CN111805532B

Movatterモバイル変換

Info

Publication number: CN111805532B
Application number: CN202010231951.5A
Authority: CN
Inventors: 高雪亚
Original assignee: Individual
Current assignee: Shanghai Dayi Electromechanical Engineering Co ltd
Priority date: 2020-03-27
Filing date: 2020-03-27
Publication date: 2021-11-26
Anticipated expiration: 2040-03-27
Also published as: CN111805532A

Abstract

The invention relates to a cloud computing type robot driving control system, which comprises: the sorting robot main body comprises a driving mechanism, a sorting mechanical structure and an anti-collision mechanism, wherein the driving mechanism is used for controlling the driving direction and speed of the sorting robot main body; the sorting mechanical structure comprises a mechanical arm, a positioner and a cargo storage box; the anti-collision mechanism comprises a plurality of distance measuring radars and a signal generator; and the cloud computing node is used for searching an image area with the shallowest depth of field and the shape similarity of the goods outline exceeding the limit in the storage scene image based on the goods outline. The cloud computing type robot driving control system is compact in design and has a certain intelligent level. Due to the fact that the matched goods of different types can be automatically selected for the sorting robots of different types to be sorted, the goods sorting speed and efficiency of the large warehouse are guaranteed.

Description

Cloud computing type robot drive control system

Technical Field

The invention relates to the field of cloud computing, in particular to a cloud computing type robot driving control system.

Background

The express delivery burst refers to that an express company suddenly receives too many express items, the express company cannot sort the express items in time, even cannot receive the express items, and a large number of express items are left at an initial station or a transfer station. The time to reach the destination is relatively long. 11/2012, large-scale sales promotion of several large e-merchants such as the Tianmao mall, the Taobao and the like becomes a shopping fierce festival, a large number of orders are submitted by consumers, a logistics peak is formed after the fierce festival of shopping, a large number of goods are still accumulated in a logistics warehouse until 13 days and 14 days after twenty-one, express delivery is slowed down and delivered, and the complaint amount of the consumers is increased.

The 'explosion' mainly has two reasons, on one hand, the electronic commerce develops rapidly, but the investment of manpower, infrastructure and the like in the logistics industry cannot catch up with the development speed of the electronic commerce, and partial phenomenon of supply and demand imbalance appears. On the other hand, the delivery capacity is limited due to factors such as shortage of diesel oil supply, and the like, so that the arrival period is prolonged. The vigorous development of the express delivery industry rapidly changes the life and shopping modes of people, and achieves the rapid development of part of enterprises and even industries.

In order to avoid the situation of bin explosion, the rapid sorting operation needs to be performed on the goods in each large-scale bin for storing express goods. At present, although the cloud computing technology is mature, research on application scenarios of the cloud computing technology is still continuously carried out, for example, technical solutions for subdividing the field into large warehouse goods sorting are also required to be supported by the cloud computing technology.

Disclosure of Invention

In order to solve the related technical problems in the prior art, the invention provides a cloud computing type robot driving control system which can intelligently select different shapes of cargo types for different types of sorting robots to carry out on-site sorting on the basis of cloud computing, so that the cargo sorting level of a large warehouse is ensured, and unmanned management of cargo sorting is realized.

Therefore, the invention at least needs to have the following three key points:

(1) the characteristic that different sorting robots sort goods with different shapes is utilized to determine the relative position of each sorting robot to the nearest goods of the type to be sorted according to the corresponding driving strategy, so that the intelligent level of the control of the sorting robots is improved;

(2) the cloud computing mode is adopted to execute the cloud processing of complex steps, so that the local computing burden is effectively reduced;

(3) the sorting robot main body with the customized structure comprises a driving mechanism, a sorting mechanical structure and an anti-collision mechanism, so that sorting processing of different sorting robots for different cargos is realized, and the cargo sorting efficiency of a large warehouse is guaranteed.

According to an aspect of the present invention, there is provided a cloud-computing robot driving control system, the system including:

the sorting robot main body comprises a driving mechanism, a sorting mechanical structure and an anti-collision mechanism, wherein the driving mechanism is used for controlling the driving direction and speed of the sorting robot main body;

the sorting mechanical structure comprises a mechanical arm, a positioner and a cargo storage box, wherein the positioner is connected with the mechanical arm and used for providing positioning information for the mechanical arm to execute sorting operation, and the cargo storage box is used for placing cargos sorted by the mechanical arm from a cargo stack;

the anti-collision mechanism comprises a plurality of distance measuring radars and a signal generator, the distance measuring radars are respectively arranged around the sorting robot main body and are used for measuring the real-time distance between the sorting robot main body and other sorting robot main bodies, and the signal generator is used for sending corresponding running driving signals to the running driving mechanism to control the running driving mechanism to drive the sorting robot main body in the direction of increasing the real-time distance when the received real-time distance is lower than a preset distance threshold value;

the front capturing mechanism is arranged at the front end of the sorting robot main body and is used for capturing image data of a storage scene of a goods pile in front of the sorting robot main body so as to obtain and output a corresponding storage scene image;

the FLASH storage chip is arranged in the sorting robot main body and is used for storing the shape outline of the goods of the corresponding type sorted by the sorting robot main body;

the cloud computing node is connected with the foreground capturing mechanism and the FLASH storage chip through a network and is used for searching an image area with the shallowest depth of field and the shape similarity of the goods outline out of limit in the storage scene image based on the goods outline, and determining the driving direction of the driving mechanism for controlling the sorting robot main body to move to the goods target corresponding to the image area based on the abscissa and the imaging depth of field of the centroid of the image area in the storage scene image;

the driving mechanism is connected with the cloud computing nodes through a network and used for receiving the driving direction determined by the cloud computing nodes so as to execute driving control on the traveling direction of the sorting robot main body;

in the cloud technology node, determining, by the driving mechanism, a driving direction of the sorting robot main body to the goods target corresponding to the image area, based on an abscissa and an imaging depth of field of the centroid of the image area in the storage scene image, includes: the larger the numerical value of the abscissa of the centroid of the image area in the storage scene image is, the more the determined traveling driving mechanism controls the traveling direction of the sorting robot main body to the goods target corresponding to the image area to be inclined to the right.

The cloud computing type robot driving control system is compact in design and has a certain intelligent level. Due to the fact that the matched goods of different types can be automatically selected for the sorting robots of different types to be sorted, the goods sorting speed and efficiency of the large warehouse are guaranteed.

Drawings

Embodiments of the invention will now be described with reference to the accompanying drawings, in which:

fig. 1 is a schematic view of an application scenario of the cloud computing type robot driving control system according to the present invention.

Fig. 2 is a block diagram illustrating a configuration of a cloud computing type robot driving control system according to a first embodiment of the present invention.

Fig. 3 is a block diagram illustrating a configuration of a cloud-computing robot driving control system according to a second embodiment of the present invention.

Detailed Description

Embodiments of the cloud-computing-type robot driving control system of the present invention will be described in detail below with reference to the accompanying drawings.

In the prior art, for some large logistics companies, the warehouse for stacking the goods managed by the logistics companies is large in scale, the goods are sorted one by one only by relying on a manual sorting mode, difficulty is high, efficiency is low, although some logistics companies also adopt the sorting mode of robots, sorting strategies belonging to each type of robots are not formulated, and therefore sorting efficiency and sorting speed cannot be further improved.

In order to overcome the defects, the invention provides a cloud computing type robot driving control system, and the corresponding technical problems can be effectively solved.

Subsequently, the technical contents of the present invention will be further specifically described by using one or more embodiments.

< first embodiment >

Fig. 2 is a block diagram illustrating a configuration of a cloud-computing robot driving control system according to a first embodiment of the present invention, the system including:

< second embodiment >

Fig. 3 is a block diagram illustrating a configuration of a cloud-computing robot driving control system according to a second embodiment of the present invention, the system including:

the time division communication interface is arranged between the cloud computing node and the driving mechanism and used for establishing network connection between the cloud computing node and the driving mechanism through a time division duplex communication link;

in the cloud technology node, determining, by the driving mechanism, a driving direction of the sorting robot main body to the goods target corresponding to the image area, based on an abscissa and an imaging depth of field of the centroid of the image area in the storage scene image, includes: the larger the numerical value of the abscissa of the centroid of the image area in the storage scene image is, the more the determined driving mechanism controls the more right the direction of the sorting robot main body to drive to the goods target corresponding to the image area;

in the cloud technology node, determining, by the driving mechanism, a driving direction of the sorting robot main body to the goods target corresponding to the image area, based on an abscissa and an imaging depth of field of the centroid of the image area in the storage scene image, includes: the larger the imaging depth of field value of the centroid of the image area in the storage scene image is, the more inward the determined driving direction of the driving mechanism controls the sorting robot main body to move towards the goods target corresponding to the image area.

Next, a detailed structure of the cloud computing robot driving control system according to the present invention will be further described.

In the cloud-computing robot drive control system: the determined driving direction of the driving mechanism for driving the sorting robot main body to move towards the goods target corresponding to the image area is as follows: the determined traveling driving mechanism controls the traveling direction of the sorting robot main body towards the goods target corresponding to the image area to be farther away from the position of the sorting robot main body and be perpendicular to the direction of the imaging plane of the front capture mechanism.

In the cloud-computing robot drive control system: in the stored scene image, the value of the abscissa and the value of the ordinate of each pixel point are set by a horizontal coordinate system established by taking the pixel point at the lower left corner in the stored scene image as the origin.

In the cloud-computing robot drive control system: the centroid of the image area is a pixel point in the image area in the stored scene image.

In the cloud-computing robot drive control system: the centroid of the image area is a pixel point in the image area in the stored scene image, and the centroid of the image area comprises: and when the centroid of the image area is not at the position of any pixel point in the stored scene image, correcting the centroid of the image area into the pixel point closest to the centroid of the image area.

In the cloud-computing robot drive control system: the signal generator is connected with the IIC control bus and used for receiving various control instructions sent by the IIC control bus.

In the cloud-computing robot drive control system: the prepositive capturing mechanism is also connected with a clock generator and is used for receiving a timing signal customized for the prepositive capturing mechanism by the clock generator.

In the cloud-computing robot drive control system: the signal generator is realized by adopting an ASIC chip, and the ASIC chip comprises an online programming interface; wherein the pre-capture mechanism and the signal generator are located on the same printed circuit board and share the same circuit supply device; the signal generator is also connected with a parallel data bus and used for receiving data from the parallel data bus and sending the data to the parallel data bus.

Meanwhile, in order to overcome the defects, the invention also builds a cloud computing type robot driving control terminal, and the terminal comprises: a memory and a processor, the processor coupled to the memory;

wherein the memory is used for storing executable instructions of the processor;

wherein the processor is configured to invoke executable instructions in the memory to implement a method of using the cloud computing type robot drive control system as described above to determine a drive strategy for a sorting robot based on the relative position of the sorting robot to its nearest respective type of cargo.

In addition, FLASH memory chips are nonvolatile memories, and blocks of memory cells called blocks can be erased and reprogrammed. The write operation of any FLASH device can only be performed in empty or erased cells, so in most cases, the erase must be performed before the write operation can be performed. While it is simple for a NAND device to perform an erase operation, NOR requires that all bits in the target block be written to 0 before an erase can be performed.

Since erasing NOR devices is performed in blocks of 64-128 KB, the time for performing a write/erase operation is 5s, whereas erasing NAND devices is performed in blocks of 8-32 KB, which requires only 4ms at most to perform the same operation.

The difference in block size when performing erasures further increases the performance gap between NOR and NADN, and statistics show that for a given set of write operations (especially when updating small files), more erase operations must be performed in NOR-based cells.

It should be understood that portions of the present invention may be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, the various steps or methods may be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, any one or combination of the following techniques, which are known in the art, may be used: a discrete logic circuit having a logic gate circuit for implementing a logic function on a data signal, an application specific integrated circuit having an appropriate combinational logic gate circuit, a Programmable Gate Array (PGA), a Field Programmable Gate Array (FPGA), or the like.

It will be understood by those skilled in the art that all or part of the steps carried by the method for implementing the above embodiments may be implemented by hardware related to instructions of a program, which may be stored in a computer readable storage medium, and when the program is executed, the program includes one or a combination of the steps of the method embodiments.

The storage medium mentioned above may be a read-only memory, a magnetic or optical disk, etc. Although embodiments of the present invention have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present invention, and that variations, modifications, substitutions and alterations can be made to the above embodiments by those of ordinary skill in the art within the scope of the present invention.

Claims

1. A cloud computing robot drive control system, comprising:

the cloud computing node is connected with the front capturing mechanism and the FLASH storage chip through a network and is used for searching an image area with the shallowest depth of field and the shape similarity of the goods outline out of limit in the storage scene image based on the goods outline, and determining the driving direction of the driving mechanism for controlling the sorting robot main body to move to the goods target corresponding to the image area based on the abscissa and the imaging depth of field of the centroid of the image area in the storage scene image;

in the cloud computing node, determining, by the driving mechanism, a driving direction of the sorting robot main body to a goods target corresponding to the image area, based on an abscissa and an imaging depth of field of a centroid of the image area in the storage scene image, includes: the larger the numerical value of the abscissa of the centroid of the image area in the storage scene image is, the more the determined driving mechanism controls the more right the direction of the sorting robot main body to drive to the goods target corresponding to the image area;

in the cloud computing node, determining, by the driving mechanism, a driving direction of the sorting robot main body to a goods target corresponding to the image area, based on an abscissa and an imaging depth of field of a centroid of the image area in the storage scene image, includes: the larger the numerical value of the imaging depth of field of the centroid of the image area in the storage scene image is, the more inwards the determined driving direction of the driving mechanism for controlling the sorting robot main body to move towards the goods target corresponding to the image area is;

the determined driving direction of the driving mechanism for driving the sorting robot main body to move towards the goods target corresponding to the image area is as follows: the determined direction in which the traveling driving mechanism controls the sorting robot main body to travel towards the goods target corresponding to the image area is farther away from the position of the sorting robot main body and is perpendicular to the direction of the imaging plane of the front capturing mechanism;

in the stored scene image, the numerical value of the abscissa and the numerical value of the ordinate of each pixel point are set by a horizontal coordinate system established by taking the pixel point at the lower left corner in the stored scene image as an origin;

the centroid of the image area is a pixel point in the image area in the stored scene image;

the centroid of the image area is a pixel point in the image area in the stored scene image, and the centroid of the image area comprises: and when the centroid of the image area is not at the position of any pixel point in the stored scene image, correcting the centroid of the image area into the pixel point closest to the centroid of the image area.

2. A cloud computing robotic drive control system as claimed in claim 1, further comprising:

the signal generator is connected with the IIC control bus and used for receiving various control instructions sent by the IIC control bus.

3. A cloud computing robotic drive control system as claimed in claim 2, further comprising:

the prepositive capturing mechanism is also connected with a clock generator and is used for receiving a timing signal customized for the prepositive capturing mechanism by the clock generator.

4. A cloud computing robotic drive control system as claimed in claim 3, further comprising:

the signal generator is realized by adopting an ASIC chip, and the ASIC chip comprises an online programming interface;

wherein the pre-capture mechanism and the signal generator are located on the same printed circuit board and share the same circuit supply device;

the signal generator is also connected with a parallel data bus and used for receiving data from the parallel data bus and sending the data to the parallel data bus.