This project is not actively maintained

I no longer have Roborock vacuum robot and I cannot test any of app's features. I am planning to get one in the near future, likelly the newest one, but for now - this project is currently on-hold...

ValetudoPNG

ValetudoPNG is a service designed to render map from Valetudo-enabled vacuum robot into a more accessible PNG format. This PNG map is sent to Home Assistant via MQTT, where it can be viewed as a real-time camera feed. ValetudoPNG was specifically developed to integrate with third-party frontend cards, such as the PiotrMachowski/lovelace-xiaomi-vacuum-map-card.

Alternative projects:

• sca075/valetudo_vacuum_camera - deploys as HACS addon, written in Python.
• alexkn/node-red-contrib-valetudo - nodered map renderer.

Broken or dead projects:

• Hypfer/ICantBelieveItsNotValetudo - original project, written in javascript for NodeJS.
• rand256/valetudo-mapper - fork of original project to be used with rand256/valetudo. Does not work with Hypfer/Valetudo.

Features

• Written in Go.
  • Single binary
  • No dependencies
  • Fast & multithreaded rendering
• Pre-built Docker images.
• Automatic map calibration data for PiotrMachowski/lovelace-xiaomi-vacuum-map-card.
• Easy configuration using yaml config file.
• Map modification:
  • Rotation
  • Scaling
  • "croping" by binding map to coordinates in robot's coordinates system
• HTTP endpoint:
  • Access image http://ip:port/api/map/image.
  • Debug image and it's coordinates/pixels in robot's coordinates system http://ip:port/api/map/image/debug.
• Designed to work with HomeAssistant in mind.

Supported architectures:

• linux/amd64: x86_64, Intel 64, AMD64, 64-bit PC architecture
• linux/arm64: aarch64, armv8, ARM 64-bit
• linux/arm/v7: armv7l, armv7-a, ARM 32-bit version 7
• linux/arm/v6: armv6l, armv6-a, ARM 32-bit version 6

Get started

Configure Valetudo

It is assumed that Valetudo is connected to Home Assistant via MQTT and is working.

Go to Valetudo URL -> Connectivity -> MQTT Connectivity -> Customizations. Make sure Provide map data is enabled.

Configuration file

Create config.yml file out of config.example.yml file and update according.

For starters, assuming that you don't have TLS and username/password set in your MQTT server, you can update only these for now:

    host: 192.168.0.123
    port: 1883

and these:

    # Should match "Topic prefix" in Valetudo MQTT settings
    valetudo_prefix: valetudo

    # Should match "Identifier" in Valetudo MQTT settings
    valetudo_identifier: rockrobo

Now move to installation and usage sections, where you will be able to easily "experiment" with your config.

Installation

Binaries

See Releases.

$ tar -xvzf valetudopng_v1.0.0_linux_amd64.tar.gz 
valetudopng_v1.0.0_linux_amd64
$ ./valetudopng_v1.0.0_linux_amd64 --help
Usage of ./valetudopng_v1.0.0_linux_amd64:
  -config string
        Path to configuration file (default "config.yml")
  -version
        prints version of the application

You can technically install it on robot itself:

[root@rockrobo ~]# grep -e scale config.yml
  scale: 2
[root@rockrobo ~]# ./valetudopng
2023/10/02 07:18:10 [MQTT producer] Connected
2023/10/02 07:18:10 [MQTT consumer] Connected
2023/10/02 07:18:10 [MQTT consumer] Subscribed to map data topic
2023/10/02 07:18:10 Image rendered! drawing:39ms, encoding:61ms, size:9.1kB
2023/10/02 07:18:16 Image rendered! drawing:37ms, encoding:72ms, size:9.1kB
2023/10/02 07:18:16 Image rendered! drawing:35ms, encoding:66ms, size:9.1kB
2023/10/02 07:18:17 Image rendered! drawing:44ms, encoding:50ms, size:7.4kB
2023/10/02 07:18:18 Image rendered! drawing:33ms, encoding:54ms, size:7.4kB
2023/10/02 07:18:20 Image rendered! drawing:34ms, encoding:52ms, size:7.4kB
2023/10/02 07:18:22 Image rendered! drawing:34ms, encoding:61ms, size:7.4kB
2023/10/02 07:18:24 Image rendered! drawing:32ms, encoding:56ms, size:7.7kB
2023/10/02 07:18:26 Image rendered! drawing:45ms, encoding:62ms, size:7.8kB
2023/10/02 07:18:28 Image rendered! drawing:33ms, encoding:64ms, size:7.8kB
2023/10/02 07:18:30 Image rendered! drawing:44ms, encoding:59ms, size:8.0kB
2023/10/02 07:18:32 Image rendered! drawing:38ms, encoding:62ms, size:8.2kB
2023/10/02 07:18:35 Image rendered! drawing:88ms, encoding:54ms, size:8.3kB
2023/10/02 07:18:36 Image rendered! drawing:35ms, encoding:72ms, size:8.4kB

Download binary appropriate for your robot's CPU and follow the service installation guidelines of another project: https://github.com/porech/roborock-oucher

Note that this service is still resources-intensive and drains more battery when robot is not charging. Generally it is not recommended to host it on robot.

Docker compose

  valetudopng:
    image: ghcr.io/erkexzcx/valetudopng:latest
    container_name: valetudopng
    restart: always
    volumes:
      - ./valetudopng/config.yml:/config.yml
    ports:
      - "3000:3000"

Docker CLI

docker run -d \
    --restart=always \
    --name=valetudopng \
    -v $(pwd)/valetudopng/config.yml:/config.yml \
    -p 3000:3000 \
    ghcr.io/erkexzcx/valetudopng:latest

Usage

When hosted, go to http://ip:port/api/map/image/debug and start selecting rectangles. Below the picture there will be information that you will want to copy/paste.

For example, this is how my PiotrMachowski/lovelace-xiaomi-vacuum-map-card card looks like with valetudo_prefix: valetudo and valetudo_identifier: rockrobo and RockRobo S5 vacuum:

type: custom:xiaomi-vacuum-map-card
map_source:
  camera: camera.rockrobo_rendered_map
calibration_source:
  entity: sensor.rockrobo_calibration_data
entity: vacuum.valetudo_rockrobo
vacuum_platform: Hypfer/Valetudo
internal_variables:
  topic: valetudo/rockrobo
map_modes:
  - template: vacuum_clean_zone_predefined
    selection_type: PREDEFINED_RECTANGLE
    predefined_selections:
      - zones: [[2185,2975,2310,3090]]
        label:
          text: Entrance
          x: 2247.5
          y: 3032.5
          offset_y: 28
        icon:
          name: mdi:door
          x: 2247.5
          y: 3032.5
  - template: vacuum_goto
  - template: vacuum_clean_zone
map_locked: true
two_finger_pan: false