Tech-invite3GPPspaceIETFspace
21222324252627282931323334353637384‑5x

Content for  TR 22.837  Word version:  19.3.0

Top   Top   Up   Prev   Next
0…   4   5…   5.2…   5.3…   5.4…   5.5…   5.6…   5.7…   5.8…   5.9…   5.10…   5.11…   5.12…   5.13…   5.14…   5.15…   5.16…   5.17…   5.18…   5.19…   5.20…   5.21…   5.22…   5.23…   5.24…   5.25…   5.26…   5.27…   5.28…   5.29…   5.30…   5.31…   5.32…   6…   7…

 

5.23  Use case on AMR collision avoidance in smart factoriesp. 66

5.23.1  Descriptionp. 66

Autonomous mobile robots (AMR) are currently being introduced in many logistics operations, e.g. manufacturing, warehousing, cross-docks, terminals, and hospitals. Compared to an automated guided vehicle (AGV) system in which a central unit takes control of scheduling, routing, and dispatching decisions for all AGVs, AMRs are robots built with intelligence to autonomously move and perform tasks. AGVs is expected to further be evolved into intelligent AMR to meet the demand of intelligent factory.
Compared to AGVs which move on transport paths guided by rails, magnetic markers etc. AMRs can travel automatically without derivatives or guides. AMRs don't rely on predetermined paths, they can easily adjust routes as user demands change, so AMRs have wider mobile range and more flexibility. AMRs can not only stop on time to avoid humans and other obstacles, but also adjust its route for its destination. However, during the AMR working process, the sensing range of a single AMR is limited and the AMR surrounding environment status may be not detected in time. For example, People or other machines that suddenly appear from behind the large factory equipment can affect the driving safety of the AMR. So, it is very challenge for AMR to get accurate and continuous sensing information along its route.
5G base stations can be deployed in a factory not only to provide communication capabilities for equipments in the factory but also sense the surrounding environment e.g. obstacles or people in the trajectory of AMRs. Base stations transmit the sensing signals and receive the reflected signals to get sensing information, then reports the real-time 3GPP sensing data to the core network. The core network can process and analyze the 3GPP sensing data for outputting the sensing result. Such sensing result can be exposed to a trusted third-party e.g. automation platform of the factory to enables AMRs to know more information about the surrounding environment to improve efficiency and driving safety.
In addition, when there are obstacles (e.g., the large factory equipment) to block the transmission of radio signals or AMR trajectory is across indoor and outdoor, multiple base stations with sensing capability can work together to improve the sensing accuracy and sensing service continuity.
Up

5.23.2  Pre-Conditionsp. 66

5G Network operator 'MM' provides 5G sensing service in the factory of Company A. Its 5G system has been deployed covering the factory to provide continuous sensing service indoor and outdoor.
Company A has placed two AMRs (AMR 1 and AMR2) in its factory for moving goods from workshop A to workshop B. At the same time, there are people moving around in both workshops, and other goods or tools may be temporarily placed on the route of the AMRs. The people walking in the workshop and the goods may block the AMR route, jeopardizing production safety. In addition, the two AMRs may collide considering their flexible routes.
The AMRs of Company A uses '5G Sensing Service' provided by 5G network Operator 'MM' during they are working. In order to ensure data security, the related sensing data is not permitted to be delivered outside Company A.
Up

5.23.3  Service Flowsp. 67

Figure 5.23.3-1 shows the route change of AMR1 in the process of carrying goods.
Copy of original 3GPP image for 3GPP TS 22.837, Fig. 5.23.3-1: Sensing People or obstacles detection in smart factory
Up
  1. The AMR#1 is delivering the car parts from workshop A to Sam who is near the assembly line in workshop B.
  2. The 3GPP sensing data collected by Base station #1/RAN, the 5G network processes the 3GPP sensing data to obtain sensing results and detects the proximity of obstacles along the trajectory of AMR#1. 5G system provides the sensing result to the AMR#1, and AMR#1 then re-route and bypass the obstacles based on the sensing result.
  3. AMR#1 is leaving the Workshop A and across from indoor to outdoor.
  4. The 3GPP sensing data is collected by Base station #2/RAN, the 5G network processes the 3GPP sensing data to obtain sensing results and detects the proximity of Daming who is walking across the trajectory of AMR#1. 5G system provides the sensing result to the AMR#1, then AMR#1 stops to wait for Daming to leave.
  5. AMR#1 enters the Workshop B.
  6. The 3GPP sensing data is collected by Base station #3/RAN, the 5G network processes the 3GPP sensing data to obtain sensing results and detects the AMR#2 near AMR#1. 5G system provides the sensing result to AMR#1, then AMR#1 re-routes and bypasses the obstacles based on the sensing result.
  7. When AMR#1 enters the coverage of Base Station #4, using the 3GPP sensing data from Base station #4/RAN, the 5G network processes the data to obtain sensing results and detects the proximity of John who is behind a large machine. 5G system provides the sensing result to AMR#1, then AMR#1 stops and waits for John to leave.
AMR#1 successfully delivers the car parts to Sam in workshop B.
Up

5.23.4  Post-Conditionsp. 67

Based on the communication and sensing services provided by the 5G network, the AMRs in the factory operate normally and reduce safety incidents.

5.23.5  Existing features partly or fully covering the use case functionalityp. 68

None.

5.23.6  Potential New Requirements needed to support the use casep. 68

[PR 5.23.6-1]
The 5G system shall be able to provide the continuity of sensing service for a specific target object, across indoor and outdoor.
[PR 5.23.6-2]
The 5G system shall be able to provide a secure mechanism to ensure sensing result data privacy within the sensing service area.
[PR 5.23.6-3]
The 5G system shall be able to support the following sensing related KPIs:
Scenario Sensing service area Confidence level [%] Accuracy of positioning estimate by sensing (for a target confidence level) Accuracy of velocity estimate by sensing (for a target confidence level) Sensing resolution Max sensing service latency [ms] Refreshing rate [s] Missed detection [%] False alarm [%]
Horizontal
[m]
Vertical [m] Horizontal [m/s] Vertical [m/s] Range resolution [m] Velocity resolution (horizontal/ vertical) [m/s x m/s]
AMR collision avoidance in smart factoriesindoor/outdoor99≤1N/A1N/A11.5<5000.05N/A5
NOTE 1:
The terms in Table 5.23.6-1 are found in clause 3.1.
NOTE 2:
The KPI values are sourced from [47].
Up

Up   Top   ToC