CN110619411A

CN110619411A - Intelligent shopping cart indoor positioning and navigation algorithm engine

Info

Publication number: CN110619411A
Application number: CN201810632631.3A
Authority: CN
Inventors: 周晓祥; 孟凡涛; 周庄原
Original assignee: Aisino Dudley Information Systems (shanghai) Co Ltd; Aisino Corp
Current assignee: Aisino Dudley Information Systems (shanghai) Co Ltd; Aisino Corp
Priority date: 2018-06-19
Filing date: 2018-06-19
Publication date: 2019-12-27

Abstract

The large-scale popularization of the outdoor positioning navigation application saves countless patients from water and fire. As long as one smart phone is owned, people can easily find a path to a destination in an unfamiliar city. Just as we rely more and more on GPS for directions outdoors, in the future, in business miles, the precise indoor positioning and navigation service will easily lead customers to buy the wanted things, and enjoy the most favorable promotion, such as taking customers to the shelf where the needed goods are bought or reasonably planning the track route. In addition, the customer may receive promotional information about the current location. For example, when shopping, the shopping cart tells you what promotion offers related to the related goods, and receives related information of the promotion, thereby realizing the shopping guide function. The invention provides a navigation algorithm engine, particularly relates to a technology for indoor positioning of an intelligent shopping cart and realization of shopping guide through a navigation algorithm, and belongs to the field of data structures and algorithms.

Description

Intelligent shopping cart indoor positioning and navigation algorithm engine

Technical Field

The system provides a navigation algorithm engine, particularly relates to a technology for indoor positioning of an intelligent shopping cart and shopping guide realization of a navigation algorithm, and belongs to the field of data structures and algorithms.

Background

The large-scale popularization of the outdoor positioning navigation application saves countless patients from water and fire. As long as one smart phone is owned, people can easily find a path to a destination in an unfamiliar city. Just as we rely more and more on GPS for directions outdoors, in the future, in business miles, the precise indoor positioning and navigation service will easily lead customers to buy the wanted things, and enjoy the most favorable promotion, such as taking customers to the shelf where the needed goods are bought or reasonably planning the track route. In addition, the customer may receive promotional information about the current location. For example, when shopping, the shopping cart tells you what promotion offers related to the related goods, and receives related information of the promotion, thereby realizing the shopping guide function.

Disclosure of Invention

The invention comprises a path planning strategy and a positioning display and movement strategy.

Firstly, a path planning strategy:

the strategy focuses more on the experience of the customer in the whole shopping process, helps the customer pass through the self-mind commodity as much as possible in the process of searching for the specific commodity, fully considers the characteristics of the age, the preference, the hot spot area of a retail store and the like of the customer, and plans an optimal traveling route for the customer instead of simply calculating the shortest path.1) step 1: calculating the heat of each road block

The calculation method is as follows:

(1) assume that the road block coverage promotion is PM1, pm2.... PMn, with the corresponding weights PW1, PW 2.. PWn.

(2) Suppose that the road block covers a commercial product M1, M2.... Mn, with corresponding weights MW1, MW 2.. MWn.

(3) Assume that the retail store has an overall promotional weight of PW and an overall merchandise weight of MW.

(4) Assume that the shelf retention rate covered by the road block is P (U)1, P (U)2.

Within D days, the stay time of all the shelves is n, the stay time of the customer i in the shelf a is m, and the stay rate of the customer in the shelf is mAssuming that the number of customers in the system is U, the retention rate of the shelf in the near D days is

If the current client cannot be determined and the whole stay time of the system is used, the road block heat BH is: BH ═ Σ (PM × PW) + Σ (M × MW) + Σp (u)

Road Block Heat calculation see FIG. 1

2) Step 2: calculating the purchase distance of the goods shelf (BuyLength)

If an item is displayed on multiple shelves, only the distance of purchase (BuyLength) of the shelf needs to be calculated to find the most appropriate item.

Let SD be the linear distance from the current vehicle to the shelf

Let DD be the linear distance from the shelf to the settlement area

The purchase distance is SD + DD

3) And step 3: all routes that can reach the target corridor are calculated.

When more than 5 paths meet the requirements, the calculation is stopped, and all the lines which can reach the target and contain all the necessary paths are calculated by using the following algorithm.

The optimal direction selection method comprises the following steps:

(1) the must-pass path of the perimeter is preferred.

(2) If no necessary path or all necessary paths are detected, if the surrounding hot paths are not detected and the heat is higher than HT (the heat boundary value is selected to be the most recommended path, and for the paths smaller than HT, the system can be uniformly treated as a common path), the hottest path is selected.

(3) And if the necessary path is detected and the hot path is detected, selecting and facing the path with the smallest included angle with the commodity.

Path search Algorithm see FIG. 2

4) And 4, step 4: calculating an optimal route

The promotions in the path are P0, P1

The weight of each promotion to that customer is W0, W1.. Wn

The walking distance is L

The walking ability coefficient is LW (default is 1, if the user can be judged to be a teenager, the value can be enlarged, if the user can be judged to be an elderly person, the value can be reduced.)

BHn is a measure of the heat of travel through each block BH1, BH2

The road block heat weight is BHW

According to the block heat algorithm, the weight of the path is

Secondly, positioning display and moving strategies:

the current position of the shopping cart is taken through the positioning system and displayed on the map.

The system may have uncertain data delay, which may result in inconsistent and even jerky display of the vehicle position. The algorithm strategy can be combined with a path planning module to move the vehicle smoothly.

1) Step 1: the current position of the shopping cart is obtained through the positioning system.

2) Step 2: smooth movement strategy

Smooth movement strategy see FIG. 3

3) And step 3: step by step movement strategy

Step by step movement strategy see FIG. 4

Drawings

FIG. 1 road block heat calculation in accordance with the present invention

FIG. 2 path search algorithm in accordance with the present invention

FIG. 3 smooth movement strategy to which the present invention relates

FIG. 4 step by step movement strategy to which the present invention relates

FIG. 5 how to divide blocks to which the invention relates

FIG. 6 how visible shelves are generated in accordance with the present invention

FIG. 7 how to find the shelf with the shortest BL according to the present invention

FIG. 8 how to determine a target road block in accordance with the invention

Figure 9 how the invention relates to the elimination of unwanted and already walked parts

FIG. 10 how to determine must-pass paths in accordance with the present invention

FIG. 11 how to determine walking direction in accordance with the invention

FIG. 12 is a partial schematic diagram of a calculated circuit according to the present invention

FIG. 13 is a partial schematic diagram of a calculated circuit according to the present invention

Figure 14 how the invention relates to direct movement

FIG. 15 how the invention relates to barrier-free stepwise movement

Figure 16 how the invention relates to barrier step-by-step movement

Detailed Description

Firstly, path planning implementation:

required parameters

●R

Measuring range radius of road block covering goods shelf

●D

Days to determine shelf retention

●MaxL

The longest acceptable walking distance defines the longest walking distance acceptable to the user, and if the value is-1, it is considered that there is no requirement for the longest distance. The system will not recommend a path that exceeds the longest acceptable distance traveled.

●HT

And the heat boundary value, the system can be uniformly treated as a common path for the path blocks smaller than HT in the path calculation process, and the system can preferentially select the paths higher than the heat boundary value. This value is used for algorithm optimization.

●LW

The user's ability to walk. The coefficients determine the outcome of the system path recommendation. For older users, the coefficient may be reduced and the system may recommend a shorter path as possible. For a teenager user, the coefficient may be scaled up and the system may attempt to recommend a more popular path.

●MaxChoice

The system has the most recommended paths. This parameter determines the maximum number of paths that the system recommends to the customer. -1 represents no limitation.

Description of the procedure

1) Step 1: distributing road blocks and calculating heat degree of each road block

(1) Each corridor or corner is first partitioned into blocks, each Block being a Block that can be bypassed (Block), which we call a Block. If some paths are unidirectional, they must be denoted as round-trip paths.

How to split the blocks see FIG. 5

(2) The system calculates for each road block the shelves that the road block can cover. (can cover what can be seen by the customer after the block is routed)

(3) The calculation method is as follows: and moving forwards step by step along the center of the road block, and regarding the goods shelves within the peripheral radius R meters as visible goods shelves in the moving process.

See how the shelf is generated see FIG. 6

2) Step 2: goods shelf for searching for goods

(1) The system needs to find the shelf with the shortest BL as the target shelf

How to find the shelf with the shortest BL is shown in FIG. 7

(2) The system needs to determine the target road block according to the goods shelf where the goods are

How to determine the target road block is shown in FIG. 8

(3) Excluding all shelves between the target aisle and the checkout area, this portion of the shelf system may be considered as the portion that the customer does not need to walk through before taking the product.

(4) Excluding parts that the customer has walked

How to exclude unnecessary and already walked parts is shown in FIG. 9

3) And step 3: system planning route

(1) If the customer has a heart-of-instrument item or promotion in the customer's pre-purchase order and the item is unique to a single shelf, the path covered by the shelf serves as the customer's obligation path.

How to determine the must-pass path see FIG. 10

(2) And determining the walking direction as the direction in which the vehicle directly points to the target corridor, and planning the travel of each road block as the non-reverse direction.

How to determine walking direction is shown in FIG. 11

(3) The system begins to calculate all routes that can reach the target corridor.

The calculated line information needs to contain

Distance traveled

Passing goods shelf, heart instrument commodity, sales promotion and other information

For paths beyond the longest walking distance (MaxL), the system is not adopted.

Part of the calculated circuit diagram I is shown in FIG. 12

Calculated partial circuit diagram II see FIG. 13

4) And 4, step 4: selecting the optimal line

After the calculation of the road block heat algorithm is completed, the system recommends the maximum MaxCoice routes for the customer from high to low for the customer to select.

Secondly, positioning display and moving implementation:

required parameters

●n

Can ensure the maximum moving distance of smooth vision and no jumping feeling

Description of the procedure

1) Step 1: the display module obtains the current position of the vehicle from the positioning engine.

2) Step 2: suppose that the current position is A, the target position is B, and the maximum moving distance is n (to ensure smooth vision)

(1) Moving directly

How to move directly see FIG. 14

(2) Barrier-free step-by-step movement

How the barrier-free stepwise movement is seen in fig. 15

(3) With barrier moving gradually

How the barrier moves step by step is seen in figure 16.

Claims

1. An intelligent shopping cart indoor positioning and navigation algorithm engine comprising: the technology for realizing shopping guide by the indoor positioning and navigation algorithm of the intelligent shopping cart is characterized in that:

the navigation algorithm may analyze the age of the customer and when the age is above the gate value, the system will prefer the shorter distance route. When the age is lower than the gate value, the system analyzes the attribute for recommendation;

the navigation algorithm can analyze the preference of the customer according to the historical shopping record and the current pre-purchase list of the customer, and help the customer pass interested commodities or sales promotion as much as possible when planning the path;

the navigation algorithm can calculate current hot commodities and promotions, takes full consideration when planning the route, and plans the commodities or promotions passing through the hot roads under the condition of not reducing the shopping experience of customers.

2. The intelligent shopping cart indoor positioning and navigation algorithm engine of claim 1, wherein: the method comprises the steps of intelligently analyzing a pre-purchase list of a current customer when a path is planned, and ensuring that the possible paths to a target shelf contain as many pre-purchased commodities as possible so as to prevent the customer from walking back.

3. The intelligent shopping cart indoor positioning and navigation algorithm engine of claims 1 and 2, wherein: the vehicle can move smoothly in a plan view by combining a smooth movement strategy and a step-by-step movement strategy, and the situation of jumping cannot occur.