carry out re-positioning on the autonomous mobile equipment based on the estimated pose information so as to update the first initial pose, the SLAM algorithm is continuously adopted to carry out accurate positioning on the autonomous mobile equipment according to the updated first initial pose, the advantage that other positioning algorithms are adopted to carry out re-positioning when the SLAM positioning fails is utilized, the problem of poor positioning stability caused by the adoption of a single positioning algorithm in the prior art is solved, and the effect of improving the positioning stability of the autonomous mobile equipment is realized.
Drawings
Fig. 1 is a flowchart illustrating a positioning method applied to an autonomous mobile device according to an embodiment of the present invention;
fig. 2a is a flowchart illustrating a positioning method applied to an autonomous mobile device according to a second embodiment of the present invention;
fig. 2b is a schematic view of a complete flow chart of a positioning method applied to an autonomous mobile device according to a second embodiment of the present invention;
fig. 3 is a schematic structural diagram of a positioning apparatus applied to an autonomous mobile device according to a third embodiment of the present invention;
fig. 4 is a schematic structural diagram of an autonomous mobile device according to a fourth embodiment of the present invention.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings and examples. It is to be understood that the specific embodiments described herein are merely illustrative of the invention and are not limiting of the invention. It should be further noted that, for the convenience of description, only some of the structures related to the present invention are shown in the drawings, not all of the structures.
Example one
Fig. 1 is a flowchart illustrating a positioning method applied to an autonomous mobile device according to an embodiment of the present invention. The method is applicable to the situation that autonomous mobile equipment such as an automatic guided vehicle and the like autonomously positions the self, and can be executed by a positioning device applied to the autonomous mobile equipment, wherein the positioning device can be composed of hardware and/or software and can be generally integrated in the autonomous mobile equipment such as the automatic guided vehicle and the like. The method specifically comprises the following steps:
and S110, acquiring estimated pose information of the autonomous mobile equipment in real time to serve as a first initial pose.
In this embodiment, the autonomous mobile device may be an unmanned, automatically positionable and navigable mobile device, such as an automated guided vehicle AGV. The estimated pose information may be roughly estimated position information and attitude information, and specifically, the autonomous mobile device may perform real-time rough positioning during the moving process to obtain the estimated pose information of the current autonomous mobile device. It should be noted that the poses mentioned in the embodiments refer to positions and postures, and are not described in detail below.
For example, the obtained estimated pose information may be used as a first initial pose, so as to further perform accurate positioning of an SLAM (Simultaneous Localization and Mapping) algorithm by using the first initial pose in subsequent steps, and perform positioning by using other more accurate algorithms when the positioning fails, so as to update the first initial pose, so that the first initial pose is more accurate, thereby reducing a failure rate of SLAM positioning and improving positioning stability of the autonomous mobile device.
Optionally, obtaining the estimated pose information of the autonomous mobile device in real time includes: acquiring data information acquired by at least one laser radar arranged on the autonomous mobile equipment in real time; and acquiring estimated pose information of the autonomous mobile equipment by adopting a milemeter pose estimation method according to the data information.
In this embodiment, at least one lidar may be disposed on an autonomous mobile device, such as an AGV vehicle body. The autonomous mobile device can rely on the at least one laser radar to sense surrounding objects for positioning, specifically, one laser radar can collect a group of data information, at least one laser radar can collect at least one group of data information, and estimated pose information of the autonomous mobile device can be obtained according to the at least one group of data information. The data collected by the laser radar can be specifically distance data, and the data collected by the laser radar can be converted into data available for positioning by converting the distance data into point cloud data in a position coordinate form. Specifically, when a plurality of laser radars are arranged, that is, when a plurality of sets of data information are acquired, the distance data can be converted into point cloud data, and then the point cloud data can be matched and spliced to obtain point cloud data with 360 degrees and no dead angle, so that the positioning accuracy can be improved.
For example, an odometer pose estimation method may be used to obtain estimated pose information for the autonomous mobile device based on at least one set of data information collected by at least one lidar. Among them, the odometer pose estimation method may be a method of estimating a change in the position of an object with time using data obtained from a sensor (e.g., an encoder or an inertial navigation sensor IMU). Specifically, the odometer can acquire the estimated pose information in the following two ways: one is from the encoder installed on motor and wheel, the encoder will trigger the fixed number of counting marks (usually there will be several hundreds or thousands) per revolution, thus record how many corresponding wheel turns, add the diameter and wheel interval of the wheel known in advance, the encoder can convert the data recorded into the distance that the wheel travels expressed by "meters", or the angle that the wheel turns expressed by "radian"; the other is to obtain data from the IMU (e.g., integrating a three-axis accelerometer and a three-axis gyroscope), the accelerometer integrates to obtain velocity, the further integration to obtain position, the gyroscope integrates to obtain angular velocity, and the further integration to obtain attitude direction. The estimated location method used in this embodiment is a process of deriving the current location from a previously known location and the estimated change in velocity over time.
And S120, according to the first initial pose, performing first accurate positioning on the autonomous mobile equipment by adopting an SLAM algorithm.
The SLAM algorithm used in this embodiment may be, for example, a Hector SLAM. Wherein, the working principle of the Hector SLAM is as follows: a grid map is adopted to represent any environment of the real world, and a local search (Gauss-Newton gradient search) and a global search matching (multi-resolution map matching) are combined to determine a reliable pose and a map in a short time.
Specifically, the autonomous mobile device may be provided with an SLAM module, for example, point cloud data serving as a first initial pose may be input to the SLAM module, and a Hector SLAM algorithm is used to perform first accurate positioning on the autonomous mobile device, so as to obtain accurate pose information. The SLAM module accurately locates autonomous mobile devices by matching the acquired lidar data for each frame to a map.
Optionally, performing first accurate positioning on the autonomous mobile device by using an SLAM algorithm according to the first initial pose, including: and according to the first initial pose, carrying out first accurate positioning on the autonomous mobile equipment by adopting an SLAM algorithm, and constructing a real-time map.
Correspondingly, after the autonomous mobile device is accurately positioned by the SLAM algorithm according to the first initial pose, the method further comprises the following steps: and if the first accurate positioning of the autonomous mobile equipment is determined to be successful, planning a traveling route of the autonomous mobile equipment according to the position and posture information of the autonomous mobile equipment obtained through positioning and a real-time map, and driving the autonomous mobile equipment to move according to the traveling route.
For example, the SLAM module may construct a real-time map of a location where the autonomous mobile device passes while performing the first accurate positioning on the autonomous mobile device, so that when it is determined that the first accurate positioning on the autonomous mobile device is successful, on the premise of avoiding an obstacle, a travel route of the mobile device may be automatically planned according to the real-time map and pose information obtained through the first accurate positioning, and a movement direction and a movement speed of the control device may be controlled, and the driving device may move according to the planned route. The mode of determining whether the first accurate positioning of the autonomous mobile device is successful may be whether the pose information of the autonomous mobile device can be acquired through a SLAM algorithm, if the pose information can be acquired, it may be determined that the first accurate positioning of the autonomous mobile device is successful, otherwise, it may be determined that the first accurate positioning of the autonomous mobile device is failed.
Specifically, a motion control module may be provided on the autonomous mobile device, and configured to execute the motion control method, control the speed and pose (including X-axis, Y-axis coordinates and an in-place angle) at which the device reaches the target position, and plan an obstacle avoidance logic corresponding to the device path position, according to the predetermined route, the current device position, and the preset in-place accuracy.
Optionally, after performing first accurate positioning on the autonomous mobile device by using an SLAM algorithm according to the first initial pose and constructing a real-time map, the method further includes: and if the map updating condition is determined to be met, optimizing the error accumulated in the real-time map construction process by adopting a nonlinear least square method so as to update the real-time map.
Because the SLAM module only has front-end scan matching and does not have a process of back-end map optimization, when some scene maps (for example, a large space map loop) are established, the SLAM module is easily affected by local error accumulation, and the map establishing effect is not ideal, therefore, in the map establishing process, the back end based on the map optimization can be introduced to solve the problem of the left-over local error accumulation. For example, under the condition that a map is constructed for the first time or the map needs to be updated, a map optimization module can be arranged at the rear end of the SLAM module to optimize the pose and the map information after long-time incremental scanning and matching, so that the map accuracy is improved, and finally the positioning and navigation accuracy of the autonomous mobile equipment is higher.
The scene that meets the map updating condition is determined, for example, the map may be first constructed, or a map updating instruction sent by a user is received, or a preset updating cycle time is reached, which is not limited herein. Illustratively, a graph theory mode can be used for representing the SLAM process of the autonomous mobile device, specifically, the pose of the device is represented by nodes, the space constraint relation between the nodes is represented by connecting lines between the nodes, errors are accumulated in the device graph building process, the errors accumulated in the graph building process are optimized through a nonlinear least square method, namely all interframe constraints are considered while optimizing, and iterative linearization solution is used.
And S130, if the first accurate positioning of the autonomous mobile equipment is determined to fail, based on the estimated pose information, adopting at least one positioning algorithm to perform positioning again on the autonomous mobile equipment so as to update the first initial pose, returning to execute the accurate positioning of the autonomous mobile equipment according to the first initial pose and adopting an SLAM algorithm.
Illustratively, if it is determined that the first accurate positioning of the autonomous mobile device fails, for example, the corresponding accurate pose information is not obtained by using the SLAM algorithm, based on the estimated pose information, the autonomous mobile device is re-positioned by using at least one positioning algorithm other than the SLAM algorithm, and the pose information obtained by using the other positioning algorithm is input to the SLAM module again as the updated first initial pose information, so that the SLAM module continues to perform accurate positioning of the autonomous mobile device by using the SLAM algorithm according to the updated first initial pose, thereby improving the positioning success rate of the autonomous mobile device and achieving the effect of improving the positioning stability of the autonomous mobile device.
The at least one positioning algorithm other than the SLAM algorithm includes, but is not limited to, an AMCL (Adaptive Monte Carlo positioning) algorithm, a global positioning algorithm, and the like, and is not limited herein.
According to the technical scheme of the embodiment, estimated pose information of the autonomous mobile equipment is obtained in real time to serve as a first initial pose, the SLAM algorithm is adopted to perform first accurate positioning on the autonomous mobile equipment according to the first initial pose, if it is determined that the first accurate positioning on the autonomous mobile equipment fails, at least one positioning algorithm is adopted to perform re-positioning on the autonomous mobile equipment based on the estimated pose information so as to update the first initial pose, the SLAM algorithm is continuously adopted to perform accurate positioning on the autonomous mobile equipment according to the updated first initial pose, the advantage that other positioning algorithms are adopted to perform re-positioning when the SLAM positioning fails is utilized, the problem that positioning stability is poor due to the fact that a single positioning algorithm is adopted in the prior art is solved, and the effect of improving the positioning stability of the autonomous mobile equipment is achieved.
Example two
Fig. 2a is a flowchart illustrating a positioning method applied to an autonomous mobile device according to a second embodiment of the present invention. The present embodiment is optimized based on the above embodiments, and provides a preferable positioning method applied to an autonomous mobile device, specifically, the method further includes, based on the estimated pose information, performing a relocation on the autonomous mobile device by using at least one positioning algorithm to update the first initial pose, and further includes: taking the estimated pose information as a second initial pose, and performing second accurate positioning on the autonomous mobile equipment by adopting an AMCL algorithm according to the second initial pose; and if the second accurate positioning of the autonomous mobile equipment is determined to be successful, the position and posture information of the autonomous mobile equipment obtained through positioning is used as the updated first initial position and posture. The method specifically comprises the following steps:
and S210, acquiring estimated pose information of the autonomous mobile equipment in real time to serve as a first initial pose.
And S220, performing first accurate positioning on the autonomous mobile equipment by adopting an SLAM algorithm according to the first initial pose.
And S230, if the first accurate positioning of the autonomous mobile equipment is determined to fail, taking the estimated pose information as a second initial pose, and performing second accurate positioning on the autonomous mobile equipment by adopting an AMCL algorithm according to the second initial pose.
On the basis of the above embodiment, if the estimated pose information obtained by estimation is accurate pose information, the estimated pose information may be directly used as an initial pose, i.e., a first initial pose, required by the SLAM module for performing accurate positioning, so as to obtain an ideal positioning result, but in reality, when the estimated pose information is used as a coarse positioning result provided by the sensor, there may be drift and an accumulated error that cannot be ignored (e.g., an accumulated error due to flatness of the ground), and therefore, there may be a case where the SLAM module cannot perform accurate positioning according to the estimated pose information.
In view of the above problems, in the present embodiment, when it is determined that the first precise positioning on the autonomous mobile device fails, the AMCL algorithm may be used to perform secondary positioning on the autonomous mobile device, so as to reduce the failure rate of positioning. Specifically, the estimated pose information is used as a second initial pose, and an AMCL algorithm is adopted to perform second accurate positioning on the autonomous mobile equipment according to the second initial pose. The AMCL algorithm is more accurate than the SLAM, and certainly, the higher the calculation memory required to be consumed, so that the AMCL algorithm can be adopted for positioning when the positioning of the SLAM algorithm fails.
Specifically, the autonomous mobile device may be provided with an AMCL module, and for example, the estimated pose information may be used as a second initial pose and input to the AMCL module, and the AMCL module performs initial positioning according to the estimated pose information and then performs accurate positioning in the constructed map by using a particle filtering method.
And S240, if the second accurate positioning of the autonomous mobile equipment is determined to be successful, the position and posture information of the autonomous mobile equipment obtained through positioning is used as the updated first initial position and posture, the execution is returned according to the first initial position and the SLAM algorithm is adopted to carry out the first accurate positioning on the autonomous mobile equipment.
In this embodiment, if it is determined that the second accurate positioning of the autonomous mobile apparatus is successful, that is, the pose information of the autonomous mobile apparatus can be acquired by using the AMCL algorithm, the pose information is issued to the SLAM module as the updated first initial pose, so that the SLAM module continues to perform the first accurate positioning of the autonomous mobile apparatus according to the updated first initial pose. Because the AMCL algorithm is more accurate than the SLAM algorithm, the pose information obtained when the second accurate positioning is successful is used as the first initial pose, so that the first accurate positioning can be ensured to be successful, the positioning success rate of the SLAM module is improved, and the positioning stability is improved.
Optionally, after the estimating pose information is used as a second initial pose and an AMCL algorithm is used to perform a second accurate positioning on the autonomous mobile device according to the second initial pose, the method further includes: if the second accurate positioning of the autonomous mobile equipment is determined to fail, performing third accurate positioning on the autonomous mobile equipment by adopting a global positioning algorithm according to the estimated pose information; and if the third accurate positioning of the autonomous mobile equipment is determined to be successful, the position and posture information of the autonomous mobile equipment obtained through positioning is used as the updated second initial position and is returned to execute the second accurate positioning of the autonomous mobile equipment by adopting an AMCL algorithm according to the second initial position and posture.
For example, if it is determined that the second accurate positioning of the autonomous mobile device fails, that is, if the AMCL algorithm is adopted or the pose information of the autonomous mobile device cannot be acquired, the global positioning algorithm may be adopted to perform positioning again on the autonomous mobile device, so as to reduce the failure rate of positioning. Specifically, according to the estimated pose information, a global positioning algorithm is adopted to carry out third accurate positioning on the autonomous mobile equipment. The global positioning algorithm is more accurate than the AMCL algorithm and the SLAM algorithm, and certainly, the required consumed operation memory is higher, so that the global positioning algorithm can be adopted for positioning when the positioning of both the SLAM algorithm and the AMCL algorithm fails.
Specifically, the autonomous mobile device may be provided with a global positioning module, for example, estimated pose information may be input to the global positioning module, and a multi-resolution pixel-accurate scanning matching method is adopted in the global positioning module, so that accumulation of local errors may be further reduced, and a positioning success rate may be improved.
Illustratively, if it is determined that the third accurate positioning of the autonomous mobile device is successful, that is, the pose information of the autonomous mobile device can be acquired by using the global positioning algorithm, the pose information is used as the updated second initial pose and is issued to the AMCL module, so that the AMCL module continues to perform the second accurate positioning of the autonomous mobile device according to the updated second initial pose, and the pose information obtained by the positioning of the AMCL module is used as the updated first initial pose and is issued to the SLAM module, so that the SLAM module continues to perform the first accurate positioning of the autonomous mobile device according to the updated first initial pose. Because the global positioning algorithm is more accurate than the AMCL algorithm and the SLAM algorithm, the pose information obtained when the third accurate positioning is successful is used as the second initial pose, so that the second accurate positioning can be ensured to be successful, the first accurate positioning can be ensured to be successful, the positioning success rate of the SLAM module is improved, and the positioning stability is improved.
Optionally, after the autonomous mobile device is located by using a global positioning algorithm according to the estimated pose information, the method further includes: and if the third accurate positioning of the autonomous mobile equipment is determined to fail, performing positioning failure alarm prompting.
Illustratively, if it is determined that the third accurate positioning of the autonomous mobile device fails, that is, the pose information of the autonomous mobile device cannot be acquired by using the global positioning algorithm, indicating that the autonomous mobile device cannot be positioned, a positioning failure alarm prompt is performed to remind a worker to intervene to check the failure reason. The alarm prompt includes but is not limited to a logo prompt, a text type prompt and/or a voice type prompt.
Of course, after the third accurate positioning fails, other positioning algorithms more accurate than the global positioning algorithm may be further set to continue positioning the autonomous mobile device, and the positioning process and logic are similar to those of the first accurate positioning, the second accurate positioning, and the third accurate positioning, and are not described herein again.
In the technical scheme of this embodiment, on the basis of the above embodiment, when it is determined that the first accurate positioning of the autonomous mobile device is failed, the estimated pose information is used as the second initial pose, the AMCL algorithm is used for performing the second accurate positioning on the autonomous mobile device according to the second initial pose, after it is determined that the second accurate positioning on the autonomous mobile device is successful, the pose information of the autonomous mobile device obtained by positioning is used as the updated first initial pose, and the first accurate positioning is performed on the autonomous mobile device according to the first initial pose by returning to the execution, and the SLAM algorithm is used for performing the first accurate positioning on the autonomous mobile device.
Based on the above embodiments, as a complete example, as shown in fig. 2b, the positioning method applied to the autonomous mobile device may specifically include the following steps:
s501, obtaining estimated pose information of the autonomous mobile equipment in real time to serve as a first initial pose.
S502, according to the first initial pose, carrying out first accurate positioning on the autonomous mobile equipment by adopting an SLAM algorithm, and constructing a real-time map.
S503, determining whether the first accurate positioning of the autonomous mobile equipment is successful, if so, executing S504, and if not, executing S507.
S504, determining whether a map updating condition is met, and if so, executing S505; if not, go to S506.
And S505, optimizing the error accumulated in the real-time map construction process by adopting a nonlinear least square method so as to update the real-time map.
S506, planning a traveling route of the autonomous mobile equipment according to the position and posture information of the autonomous mobile equipment obtained through positioning and a real-time map, and driving the autonomous mobile equipment to move according to the traveling route.
And S507, taking the estimated pose information as a second initial pose, and performing second accurate positioning on the autonomous mobile equipment by adopting an AMCL algorithm according to the second initial pose.
S508, whether the second accurate positioning of the autonomous mobile equipment is successful is determined, and if yes, S509 is executed; if not, go to S510.
And S509, taking the position and posture information of the autonomous mobile equipment obtained through positioning as the updated first initial position and posture, and returning to execute the S502.
And S510, performing third accurate positioning on the autonomous mobile equipment by adopting a global positioning algorithm according to the estimated pose information.
S511, determining whether the third accurate positioning of the autonomous mobile equipment is successful, if so, executing S512; if not, S513 is executed.
And S512, taking the position and posture information of the autonomous mobile equipment obtained by positioning as an updated second initial position and posture, and returning to execute S507.
And S513, carrying out positioning failure alarm prompt.
EXAMPLE III
Fig. 3 is a schematic structural diagram of a positioning apparatus applied to an autonomous mobile device according to a third embodiment of the present invention. Referring to fig. 3, the positioning apparatus applied to the autonomous mobile device includes: the pose acquisition module 310, the SLAM positioning module 320, and the first update module 330 are described in detail below.
A pose acquisition module 310, configured to acquire estimated pose information of the autonomous mobile apparatus in real time as a first initial pose;
the SLAM positioning module 320 is used for performing first accurate positioning on the autonomous mobile equipment by adopting an SLAM algorithm according to the first initial pose;
a first updating module 330, configured to, if it is determined that the first precise positioning of the autonomous mobile apparatus fails, perform a re-positioning of the autonomous mobile apparatus using at least one positioning algorithm based on the estimated pose information to update the first initial pose, and return to performing a precise positioning of the autonomous mobile apparatus using a SLAM algorithm according to the first initial pose.
Optionally, the first updating module 330 may specifically include:
the AMCL positioning sub-module is used for taking the estimated pose information as a second initial pose and performing second accurate positioning on the autonomous mobile equipment by adopting a self-adaptive Monte Carlo positioning AMCL algorithm according to the second initial pose;
and the first pose updating submodule is used for taking the pose information of the autonomous mobile equipment obtained by positioning as the updated first initial pose if the second accurate positioning of the autonomous mobile equipment is determined to be successful.
Optionally, the first updating module 330 may specifically further include:
a global positioning sub-module, configured to, after taking the estimated pose information as a second initial pose and performing second accurate positioning on the autonomous mobile device by using an AMCL algorithm according to the second initial pose, perform third accurate positioning on the autonomous mobile device by using a global positioning algorithm according to the estimated pose information if it is determined that the second accurate positioning on the autonomous mobile device fails;
and the second pose updating submodule is used for taking the pose information of the autonomous mobile equipment obtained by positioning as the updated second initial pose if the third accurate positioning of the autonomous mobile equipment is determined to be successful, returning to execute the second accurate positioning of the autonomous mobile equipment by adopting an AMCL algorithm according to the second initial pose.
Optionally, the first updating module 330 may specifically further include:
and the alarm prompting submodule is used for performing positioning failure alarm prompting if determining that the third accurate positioning of the autonomous mobile equipment fails after the autonomous mobile equipment is positioned by adopting a global positioning algorithm according to the estimated pose information.
Optionally, the pose acquisition module 310 may be specifically configured to:
acquiring data information acquired by at least one laser radar arranged on the autonomous mobile equipment in real time;
and acquiring estimated pose information of the autonomous mobile equipment by adopting a milemeter pose estimation method according to the data information.
Optionally, the SLAM locating module 320 may be specifically configured to:
according to the first initial pose, carrying out first accurate positioning on the autonomous mobile equipment by adopting an SLAM algorithm, and constructing a real-time map;
correspondingly, the device may further include:
and the motion control module is used for planning a traveling route of the autonomous mobile equipment according to the position and pose information of the autonomous mobile equipment obtained by positioning and the real-time map and driving the autonomous mobile equipment to move according to the traveling route if the autonomous mobile equipment is determined to be successfully positioned by adopting a SLAM algorithm according to the first initial position and the first accurate positioning of the autonomous mobile equipment.
Optionally, the apparatus may further include:
and the map optimization module is used for optimizing the error accumulated in the real-time map construction process by adopting a nonlinear least square method to update the real-time map if the map update condition is met after the autonomous mobile equipment is accurately positioned by adopting an SLAM algorithm according to the first initial pose and the real-time map is constructed.
The product can execute the method provided by any embodiment of the invention, and has corresponding functional modules and beneficial effects of the execution method.
Example four
Fig. 4 is a schematic structural diagram of an autonomous mobile device according to a fourth embodiment of the present invention, and as shown in fig. 4, the autonomous mobile device according to the present embodiment includes: a processor 41 and a memory 42. The number of the processors in the autonomous mobile device may be one or more, and fig. 4 illustrates one processor 41, the processor 41 and the memory 42 in the autonomous mobile device may be connected by a bus or other means, and fig. 4 illustrates the connection by a bus.
The processor 41 of the autonomous mobile apparatus in this embodiment integrates the positioning apparatus applied to the autonomous mobile apparatus provided in the above embodiment. Further, the memory 42 of the autonomous mobile device may be used as a computer readable storage medium for storing one or more programs, such as software programs, computer executable programs, and modules, corresponding to the program instructions/modules of the positioning method applied to the autonomous mobile device according to the embodiment of the present invention (for example, the modules applied to the positioning apparatus of the autonomous mobile device shown in FIG. 3 include the pose acquisition module 310, the SLAM positioning module 320, and the first update module 330). The processor 41 executes various functional applications and data processing of the autonomous mobile device by executing software programs, instructions and modules stored in the memory 42, that is, implements the positioning method applied to the autonomous mobile device in the above-described method embodiment.
The memory 42 may include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required for at least one function; the storage data area may store data created according to the use of the autonomous mobile device, and the like. Further, the memory 42 may include high speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other non-volatile solid state storage device. In some examples, memory 42 may further include memory located remotely from processor 41, which may be connected to the autonomous mobile device through a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
And, when the one or more programs included in the above-mentioned autonomous mobile apparatus are executed by the one or more processors 41, the programs perform the following operations:
acquiring estimated pose information of the autonomous mobile equipment in real time to serve as a first initial pose; according to the first initial pose, performing first accurate positioning on the autonomous mobile equipment by adopting a synchronous positioning and mapping SLAM algorithm; and if determining that the first accurate positioning of the autonomous mobile equipment fails, based on the estimated pose information, adopting at least one positioning algorithm to perform re-positioning on the autonomous mobile equipment so as to update the first initial pose, returning to execute accurate positioning on the autonomous mobile equipment according to the first initial pose by adopting a SLAM algorithm.
EXAMPLE five
An embodiment of the present invention further provides a computer-readable storage medium, on which a computer program is stored, where the computer program, when being applied to a positioning apparatus of an autonomous mobile device, implements a positioning method applied to the autonomous mobile device, where the method includes: acquiring estimated pose information of the autonomous mobile equipment in real time to serve as a first initial pose; according to the first initial pose, performing first accurate positioning on the autonomous mobile equipment by adopting a synchronous positioning and mapping SLAM algorithm; and if determining that the first accurate positioning of the autonomous mobile equipment fails, based on the estimated pose information, adopting at least one positioning algorithm to perform re-positioning on the autonomous mobile equipment so as to update the first initial pose, returning to execute accurate positioning on the autonomous mobile equipment according to the first initial pose by adopting a SLAM algorithm.
Of course, the computer-readable storage medium stored thereon when the computer program is executed is not limited to implement the method operations described above, and may also implement the related operations in the positioning method applied to the autonomous mobile device, which are provided by any embodiment of the present invention.
From the above description of the embodiments, it is obvious for those skilled in the art that the present invention can be implemented by software and necessary general hardware, and certainly, can also be implemented by hardware, but the former is a better embodiment in many cases. Based on such understanding, the technical solutions of the present invention may be embodied in the form of a software product, which can be stored in a computer-readable storage medium, such as a floppy disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a FLASH Memory (FLASH), a hard disk or an optical disk of a computer, and includes several instructions for enabling a computer device (which may be a personal computer, a server, or a network device) to execute the methods according to the embodiments of the present invention.
It should be noted that, in the above embodiment of the positioning apparatus applied to the autonomous mobile device, the included units and modules are merely divided according to the functional logic, but are not limited to the above division as long as the corresponding functions can be implemented; in addition, specific names of the functional units are only for convenience of distinguishing from each other, and are not used for limiting the protection scope of the present invention.
It is to be noted that the foregoing is only illustrative of the preferred embodiments of the present invention and the technical principles employed. It will be understood by those skilled in the art that the present invention is not limited to the particular embodiments described herein, but is capable of various obvious changes, rearrangements and substitutions as will now become apparent to those skilled in the art without departing from the scope of the invention. Therefore, although the present invention has been described in greater detail by the above embodiments, the present invention is not limited to the above embodiments, and may include other equivalent embodiments without departing from the spirit of the present invention, and the scope of the present invention is determined by the scope of the appended claims.
Claims (7)
1. A positioning method applied to an autonomous mobile device, comprising:
acquiring estimated pose information of the autonomous mobile equipment in real time to serve as a first initial pose; wherein, obtain autonomic mobile device's estimation position appearance information in real time, include:
acquiring data information acquired by at least one laser radar arranged on the autonomous mobile equipment in real time;
acquiring estimated pose information of the autonomous mobile equipment by adopting a milemeter pose estimation method according to the data information; the odometer pose estimation method is used for deducing the current position according to the previously known position and the estimated variation of the speed along with time;
according to the first initial pose, performing first accurate positioning on the autonomous mobile equipment by adopting a synchronous positioning and mapping SLAM algorithm;
if determining that the first accurate positioning of the autonomous mobile equipment fails, based on the estimated pose information, adopting at least one positioning algorithm to perform re-positioning on the autonomous mobile equipment so as to update the first initial pose, returning to execute accurate positioning on the autonomous mobile equipment according to the first initial pose by adopting a SLAM algorithm;
wherein relocating the autonomous mobile device based on the estimated pose information using at least one positioning algorithm to update the first initial pose comprises:
taking the estimated pose information as a second initial pose, and performing second accurate positioning on the autonomous mobile equipment by adopting a self-adaptive Monte Carlo positioning AMCL algorithm according to the second initial pose;
if the second accurate positioning of the autonomous mobile equipment is determined to be successful, the position and posture information of the autonomous mobile equipment obtained through positioning is used as the updated first initial position and posture;
if the second accurate positioning of the autonomous mobile equipment is determined to fail, performing third accurate positioning on the autonomous mobile equipment by adopting a global positioning algorithm according to the estimated pose information;
and if the third accurate positioning of the autonomous mobile equipment is determined to be successful, the pose information of the autonomous mobile equipment obtained by positioning is used as the updated second initial pose, and the AMCL algorithm is adopted to perform the second accurate positioning of the autonomous mobile equipment according to the second initial pose.
2. The method of claim 1, further comprising, after locating the autonomous mobile device with a global positioning algorithm based on the estimated pose information:
and if the third accurate positioning of the autonomous mobile equipment is determined to fail, performing positioning failure alarm prompting.
3. The method of claim 1, wherein the first fine positioning of the autonomous mobile device with the SLAM algorithm according to the first initial pose comprises:
according to the first initial pose, carrying out first accurate positioning on the autonomous mobile equipment by adopting an SLAM algorithm, and constructing a real-time map;
correspondingly, after the first accurate positioning of the autonomous mobile device is performed by using the SLAM algorithm according to the first initial pose, the method further includes:
if the first accurate positioning of the autonomous mobile equipment is determined to be successful, planning a traveling route of the autonomous mobile equipment according to the position and posture information of the autonomous mobile equipment obtained through positioning and the real-time map, and driving the autonomous mobile equipment to move according to the traveling route.
4. The method of claim 3, wherein after performing a first fine positioning of the autonomous mobile device using a SLAM algorithm and constructing a real-time map according to the first initial pose, further comprising:
and if the map updating condition is determined to be met, optimizing the error accumulated in the real-time map construction process by adopting a nonlinear least square method so as to update the real-time map.
5. A positioning apparatus for use with an autonomous mobile device, comprising:
the system comprises a pose acquisition module, a first detection module and a second detection module, wherein the pose acquisition module is used for acquiring estimated pose information of the autonomous mobile equipment in real time to serve as a first initial pose, and is specifically used for acquiring data information acquired by at least one laser radar arranged on the autonomous mobile equipment in real time; acquiring estimated pose information of the autonomous mobile equipment by adopting a milemeter pose estimation method according to the data information; the odometer pose estimation method is used for deducing the current position according to the previously known position and the estimated variation of the speed along with time;
the SLAM positioning module is used for carrying out first accurate positioning on the autonomous mobile equipment by adopting an SLAM algorithm according to the first initial pose;
a first updating module, configured to, if it is determined that the first precise positioning of the autonomous mobile apparatus fails, perform a re-positioning of the autonomous mobile apparatus using at least one positioning algorithm based on the estimated pose information to update the first initial pose, and return to performing a precise positioning of the autonomous mobile apparatus using a SLAM algorithm according to the first initial pose;
a first update module comprising:
the AMCL positioning sub-module is used for taking the estimated pose information as a second initial pose and performing second accurate positioning on the autonomous mobile equipment by adopting a self-adaptive Monte Carlo positioning AMCL algorithm according to the second initial pose;
a first pose updating submodule, configured to, if it is determined that the second accurate positioning of the autonomous mobile apparatus is successful, take pose information of the autonomous mobile apparatus obtained by the positioning as the updated first initial pose;
the global positioning sub-module is used for carrying out third accurate positioning on the autonomous mobile equipment by adopting a global positioning algorithm according to the estimated pose information if the second accurate positioning on the autonomous mobile equipment is determined to fail;
and the second pose updating submodule is used for taking the pose information of the autonomous mobile equipment obtained by positioning as the updated second initial pose if the third accurate positioning of the autonomous mobile equipment is determined to be successful, returning to execute the second accurate positioning of the autonomous mobile equipment by adopting an AMCL algorithm according to the second initial pose.
6. An autonomous mobile device, the device comprising:
one or more processors;
a memory for storing one or more programs;
when executed by the one or more processors, cause the one or more processors to implement a positioning method as claimed in any one of claims 1-4 as applied to an autonomous mobile device.
7. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out a positioning method applied to an autonomous mobile device as claimed in any one of claims 1 to 4.
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