GoPi5Go-Dave Shines With Turtlebot3 Cartographer

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Last year I spent a month of days and nights learning to install, configure, and run the nav2 slam_toolbox package that is widely esteemed as the most accurate mapping and localization package yet. This is how slam_toolbox maps Dave’s “office” at 0.05 meter resolution:

slam_toolbox_office
slam_toolbox_office1920×1209 191 KB

Last week I spent one hour learning how to run turtlebot3_cartographer, and then one solid day creating the GoPiGo3 version called gpg3_cartographer. This is how gpg3_cartographer maps Dave’s “office” at 0.05 meter resolution:

gpg_cart_office
gpg_cart_office1920×1209 165 KB

Turtlebot3 Cartographer sure makes GoPi5Go-Dave shine!

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Glad to hear it!

(So, which of the smudges is the cat? :rofl:)

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gpg_cart_office_annotated
gpg_cart_office_annotated1920×1209 170 KB

What really impresses me in this result:

  1. It managed to “see” the black UPS, the black flightsim computer, and the black filing cabinet enough to close the area. This is the LIDAR return standing in front of the dock:

Dave_LIDAR_office
Dave_LIDAR_office1920×1237 166 KB

  1. The red odometry line shows how bad my ros2_gopigo3_driver is at estimating the bot position, but using the odometry with LIDAR data, Cartographer managed to localize the robot correctly in the room after the first 2 meters of travel in the room.
  2. I did not have to tune or change anything, period! ros2 launch turtlebot3_cartographer cartographer.launch.py and it used my GoPiGo3 robot description (dave.urdf), my LIDAR (ydlidar x4 not turtlebot3 RPILidar, my lousy GoPiGo3 odometry, and didn’t complain there was no IMU data.
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I found the cat!

The Cat
The Cat814×679 64.4 KB

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Luckily, Dave doesn’t get that “juiced”, but I do think I read someone built a ROS cat detector.

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Doesn’t the latest GoPiGo O/S have some Tensor-Flow object recognition stuff in there?  I bet that would work as a “cat detector” and I’m sure you could cobble up something with Dave and/or Carl.  (Didn’t you have Carl doing lane finding awhile back?  I wonder if Carl’s getting lonely. . .)

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The original map looks like something you could put up in a museum alongside Van Gogh or Pollock.  (Sometimes I think they were “sauteing” some “mushrooms” for dinner.)

Maybe you don’t have self-aware robots yet, but they’re doing quite well as impressionistic artists!

That’s the sweetest part of all. . . .
Fiddler on the Roof

Like your scripts, it’s sweet when things come together like they’re supposed to.

Once I get some traction on the display stuff, I’m going to dedicate a SD card to trying out your downloadable ROS build, just to see what happens.

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Yes - with the PiCamera

Yes - it detects cats at roughly 1 frame per second - (sometimes even dreams it is seeing cats)

Yes, Create3-WaLI was detecting cats with the Oak-D camera at 30fps. Dave will be able to reuse the Create3-WaLI code without a change.

Carl has not indicated he is jealous of my attention to his little, younger brother. I do try to interact with Carl quite often to get the weather forecast, and to check his battery health of course. Carl has an annoying habit of trying to talk to the TV, so I often have to yell from livingroom to him “Hey Carl, go to sleep!”.

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Goal met!  He’s “interacting with his surroundings”!

Now you can take that off your bucket-list. . .

Sweet!  Nice when you DON’T have to re-invent the wheel for a change.

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It also recognizes bottles and wine glasses, so I thought about teaching Dave to guard my wine collection … but I’m not planning on restocking after I finish this 592nd bottle (in 20 years). It’s an aged, terroir select, heavy tannin, oaked Cab, (worth guarding), that I selected to be my last.

==== YOLOv4 

ros2 launch depthai_examples yolov4_publisher.launch.py camera_model:=OAK-D-LITE spatial_camera:=false

       "labels":
        [
            0 "person",
            1 "bicycle",
            2 "car",
            3 "motorbike",
            4 "aeroplane",
            5 "bus",
            6 "train",
            7 "truck",
            8 "boat",
            9 "traffic light",
            10 "fire hydrant",
            11 "stop sign",
            12 "parking meter",
            13 "bench",
            14 "bird",
            15 "cat",                     <<<------- CAT
            16 "dog",
            17 "horse",
            18 "sheep",
            19 "cow",
            20 "elephant",
            21 "bear",
            22 "zebra",
            23 "giraffe",
            24 "backpack",
            25 "umbrella",
            26 "handbag",
            27 "tie",
            28 "suitcase",
            29 "frisbee",
            30 "skis",
            31 "snowboard",
            32 "sports ball",
            33 "kite",
            34 "baseball bat",
            35 "baseball glove",
            36 "skateboard",
            37 "surfboard",
            38 "tennis racket",
            39 "bottle",                      <<<--- BOTTLE
            40 "wine glass",              <<<--- WINE GLASS
            41 "cup",
            42 "fork",
            43 "knife",
            44 "spoon",
            45 "bowl",
            46 "banana",
            47 "apple",
            48 "sandwich",
            49 "orange",
            50 "broccoli",
            51 "carrot",
            52 "hot dog",
            53 "pizza",
            54 "donut",
            55 "cake",
            56 "chair",
            57 "sofa",
            58 "pottedplant",
            59 "bed",
            60 "diningtable",
            61 "toilet",
            62 "tvmonitor",
            63 "laptop",
            64 "mouse",
            65 "remote",                  
            66 "keyboard",
            67 "cell phone",          <<<--- CELL PHONE
            68 "microwave",
            69 "oven",
            70 "toaster",
            71 "sink",
            72 "refrigerator",
            73 "book",
            74 "clock",
            75 "vase",
            76 "scissors",
            77 "teddy bear",
            78 "hair drier",
            79 "toothbrush"
        ]

Maybe I should teach him to answer “Hey Dave, Where’s my cell phone?”

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