Mobile cleaning robot hardware recommendations
A method of assisting user-configuration of hardware for a mobile autonomous cleaning robot can include detecting a flooring type of a room or other portion of an environment. A size of the portion of the environment can be detected and a total size of the environment can be determined, generating a hardware characteristic recommendation can be generated based at least in part on the flooring type, the size of the portion of the environment, and the total size of the environment.
1. A method of assisting user-configuration of hardware for a mobile autonomous cleaning robot, the method comprising:
detecting a flooring type of a portion of an environment;
detecting a size of the portion of the environment;
determining a total size of the environment;
generating a roller type recommendation based at least in part on the flooring type, the size of the portion of the environment, and the total size of the environment; and
transmitting the roller type recommendation to a user interface device.
2. The method of claim 1 , further comprising:
detecting a flooring type within each portion of the environment accessed by the mobile autonomous cleaning robot; and
determining a total area of one or more flooring types of the environment based at least in part on detection of the flooring types; and
generating the roller type recommendation based at least in part on the total area of the one or more flooring types of the environment.
3. The method of claim 2 , further comprising:
determining a cleaning frequency of the mobile autonomous cleaning robot in one or more portions of the environment; and
generating the roller type recommendation based at least in part on the cleaning frequency.
4. The method of claim 3 , further comprising:
modifying one or more of the total areas of the portions of the flooring types based at least in part on the cleaning frequency of the mobile autonomous cleaning robot in one or more portions of the environment; and
generating the roller type recommendation based at least in part on the modified total areas of the flooring types.
5. The method of claim 3 , further comprising:
modifying one or more of the total areas of the portions of the flooring types based at least in part on a keep-out zone or a focused cleaning zone of the environment; and
generating the roller type recommendation based at least in part on the modified total areas of the flooring types.
6. The method of claim 1 , further comprising:
determining a user type based at least in part on input received from the user interface device; and
generating the roller type recommendation based at least in part on the user type.
7. The method of claim 6 , further comprising:
determining the user type based at least in part on data received from a fleet of mobile autonomous cleaning robots.
8. The method of claim 1 , further comprising:
detecting, using the mobile autonomous cleaning robot, a mobility obstacle within the environment; and
generating the roller type recommendation based at least in part on the mobility obstacle.
9. The method of claim 1 , further comprising:
detecting, using a sensor of the mobile autonomous cleaning robot, debris within the environment; and
generating the roller type recommendation based at least in part on the detected debris.
10. The method of claim 9 , further comprising:
detecting, using a sensor of the mobile autonomous cleaning robot, a type of the debris within the environment; and
generating the roller type recommendation based at least in part on the type of detected debris.
11. A method of assisting user-configuration of hardware for a mobile autonomous cleaning robot, the method comprising:
creating a map of an environment using a mobile autonomous cleaning robot, the map defined at least partially by one or more rooms;
detecting, using the mobile autonomous cleaning robot, a mobility obstacle within the environment; and
generating a mobility feature recommendation based at least in part on the mobility obstacle; and
transmitting the mobility feature type recommendation to a user interface device.
12. The method of claim 11 , further comprising:
determining a mobility feature size based at least in part on the mobility obstacle.
13. The method of claim 12 , further comprising:
determining a mobility feature compliance based at least in part on the mobility obstacle.
14. The method of claim 11 , wherein the mobility feature is a roller including a nub.
15. The method of claim 11 , wherein the mobility feature is a caster.
16. The method of claim 11 , wherein the mobility obstacle is a threshold or transition between flooring types.
17. The method of claim 16 , further comprising:
determining an optimal side brush length based at least in part on the flooring type indication.
18. A method of assisting user-configuration of hardware for a mobile autonomous cleaning robot, the method comprising:
detecting a size of the portion of the environment;
determining a total size of the environment;
detecting, using a sensor of the mobile autonomous cleaning robot, a size of debris within the portion of the environment
generating a hardware characteristic recommendation based at least in part on the flooring type, the size of the portion of the environment, and the size of the debris within the portion of the environment; and
transmitting the hardware characteristic recommendation to a user interface device.
19. The method of claim 18 , wherein the hardware characteristic recommendation is a side brush type recommendation based at least in part on the flooring type indication.
20. The method of claim 18 , wherein the hardware characteristic recommendation is a roller having relatively large vanes when large debris is detected.
21. The method of claim 18 , wherein the hardware characteristic recommendation is a roller having relatively small vanes when small debris is detected.