CN112348434A - Cloud community takeout full-automatic distribution scheme - Google Patents
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Abstract
The invention discloses a full-automatic distribution scheme for takeout in a clouded community, and relates to the technical field of cloud communication; the method comprises the steps of inputting order distribution information into a cloud end, dividing different meal delivery areas according to the takeout quantity through the cloud end, distributing and delivering food by a delivery vehicle according to the meal delivery areas, communicating the delivery vehicle with the cloud end through a 5G network, receiving the distribution information, initializing by using an ROS navigation system, monitoring the navigation state, replacing the navigation strategy in due time, starting a planner, generating a cost map, calculating a global route from the delivery vehicle to a target position, simultaneously carrying out local obstacle avoidance until the target position is reached, sending a message to an order user, and waiting for the user to unlock the meal delivery vehicle.
Description
Technical Field
The invention discloses a scheme, relates to the technical field of cloud communication, and particularly relates to a full-automatic distribution scheme for takeout in a clouded cell.
Background
With the pace of life increasing, take-out orders have become a part of people's daily lives. The existing food delivery mode is still delivered by riders, but the delivery is difficult to deliver on time due to the fact that most riders are not familiar with unfamiliar communities and influence of environmental factors in the communities and the like.
Disclosure of Invention
Aiming at the problems in the prior art, the invention provides a full-automatic distribution scheme for the takeout in the cloud community, which can deliver the takeout for ordering on time, and based on the characteristics of low delay and high bandwidth of a 5G network, the active obstacle avoidance function is realized by utilizing a laser radar, and the fixed-point navigation of a distribution vehicle is realized by utilizing the ROS navigation technology. Navigation programs of all distribution vehicles can run on the cloud server, so that the running cost of the distribution vehicles is saved, and meanwhile, safety, time and labor are guaranteed.
The specific scheme provided by the invention is as follows:
a full-automatic distribution scheme for cloud community takeout comprises the following steps: recording order distribution information into a cloud end, dividing different meal delivery areas according to the takeout quantity through the cloud end, distributing distribution cars to deliver meals according to the meal delivery areas,
the distribution vehicle is communicated with the cloud through a 5G network, receives distribution information, utilizes an ROS navigation system to initialize, monitors the navigation state, changes the navigation strategy in due time, starts a planner, generates a cost map, calculates the overall route from the distribution vehicle to a target position, carries out local obstacle avoidance at the same time until the target position is reached, sends a message to an order user, and waits for the user to unlock the distribution vehicle for food.
Preferably, in the scheme of the cloud cell takeout full-automatic delivery, a move _ base module in an ROS navigation system is used for scheduling a navigation behavior of a delivery vehicle.
Preferably, the scheduling process in the cloud cell takeout full-automatic delivery scheme is as follows:
starting two planners of global planning and local planning through a Move _ base module, taking charge of global path planning and local path planning, generating a cost map,
calculating a global route from the vehicle to the target position through global path planning,
and planning local obstacle avoidance through local planning.
Preferably, the process of planning local obstacle avoidance in the cloud community takeout full-automatic delivery scheme is as follows:
and obtaining a sampling space of the speed by a kinematic model of the movement of the delivery vehicle, calculating an objective function of each sample in the sampling space to obtain an expected speed, and interpolating to form a track for output.
A full-automatic distribution system for cloud community takeout comprises a communication module, an area division module, an encryption and decryption module and an ROS navigation system,
order information is input into the cloud end, different meal delivery areas are divided by the cloud end according to the takeout quantity, delivery vehicles are distributed to deliver meals according to the meal delivery areas,
the communication module is used for communicating the delivery vehicle with the cloud end through a 5G network and receiving order delivery information of the cloud end, the region division module divides different meal delivery regions according to the takeout quantity through the communication module, the cloud end is obtained by the region division module, the distributed meals of the delivery vehicle are received according to the meal delivery regions,
and the ROS navigation system initializes the distribution vehicle, monitors the navigation state, changes the navigation strategy at proper time, starts a planner, generates a cost map, calculates the global route from the distribution vehicle to the target position, simultaneously carries out local obstacle avoidance until the target position is reached, sends a message to an order user, and waits for the user to unlock the distribution vehicle for food distribution.
Preferably, in the cloud cell takeout full-automatic distribution system, the move _ base module in the ROS navigation system is used for scheduling the navigation behavior of the distribution vehicle.
Preferably, the move _ base module scheduling process in the cloud cell takeout full-automatic delivery system is as follows:
starting two planners of global planning and local planning through a Move _ base module, taking charge of global path planning and local path planning, generating a cost map,
calculating a global route from the vehicle to the target position through global path planning,
and planning local obstacle avoidance through local planning.
Preferably, the process of planning local obstacle avoidance by using local planning through the Move _ base module in the cloud cell takeout full-automatic delivery system is as follows:
and obtaining a sampling space of the speed by a kinematic model of the movement of the delivery vehicle, calculating an objective function of each sample in the sampling space to obtain an expected speed, and interpolating to form a track for output.
The invention provides a full-automatic distribution scheme for cloud community takeout, which has the following advantages compared with the prior art:
1. by means of the 5G network, the navigation efficiency is greatly improved, and the real-time performance and the reliability of automatic navigation are ensured.
2. Take-out delivery personnel need not to get into the district, only need can accomplish the operation of type-in order at the district gate, labour saving and time saving improves delivery efficiency.
3. The automatic navigation program runs on the cloud server, and then the 5G is used for transmitting information and sending instructions, so that the vehicle cost is greatly saved.
4. The community cloud system can divide a plurality of areas according to the takeaway quantity of different areas, and the quantity of delivery vehicles can be adjusted according to the takeaway quantity, so that the vehicle running cost is saved, and the efficiency is improved.
5. All the delivery vehicles can be planned and commanded by the community cloud system in a unified way, so that the cloud computing power is fully utilized, and a large amount of manpower is saved.
6. The user needs to scan the two-dimensional code on the robot to take the takeaway, so that the phenomenon that the takeaway is taken by mistake is prevented.
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FIG. 1 is a schematic flow chart of the scheme of the invention.
Detailed Description
The present invention is further described below in conjunction with the following figures and specific examples so that those skilled in the art may better understand the present invention and practice it, but the examples are not intended to limit the present invention.
The invention provides a full-automatic distribution scheme for takeout in a cloud community, which comprises the following steps: recording order distribution information into a cloud end, dividing different meal delivery areas according to the takeout quantity through the cloud end, distributing distribution cars to deliver meals according to the meal delivery areas,
the distribution vehicle is communicated with the cloud through a 5G network, receives distribution information, utilizes an ROS navigation system to initialize, monitors the navigation state, changes the navigation strategy in due time, starts a planner, generates a cost map, calculates the overall route from the distribution vehicle to a target position, carries out local obstacle avoidance at the same time until the target position is reached, sends a message to an order user, and waits for the user to unlock the distribution vehicle for food.
In order to improve the inconvenience of taking takeouts at ordinary times, take-out dispatchers do not need to enter a cell, and the time for searching for the residence of a user is saved. The distribution vehicle is an intelligent robot, is in communication connection with a cloud system of a cell through a 5G network in the cell and is uniformly scheduled by the cloud system, the distribution vehicle realizes a navigation distribution function based on a Robot Operating System (ROS), and the distribution vehicle has a fixed-point autonomous navigation function.
In specific application, in some embodiments of the present invention, the ROS navigation system in the distribution vehicle is divided into a data collection layer (sensor data collection), a global planning layer (globalplanner), a local planning layer (localplanner), a behavior layer (which gives the current behavior of the vehicle by combining the vehicle state and upper layer instructions), and a controller layer (which communicates with the lower computer). During navigation, the move _ base module in the ROS navigation system is responsible for scheduling the whole navigation behavior, including initializing costmap and planer, monitoring the navigation state and timely replacing the navigation strategy.
The method relates to behavior control, and the move _ base is specifically realized as a finite state machine, defines a plurality of recovery _ videos, and specifies behaviors after problems occur in the vehicle navigation process. The specific process is as follows:
the Move _ base firstly starts two planners of global planning and local planning, takes charge of global path planning and local path planning, generates own cost map through a costmap component,
through global path planning, the global route from the vehicle to the target position is calculated, the realization method is to find the optimum based on cost search of the grid map,
and then, planning local obstacle avoidance through local planning. The specific navigation realization algorithm is dynamicwindows sapphire, and the specific flow is as follows:
and obtaining a sampling space of the speed by a kinematic model of the mobile chassis, calculating an objective function of each sample in the sampling space to obtain the expected speed, and interpolating to form a track for output. In the running process of the vehicle, planning (waking up a planner), operation (calculating and issuing legal speed), cleaning (recovery _ behavior) and the like can be performed according to the state of the vehicle.
And the program with the navigation function can run on the cloud server, communicates with the server through the 5G network and receives the command of the server. When the delivery vehicle arrives downstairs at the user's residence, the delivery vehicle will send a message to the user to remind the user that the take-out has arrived. The user only needs to scan the sign indicating number unblock and take the takeaway, prevents that the takeaway from being stolen the phenomenon of taking by mistake and taking takes place. After delivery is complete, the delivery vehicle is automatically navigated back to the delivery point area.
Meanwhile, the invention also provides a full-automatic distribution system for the cloud community takeout, which comprises a communication module, a region division module, an encryption and decryption module and an ROS navigation system,
order information is input into the cloud end, different meal delivery areas are divided by the cloud end according to the takeout quantity, delivery vehicles are distributed to deliver meals according to the meal delivery areas,
the communication module is used for communicating the delivery vehicle with the cloud end through a 5G network and receiving order delivery information of the cloud end, the region division module divides different meal delivery regions according to the takeout quantity through the communication module, the cloud end is obtained by the region division module, the distributed meals of the delivery vehicle are received according to the meal delivery regions,
and the ROS navigation system initializes the distribution vehicle, monitors the navigation state, changes the navigation strategy at proper time, starts a planner, generates a cost map, calculates the global route from the distribution vehicle to the target position, simultaneously carries out local obstacle avoidance until the target position is reached, sends a message to an order user, and waits for the user to unlock the distribution vehicle for food distribution.
The information interaction, execution process and other contents between the modules in the system are based on the same concept as the method embodiment of the present invention, and specific contents can be referred to the description in the method embodiment of the present invention, and are not described herein again.
It should be noted that not all steps and modules in the above flows and system structures are necessary, and some steps or modules may be omitted according to actual needs. The execution order of the steps is not fixed and can be adjusted as required. The system structure described in the above embodiments may be a physical structure or a logical structure, that is, some modules may be implemented by the same physical entity, or some modules may be implemented by a plurality of physical entities, or some components in a plurality of independent devices may be implemented together.
The above-mentioned embodiments are merely preferred embodiments for fully illustrating the present invention, and the scope of the present invention is not limited thereto. The equivalent substitution or change made by the technical personnel in the technical field on the basis of the invention is all within the protection scope of the invention. The protection scope of the invention is subject to the claims.
Claims (8)
1. A full-automatic distribution scheme for takeout in a cloud community is characterized in that order distribution information is input into a cloud end, different meal delivery areas are divided by the cloud end according to takeout quantity, distribution cars are distributed according to the meal delivery areas to deliver meals,
the distribution vehicle is communicated with the cloud through a 5G network, receives distribution information, utilizes an ROS navigation system to initialize, monitors the navigation state, changes the navigation strategy in due time, starts a planner, generates a cost map, calculates the overall route from the distribution vehicle to a target position, carries out local obstacle avoidance at the same time until the target position is reached, sends a message to an order user, and waits for the user to unlock the distribution vehicle for food.
2. The scheme of claim 1, wherein a move _ base module in the ROS navigation system is used for scheduling the navigation action of a delivery vehicle.
3. The scheme of claim 2, wherein the scheduling process is as follows:
starting two planners of global planning and local planning through a Move _ base module, taking charge of global path planning and local path planning, generating a cost map,
calculating a global route from the vehicle to the target position through global path planning,
and planning local obstacle avoidance through local planning.
4. The cloud community takeout fully-automatic distribution scheme as claimed in claim 3, wherein the local obstacle avoidance planning process comprises:
and obtaining a sampling space of the speed by a kinematic model of the movement of the delivery vehicle, calculating an objective function of each sample in the sampling space to obtain an expected speed, and interpolating to form a track for output.
5. A full-automatic distribution system for take-out in a cloud community is characterized by comprising a communication module, an area division module, an encryption and decryption module and an ROS navigation system,
order information is input into the cloud end, different meal delivery areas are divided by the cloud end according to the takeout quantity, delivery vehicles are distributed to deliver meals according to the meal delivery areas,
the communication module is used for communicating the delivery vehicle with the cloud end through a 5G network and receiving order delivery information of the cloud end, the region division module divides different meal delivery regions according to the takeout quantity through the communication module, the cloud end is obtained by the region division module, the distributed meals of the delivery vehicle are received according to the meal delivery regions,
and the ROS navigation system initializes the distribution vehicle, monitors the navigation state, changes the navigation strategy at proper time, starts a planner, generates a cost map, calculates the global route from the distribution vehicle to the target position, simultaneously carries out local obstacle avoidance until the target position is reached, sends a message to an order user, and waits for the user to unlock the distribution vehicle for food distribution.
6. The cloud cell takeout fully-automatic delivery system of claim 5, wherein a move _ base module in the ROS navigation system is used for scheduling the navigation action of a delivery vehicle.
7. The cloud cell takeout fully-automatic distribution system as claimed in claim 6, wherein the move _ base module scheduling process is as follows:
starting two planners of global planning and local planning through a Move _ base module, taking charge of global path planning and local path planning, generating a cost map,
calculating a global route from the vehicle to the target position through global path planning,
and planning local obstacle avoidance through local planning.
8. The cloud cell takeout fully-automatic distribution system as claimed in claim 7, wherein the process of planning local obstacle avoidance by using local planning through the Move _ base module comprises:
and obtaining a sampling space of the speed by a kinematic model of the movement of the delivery vehicle, calculating an objective function of each sample in the sampling space to obtain an expected speed, and interpolating to form a track for output.
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