feat: update SLAM stack for Jetson Orin Nano Super (67 TOPS, JetPack 6)
Platform upgrade: Jetson Nano 4GB → Orin Nano Super 8GB (March 1, 2026) All Nano-era constraints removed — power/rate/resolution limits obsolete. Dockerfile: l4t-jetpack:r36.2.0 (JetPack 6 / Ubuntu 22.04 / CUDA 12.x), ROS2 Humble via native apt, added ros-humble-rtabmap-ros, ros-humble-v4l2-camera for future IMX219 CSI (Phase 2c) New: slam_rtabmap.launch.py — Orin primary SLAM entry point RTAB-Map with subscribe_scan (RPLIDAR) + subscribe_rgbd (D435i) Replaces slam_toolbox as docker-compose default New: config/rtabmap_params.yaml — Orin-optimized DetectionRate 10Hz, MaxFeatures 1000, Grid/3D true, TimeThr 0 (no limit), Mem/STMSize 0 (unlimited) Updated: config/realsense_d435i.yaml — 848x480x30, pointcloud enabled Updated: config/slam_toolbox_params.yaml — 10Hz rate, 1s map interval Updated: SLAM-SETUP-PLAN.md — full rewrite for Orin: arch diagram, Phase 2c IMX219 plan (4x 160° CSI surround), 25W power budget docker-compose.yml: image tag jetson-orin, default → slam_rtabmap.launch.py Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
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@ -1,12 +1,15 @@
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# Jetson Nano — ROS2 Humble dev container
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# Base: JetPack 4.6 (L4T R32.6.1) + CUDA 10.2
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# Arch: ARM64 (aarch64)
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# Jetson Orin Nano Super — ROS2 Humble dev container
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# Base: JetPack 6 (L4T R36.2.0) + CUDA 12.x / Ubuntu 22.04
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#
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# Hardware: Jetson Orin Nano Super 8GB (67 TOPS, 1024-core Ampere)
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# Previous: Jetson Nano 4GB (JetPack 4.6 / L4T R32.6.1) — see git history
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FROM nvcr.io/nvidia/l4t-base:r32.6.1
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FROM nvcr.io/nvidia/l4t-jetpack:r36.2.0
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LABEL maintainer="sl-jetson <saltylab>"
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LABEL description="ROS2 Humble + SLAM stack for Jetson Nano self-balancing robot"
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LABEL jetpack="4.6"
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LABEL maintainer="sl-perception <saltylab>"
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LABEL description="ROS2 Humble + SLAM stack for Jetson Orin Nano Super self-balancing robot"
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LABEL jetpack="6.0"
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LABEL l4t="r36.2.0"
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LABEL ros_distro="humble"
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ENV DEBIAN_FRONTEND=noninteractive
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@ -15,32 +18,29 @@ ENV ROS_ROOT=/opt/ros/${ROS_DISTRO}
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ENV PYTHONDONTWRITEBYTECODE=1
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ENV PYTHONUNBUFFERED=1
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# ── System deps ────────────────────────────────────────────────────────────────
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# ── Locale ─────────────────────────────────────────────────────────────────────
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RUN apt-get update && apt-get install -y --no-install-recommends \
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locales tzdata \
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&& locale-gen en_US.UTF-8 \
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&& rm -rf /var/lib/apt/lists/*
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ENV LANG=en_US.UTF-8
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# ── System deps ─────────────────────────────────────────────────────────────────
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RUN apt-get update && apt-get install -y --no-install-recommends \
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# Build tools
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build-essential cmake git wget curl \
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# Python
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python3-dev python3-pip python3-setuptools python3-wheel \
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# Serial / I2C / SPI
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i2c-tools libi2c-dev python3-smbus \
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picocom minicom setserial \
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# USB
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usbutils libusb-1.0-0-dev \
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# Misc
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locales tzdata htop tmux nano \
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# Networking
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htop tmux nano \
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net-tools iputils-ping \
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&& rm -rf /var/lib/apt/lists/*
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RUN locale-gen en_US.UTF-8
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ENV LANG=en_US.UTF-8
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# ── ROS2 Humble (from ROS2 apt repo — ARM64 build) ─────────────────────────────
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# Note: official humble debs for ARM64/L4T are provided via NVIDIA Isaac ROS
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# or via ros2-apt-source for 20.04 focal.
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# ── ROS2 Humble (Ubuntu 22.04 native — standard apt, no ARM64 workarounds) ─────
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RUN curl -sSL https://raw.githubusercontent.com/ros/rosdistro/master/ros.asc \
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| apt-key add - && \
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echo "deb [arch=arm64] http://packages.ros.org/ros2/ubuntu focal main" \
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| gpg --dearmor -o /usr/share/keyrings/ros-archive-keyring.gpg && \
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echo "deb [arch=arm64 signed-by=/usr/share/keyrings/ros-archive-keyring.gpg] \
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http://packages.ros.org/ros2/ubuntu jammy main" \
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> /etc/apt/sources.list.d/ros2.list && \
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apt-get update && apt-get install -y --no-install-recommends \
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ros-humble-ros-base \
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@ -51,50 +51,45 @@ RUN curl -sSL https://raw.githubusercontent.com/ros/rosdistro/master/ros.asc \
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&& rosdep init && rosdep update \
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&& rm -rf /var/lib/apt/lists/*
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# ── Nav / SLAM / sensor packages ──────────────────────────────────────────────
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# ── SLAM / Nav / Sensor packages ───────────────────────────────────────────────
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RUN apt-get update && apt-get install -y --no-install-recommends \
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ros-humble-nav2-bringup \
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ros-humble-rtabmap-ros \
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ros-humble-slam-toolbox \
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ros-humble-nav2-bringup \
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ros-humble-robot-localization \
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ros-humble-rplidar-ros \
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ros-humble-realsense2-camera \
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ros-humble-realsense2-description \
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ros-humble-tf2-tools \
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ros-humble-robot-state-publisher \
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ros-humble-rqt \
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ros-humble-rqt-common-plugins \
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ros-humble-rviz2 \
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ros-humble-rosbridge-server \
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ros-humble-image-transport-plugins \
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ros-humble-v4l2-camera \
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&& rm -rf /var/lib/apt/lists/*
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# ── GPIO / serial Python libs ──────────────────────────────────────────────────
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# ── GPIO / serial Python libs ───────────────────────────────────────────────────
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RUN pip3 install --no-cache-dir \
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Jetson.GPIO \
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pyserial \
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smbus2 \
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adafruit-blinka \
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RPi.GPIO \
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numpy \
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scipy
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Jetson.GPIO pyserial smbus2 numpy scipy
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# ── RealSense SDK (librealsense2 ARM64) ───────────────────────────────────────
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# Pre-built for L4T — install from Jetson Hacks script or apt source
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# ── RealSense SDK (librealsense2 ARM64 for JetPack 6) ─────────────────────────
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RUN apt-get update && apt-get install -y --no-install-recommends \
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libssl-dev libusb-1.0-0-dev pkg-config libgtk-3-dev \
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&& rm -rf /var/lib/apt/lists/*
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# librealsense2 ARM64 wheel (NVIDIA-patched for L4T)
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RUN pip3 install --no-cache-dir pyrealsense2
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# ── Workspace setup ───────────────────────────────────────────────────────────
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# ── Workspace setup ────────────────────────────────────────────────────────────
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RUN mkdir -p /ros2_ws/src
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WORKDIR /ros2_ws
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# Source ROS2 in every shell
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RUN echo "source /opt/ros/${ROS_DISTRO}/setup.bash" >> /root/.bashrc && \
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echo "source /ros2_ws/install/local_setup.bash 2>/dev/null || true" >> /root/.bashrc && \
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echo "export RMW_IMPLEMENTATION=rmw_cyclonedds_cpp" >> /root/.bashrc
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# ── Entrypoint ────────────────────────────────────────────────────────────────
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# ── Entrypoint ─────────────────────────────────────────────────────────────────
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COPY scripts/entrypoint.sh /entrypoint.sh
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RUN chmod +x /entrypoint.sh
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@ -1,53 +1,33 @@
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# RealSense D435i configuration — Jetson Nano (power-budget tuned)
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# RealSense D435i configuration — Jetson Orin Nano Super
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#
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# Profile format: WxHxFPS
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# Constraint: ~10W total budget. 640x480x15 saves ~0.4W vs 30fps.
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# Previous Nano 4GB settings (640x480x15, no point cloud) replaced.
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# Orin Nano Super has ample Ampere GPU headroom for 848x480x30fps + point cloud.
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#
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# Reference topics at these settings:
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# /camera/color/image_raw 640x480 15 Hz RGB8
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# /camera/depth/image_rect_raw 640x480 15 Hz Z16
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# /camera/aligned_depth_to_color/image_raw 640x480 15 Hz Z16
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# /camera/imu 6-axis ~200 Hz (accel@100Hz + gyro@400Hz fused)
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# /camera/color/camera_info 640x480 15 Hz
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# /camera/depth/camera_info 640x480 15 Hz
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#
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# Hardware IMU: Bosch BMI055
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# Accelerometer native rate: 100 Hz
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# Gyroscope native rate: 400 Hz
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# unite_imu_method=2: linearly interpolates accel to match gyro timestamps
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# Reference topics:
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# /camera/color/image_raw 848x480 30 Hz RGB8
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# /camera/depth/image_rect_raw 848x480 30 Hz Z16
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# /camera/aligned_depth_to_color/image_raw 848x480 30 Hz Z16
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# /camera/color/camera_info 848x480 30 Hz
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# /camera/depth/camera_info 848x480 30 Hz
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# /camera/imu ~400 Hz (gyro@400Hz + accel@100Hz fused)
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# /camera/points PointCloud2 30 Hz
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camera:
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ros__parameters:
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# ── Streams ──────────────────────────────────────────────────────────────
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depth_module.profile: "640x480x15"
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rgb_camera.profile: "640x480x15"
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depth_module.profile: "848x480x30"
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rgb_camera.profile: "848x480x30"
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enable_depth: true
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enable_color: true
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enable_infra1: false # not needed for RGB-D SLAM
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enable_infra1: false
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enable_infra2: false
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# ── IMU ──────────────────────────────────────────────────────────────────
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enable_gyro: true
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enable_accel: true
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# 0=none 1=copy 2=linear_interpolation
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# Use 2: aligns accel timestamps to gyro rate, required for sensor fusion
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unite_imu_method: 2
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unite_imu_method: 2 # linear_interpolation
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# ── Alignment ────────────────────────────────────────────────────────────
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# Projects depth pixels into RGB frame — required for rtabmap_ros rgbd input
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align_depth.enable: true
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pointcloud.enable: true # Orin Ampere GPU handles this without issue
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# ── Point cloud ──────────────────────────────────────────────────────────
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# Disabled: rtabmap_ros generates its own from aligned depth.
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# Maxwell GPU cannot handle both simultaneously at budget.
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pointcloud.enable: false
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# ── TF ───────────────────────────────────────────────────────────────────
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publish_tf: true
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tf_publish_rate: 0.0 # 0 = publish static transforms only (no redundant timer)
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# ── Device ───────────────────────────────────────────────────────────────
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# Leave serial_no empty to auto-select first found device
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# serial_no: ''
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# device_type: d435i
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tf_publish_rate: 0.0
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78
jetson/config/rtabmap_params.yaml
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78
jetson/config/rtabmap_params.yaml
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# RTAB-Map configuration — Jetson Orin Nano Super
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#
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# Hardware context: 67 TOPS, 1024-core Ampere GPU, 8GB RAM
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# All Nano-era constraints (2Hz cap, 400 features, no 3D) removed.
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#
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# Sensor inputs:
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# /scan LaserScan from RPLIDAR A1M8 ~5.5 Hz
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# /camera/color/image_raw RGB from RealSense D435i 30 Hz
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# /camera/depth/image_rect_raw Depth from D435i 30 Hz
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# /camera/color/camera_info Camera intrinsics 30 Hz
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#
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# Outputs:
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# /rtabmap/map OccupancyGrid (2D occupancy)
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# /rtabmap/cloud_map PointCloud2 (3D point cloud, enabled)
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# /rtabmap/odom Odometry (visual-inertial odometry)
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# /rtabmap/mapData Map data for serialization/loop closure
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#
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# Frame assumptions (match sensors.launch.py static TF):
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# map → odom → base_link → laser
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# → camera_link
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rtabmap:
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ros__parameters:
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# ── Core rate and timing ───────────────────────────────────────────────────
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# Process at 10Hz — far below D435i 30fps ceiling, still 5x faster than Nano
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Rtabmap/DetectionRate: "10"
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# No processing time limit — Orin has headroom (Nano was 700ms)
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Rtabmap/TimeThr: "0"
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# Update map every 5cm or ~3° rotation (was 10cm / 5°)
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RGBD/LinearUpdate: "0.05"
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RGBD/AngularUpdate: "0.05"
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# ── Visual features ────────────────────────────────────────────────────────
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# 1000 ORB features per frame (Nano was 400)
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Kp/MaxFeatures: "1000"
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Vis/MaxFeatures: "1000"
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# ── Memory ────────────────────────────────────────────────────────────────
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# Unlimited short-term memory — 8GB RAM (Nano was 30 keyframes)
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Mem/STMSize: "0"
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# Keep full map in working memory
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Mem/IncrementalMemory: "true"
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# ── Map generation ────────────────────────────────────────────────────────
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# 3D occupancy grid enabled — Ampere GPU handles point cloud generation
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Grid/3D: "true"
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Grid/CellSize: "0.05" # 5cm voxels
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Grid/RangeMin: "0.3" # ignore points closer than 30cm
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Grid/RangeMax: "8.0" # clip at A1M8 reliable range
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# ── Sensor subscriptions ──────────────────────────────────────────────────
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# Subscribe to both RPLIDAR scan (fast 2D) and D435i depth (3D)
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subscribe_scan: "true"
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subscribe_rgbd: "true"
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subscribe_odom_info: "false"
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# ── Loop closure ──────────────────────────────────────────────────────────
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# More aggressive loop closure — Orin can handle it
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RGBD/LoopClosureReextractFeatures: "true"
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Kp/IncrementalFlann: "true"
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# ── Odometry ──────────────────────────────────────────────────────────────
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# Use F2M (frame-to-map) visual odometry — more accurate on Orin
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Odom/Strategy: "0" # 0=F2M, 1=F2F
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Odom/ResetCountdown: "1"
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OdomF2M/MaxSize: "2000"
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# ── RGBD node input topics ─────────────────────────────────────────────────
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rgb_topic: /camera/color/image_raw
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depth_topic: /camera/depth/image_rect_raw
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camera_info_topic: /camera/color/camera_info
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depth_camera_info_topic: /camera/depth/camera_info
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scan_topic: /scan
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# ── Output ────────────────────────────────────────────────────────────────
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# Publish 3D point cloud map
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cloud_output_voxelized: "true"
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cloud_voxel_size: "0.05" # match Grid/CellSize
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# slam_toolbox — online async SLAM configuration
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# Tuned for Jetson Nano 4GB (constrained CPU/RAM, indoor mapping)
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# Jetson Orin Nano Super — all Nano rate caps removed.
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#
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# Primary SLAM is now RTAB-Map (slam_rtabmap.launch.py).
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# slam_toolbox retained for LIDAR-only localization against pre-built maps.
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#
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# Input: /scan (LaserScan from RPLIDAR A1M8, ~5.5 Hz)
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# Output: /map (OccupancyGrid, updated every map_update_interval seconds)
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#
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# Frame assumptions (must match sensors.launch.py static TF):
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# map → odom → base_link → laser
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# (odom not yet published — slam_toolbox handles this via scan matching)
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# Output: /map (OccupancyGrid)
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slam_toolbox:
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ros__parameters:
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# ── Frames ───────────────────────────────────────────────────────────────
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odom_frame: odom
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map_frame: map
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base_frame: base_link
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scan_topic: /scan
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mode: mapping # 'mapping' or 'localization'
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mode: mapping
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# ── Map params ───────────────────────────────────────────────────────────
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resolution: 0.05 # 5 cm/cell — good balance for A1M8 angular res
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max_laser_range: 8.0 # clip to reliable range of A1M8 (spec: 12m)
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map_update_interval: 5.0 # seconds between full map publishes (saves CPU)
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minimum_travel_distance: 0.3 # only update after moving 30 cm
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minimum_travel_heading: 0.3 # or rotating ~17°
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resolution: 0.05
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max_laser_range: 8.0
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map_update_interval: 1.0 # 1s (was 5s on Nano)
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minimum_travel_distance: 0.2
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minimum_travel_heading: 0.2
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# ── Performance (Nano-specific) ───────────────────────────────────────────
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# Reduce scan processing rate to stay within ~3.5W CPU budget
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minimum_time_interval: 0.5 # max 2 Hz scan processing (A1M8 is ~5.5 Hz)
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minimum_time_interval: 0.1 # ~10Hz processing (was 0.5s on Nano)
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transform_timeout: 0.2
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tf_buffer_duration: 30.0
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stack_size_to_use: 40000000 # 40 MB stack
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enable_interactive_mode: false # disable interactive editing (saves CPU)
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stack_size_to_use: 40000000
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enable_interactive_mode: false
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# ── Scan matching ─────────────────────────────────────────────────────────
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use_scan_matching: true
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use_scan_barycenter: true
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scan_buffer_size: 10
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scan_buffer_size: 20
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scan_buffer_maximum_scan_distance: 10.0
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# ── Loop closure ──────────────────────────────────────────────────────────
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do_loop_closing: true
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loop_match_minimum_chain_size: 10
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loop_match_maximum_variance_coarse: 3.0
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@ -46,31 +39,25 @@ slam_toolbox:
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loop_match_minimum_response_fine: 0.45
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loop_search_maximum_distance: 3.0
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# ── Correlation (coarse scan matching) ───────────────────────────────────
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correlation_search_space_dimension: 0.5
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correlation_search_space_resolution: 0.01
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correlation_search_space_smear_deviation: 0.1
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# ── Loop search space ─────────────────────────────────────────────────────
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loop_search_space_dimension: 8.0
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loop_search_space_resolution: 0.05
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loop_search_space_smear_deviation: 0.03
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# ── Response expansion ────────────────────────────────────────────────────
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link_match_minimum_response_fine: 0.1
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link_scan_maximum_distance: 1.5
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use_response_expansion: true
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# ── Penalties (scan matcher quality thresholds) ───────────────────────────
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distance_variance_penalty: 0.5
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angle_variance_penalty: 1.0
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fine_search_angle_offset: 0.00349 # ~0.2°
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coarse_search_angle_offset: 0.349 # ~20°
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coarse_angle_resolution: 0.0349 # ~2°
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fine_search_angle_offset: 0.00349
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coarse_search_angle_offset: 0.349
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coarse_angle_resolution: 0.0349
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minimum_angle_penalty: 0.9
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minimum_distance_penalty: 0.5
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|
||||
# ── Solver ────────────────────────────────────────────────────────────────
|
||||
solver_plugin: solver_plugins::CeresSolver
|
||||
ceres_linear_solver: SPARSE_NORMAL_CHOLESKY
|
||||
ceres_preconditioner: SCHUR_JACOBI
|
||||
|
||||
@ -8,7 +8,7 @@ services:
|
||||
|
||||
# ── Core ROS2 + SLAM node ─────────────────────────────────────────────────
|
||||
saltybot-ros2:
|
||||
image: saltybot/ros2-humble:jetson-nano
|
||||
image: saltybot/ros2-humble:jetson-orin
|
||||
build:
|
||||
context: .
|
||||
dockerfile: Dockerfile
|
||||
@ -51,7 +51,7 @@ services:
|
||||
command: >
|
||||
bash -c "
|
||||
source /opt/ros/humble/setup.bash &&
|
||||
ros2 launch saltybot_bringup slam.launch.py
|
||||
ros2 launch saltybot_bringup slam_rtabmap.launch.py
|
||||
"
|
||||
|
||||
# ── RPLIDAR driver node ────────────────────────────────────────────────────
|
||||
|
||||
@ -0,0 +1,114 @@
|
||||
"""
|
||||
slam_rtabmap.launch.py — RTAB-Map RGB-D + LIDAR SLAM (Orin primary entry point)
|
||||
|
||||
Replaces slam.launch.py (slam_toolbox) as the docker-compose default on Orin.
|
||||
RTAB-Map chosen over slam_toolbox for Orin because:
|
||||
- Native D435i depth + RPLIDAR sensor fusion
|
||||
- 3D point cloud output (Ampere GPU handles it)
|
||||
- Better loop closure with visual features
|
||||
- Outputs occupancy map directly consumable by Nav2
|
||||
|
||||
Stack:
|
||||
sensors.launch.py (RPLIDAR + RealSense D435i + static TF)
|
||||
rtabmap_ros/rtabmap (RTAB-Map node with RGB-D + scan input)
|
||||
|
||||
RTAB-Map input topics:
|
||||
/camera/color/image_raw 30 Hz (RGB from D435i)
|
||||
/camera/depth/image_rect_raw 30 Hz (depth from D435i)
|
||||
/camera/color/camera_info 30 Hz
|
||||
/scan ~5.5 Hz (RPLIDAR A1M8)
|
||||
|
||||
RTAB-Map output topics:
|
||||
/rtabmap/map OccupancyGrid (2D — Nav2 input)
|
||||
/rtabmap/cloud_map PointCloud2 (3D — visualization)
|
||||
/rtabmap/odom Odometry (visual-inertial)
|
||||
|
||||
Config: /config/rtabmap_params.yaml (mounted from jetson/config/)
|
||||
|
||||
Verify:
|
||||
ros2 topic hz /rtabmap/map # ~1Hz map updates
|
||||
ros2 topic hz /rtabmap/cloud_map # ~1Hz 3D cloud updates
|
||||
ros2 topic hz /rtabmap/odom # ~10Hz odometry
|
||||
"""
|
||||
|
||||
import os
|
||||
from launch import LaunchDescription
|
||||
from launch.actions import IncludeLaunchDescription, DeclareLaunchArgument
|
||||
from launch.launch_description_sources import PythonLaunchDescriptionSource
|
||||
from launch.substitutions import LaunchConfiguration
|
||||
from launch_ros.actions import Node
|
||||
from ament_index_python.packages import get_package_share_directory
|
||||
|
||||
|
||||
RTABMAP_PARAMS_FILE = '/config/rtabmap_params.yaml'
|
||||
|
||||
|
||||
def generate_launch_description():
|
||||
use_sim_time_arg = DeclareLaunchArgument(
|
||||
'use_sim_time',
|
||||
default_value='false',
|
||||
description='Use simulation clock (set true for rosbag playback)',
|
||||
)
|
||||
|
||||
bringup_share = get_package_share_directory('saltybot_bringup')
|
||||
|
||||
sensors_launch = IncludeLaunchDescription(
|
||||
PythonLaunchDescriptionSource(
|
||||
os.path.join(bringup_share, 'launch', 'sensors.launch.py')
|
||||
),
|
||||
)
|
||||
|
||||
# RTAB-Map node (rtabmap_ros package)
|
||||
# RGB-D + LIDAR mode: subscribe_scan=true, subscribe_rgbd=true
|
||||
rtabmap_node = Node(
|
||||
package='rtabmap_ros',
|
||||
executable='rtabmap',
|
||||
name='rtabmap',
|
||||
output='screen',
|
||||
parameters=[
|
||||
RTABMAP_PARAMS_FILE,
|
||||
{
|
||||
'use_sim_time': LaunchConfiguration('use_sim_time'),
|
||||
# Frame IDs — must match sensors.launch.py static TF
|
||||
'frame_id': 'base_link',
|
||||
'odom_frame_id': 'odom',
|
||||
'map_frame_id': 'map',
|
||||
},
|
||||
],
|
||||
remappings=[
|
||||
# RGB-D inputs from RealSense
|
||||
('rgb/image', '/camera/color/image_raw'),
|
||||
('rgb/camera_info', '/camera/color/camera_info'),
|
||||
('depth/image', '/camera/depth/image_rect_raw'),
|
||||
# 2D LIDAR from RPLIDAR A1M8
|
||||
('scan', '/scan'),
|
||||
],
|
||||
arguments=['--delete_db_on_start'], # fresh map each launch
|
||||
)
|
||||
|
||||
# RTAB-Map visualization node (optional — comment out to save CPU)
|
||||
rtabmap_viz_node = Node(
|
||||
package='rtabmap_ros',
|
||||
executable='rtabmapviz',
|
||||
name='rtabmapviz',
|
||||
output='screen',
|
||||
parameters=[{
|
||||
'use_sim_time': LaunchConfiguration('use_sim_time'),
|
||||
'frame_id': 'base_link',
|
||||
}],
|
||||
remappings=[
|
||||
('rgb/image', '/camera/color/image_raw'),
|
||||
('rgb/camera_info', '/camera/color/camera_info'),
|
||||
('depth/image', '/camera/depth/image_rect_raw'),
|
||||
('scan', '/scan'),
|
||||
],
|
||||
# Only launch viz if DISPLAY is available
|
||||
condition=None, # always launch; comment this node out if headless
|
||||
)
|
||||
|
||||
return LaunchDescription([
|
||||
use_sim_time_arg,
|
||||
sensors_launch,
|
||||
rtabmap_node,
|
||||
# rtabmap_viz_node, # uncomment for rviz-style RTAB-Map visualization
|
||||
])
|
||||
@ -1,264 +1,167 @@
|
||||
# bd-wax: Jetson Nano + RealSense D435i + RPLIDAR SLAM Setup — Technical Plan
|
||||
# SLAM Setup Plan — Jetson Orin Nano Super
|
||||
|
||||
**Bead:** bd-wax
|
||||
**Phase:** 2 (lower priority than Phase 1 balance)
|
||||
**Owner:** sl-perception
|
||||
**Hardware:** Jetson Nano 4GB + Intel RealSense D435i + RPLIDAR A1M8
|
||||
**Goal:** Indoor SLAM, mapping, and autonomous navigation (person-following)
|
||||
**Bead:** bd-wax (plan), bd-a2j (sensor drivers done PR #17)
|
||||
**Phase:** 2 | **Owner:** sl-perception
|
||||
**Updated:** 2026-03-01 — revised for Jetson Orin Nano Super (replaces Nano 4GB)
|
||||
|
||||
> All Nano-era constraints (10W cap, 2Hz detection, 400 features, no 3D) are obsolete.
|
||||
|
||||
---
|
||||
|
||||
## Hardware Summary
|
||||
## Hardware
|
||||
|
||||
| Component | Specs |
|
||||
|-----------|-------|
|
||||
| Jetson Nano 4GB | Quad-core ARM Cortex-A57 @ 1.43GHz, 128-core Maxwell GPU, 4GB LPDDR4 |
|
||||
| RealSense D435i | Stereo depth (0.1–10m), 848×480 @ 90fps, BMI055 IMU (accel+gyro) |
|
||||
| RPLIDAR A1M8 | 360° 2D LIDAR, 12m range, 8000 samples/s, ~5.5Hz scan rate |
|
||||
| AI Brain | **Jetson Orin Nano Super 8GB** — 6-core A78AE, 1024-core Ampere, **67 TOPS**, JetPack 6 |
|
||||
| Depth Cam | Intel RealSense D435i — 848×480 @ 90fps, BMI055 IMU |
|
||||
| LIDAR | RPLIDAR A1M8 — 360° 2D, 12m range, ~5.5 Hz |
|
||||
| Wide Cams | 4× IMX219 160° CSI — front/right/rear/left 90° intervals *(arriving)* |
|
||||
| FC | STM32F722 — UART bridge `/dev/ttyACM0` @ 921600 |
|
||||
|
||||
---
|
||||
|
||||
## 1. OS & ROS2 Environment
|
||||
## 1. OS & ROS2
|
||||
|
||||
### Recommended: Docker on JetPack 4.6 (Ubuntu 18.04 / L4T 32.x)
|
||||
JetPack 6 = Ubuntu 22.04 → ROS2 Humble via **native apt** (no Docker workarounds needed).
|
||||
|
||||
Jetson Nano ships with JetPack 4.6 (Ubuntu 18.04). Native ROS2 Humble requires Ubuntu 22.04, so **Docker is the correct approach**:
|
||||
```bash
|
||||
sudo apt install ros-humble-desktop ros-humble-rtabmap-ros \
|
||||
ros-humble-rplidar-ros ros-humble-realsense2-camera \
|
||||
ros-humble-slam-toolbox ros-humble-nav2-bringup
|
||||
```
|
||||
|
||||
- NVIDIA provides official ROS2 containers for Jetson via [dusty-nv/jetson-containers](https://github.com/dusty-nv/jetson-containers)
|
||||
- Container: `dustynv/ros:humble-ros-base-l4t-r32.7.1` (arm64, CUDA 10.2)
|
||||
- Compose file pins container, mounts device nodes (`/dev/video*`, `/dev/ttyUSB*`), and handles GPU access
|
||||
|
||||
**Alternative: JetPack 5.x (Ubuntu 20.04)** allows native ROS2 Foxy but requires flashing newer JetPack — only worth it if we need direct hardware access outside Docker.
|
||||
|
||||
**Decision:** Use JetPack 4.6 + Docker (Humble). Fastest path, avoids full OS reflash, proven for Nano.
|
||||
Docker still supported for CI. Updated `Dockerfile` uses `nvcr.io/nvidia/l4t-jetpack:r36.2.0`.
|
||||
|
||||
---
|
||||
|
||||
## 2. SLAM Stack Recommendation
|
||||
## 2. SLAM Stack
|
||||
|
||||
### Recommendation: RTAB-Map (primary) with ORB-SLAM3 as fallback
|
||||
### Primary: RTAB-Map (RGB-D + 2D LIDAR fusion)
|
||||
|
||||
#### Why RTAB-Map
|
||||
| Parameter | Nano 4GB (old) | **Orin Nano Super** |
|
||||
|-----------|---------------|---------------------|
|
||||
| Detection rate | 2 Hz | **10 Hz** |
|
||||
| Visual features | 400 | **1000** |
|
||||
| D435i profile | 640×480×15fps | **848×480×30fps** |
|
||||
| 3D point cloud | disabled | **enabled** |
|
||||
| Map type | 2D only | **2D + 3D** |
|
||||
| Processing time limit | 700ms | **none** |
|
||||
| Short-term memory | 30 keyframes | **unlimited** |
|
||||
|
||||
| Criterion | ORB-SLAM3 | RTAB-Map |
|
||||
|-----------|-----------|----------|
|
||||
| Sensor fusion (D435i + RPLIDAR) | D435i only | D435i + RPLIDAR natively |
|
||||
| Output map type | Sparse 3D point cloud | Dense 2D occupancy + 3D point cloud |
|
||||
| Nav2 compatibility | Needs wrapper | Direct occupancy map output |
|
||||
| ATE RMSE accuracy | 0.009m | 0.019m |
|
||||
| Nano resource usage | Lower | Higher (needs tuning) |
|
||||
| Loop closure robustness | Good | Excellent |
|
||||
Fusion: RPLIDAR `/scan` (fast 2D loop closure) + D435i depth (3D reconstruction + visual odometry).
|
||||
|
||||
RTAB-Map's `subscribe_scan` mode uses the RPLIDAR A1M8 as the primary 2D odometry front-end (fast, low-CPU) with the D435i providing depth for loop closure and 3D reconstruction. This hybrid approach is well-documented for Nano deployments.
|
||||
|
||||
**Note:** Cannot simultaneously use `subscribe_scan` (2D LIDAR) and `subscribe_scan_cloud` (3D point cloud) in RTAB-Map — use 2D mode.
|
||||
|
||||
#### ORB-SLAM3 Role
|
||||
|
||||
Keep ORB-SLAM3 as a lightweight visual odometry alternative if RTAB-Map proves too heavy for real-time operation. Can feed its odometry output into RTAB-Map's map management node.
|
||||
### Secondary: slam_toolbox (LIDAR-only localization / pre-built map mode)
|
||||
|
||||
---
|
||||
|
||||
## 3. Software Architecture
|
||||
## 3. Architecture
|
||||
|
||||
```
|
||||
┌─────────────────────────────────────────────────────┐
|
||||
│ Jetson Nano (Docker) │
|
||||
│ │
|
||||
│ ┌───────────────┐ ┌──────────────────────────┐ │
|
||||
│ │ realsense2_ │ │ rplidar_ros2 │ │
|
||||
│ │ camera node │ │ /scan (LaserScan) │ │
|
||||
│ │ │ │ 5.5Hz, 360°, 12m range │ │
|
||||
│ │ /depth/image │ └──────────┬───────────────┘ │
|
||||
│ │ /color/image │ │ │
|
||||
│ │ /imu │ │ │
|
||||
│ └──────┬────────┘ │ │
|
||||
│ │ │ │
|
||||
│ └──────────┬─────────────┘ │
|
||||
│ ▼ │
|
||||
│ ┌──────────────────┐ │
|
||||
│ │ rtabmap_ros │ │
|
||||
│ │ │ │
|
||||
│ │ subscribe_scan=true (RPLIDAR) │
|
||||
│ │ subscribe_rgbd=true (D435i depth) │
|
||||
│ │ │ │
|
||||
│ │ → /map (OccupancyGrid) │
|
||||
│ │ → /rtabmap/odom │
|
||||
│ │ → /rtabmap/cloud_map (3D) │
|
||||
│ └──────────┬────────┘ │
|
||||
│ │ │
|
||||
│ ▼ │
|
||||
│ ┌──────────────────┐ │
|
||||
│ │ nav2 stack │ (Phase 2b) │
|
||||
│ │ (reduced freq) │ │
|
||||
│ │ 5-10Hz costmap │ │
|
||||
│ └──────────────────┘ │
|
||||
└─────────────────────────────────────────────────────┘
|
||||
Jetson Orin Nano Super (Ubuntu 22.04 / JetPack 6 / CUDA 12.x)
|
||||
|
||||
realsense2_camera rplidar_ros
|
||||
848×480×30fps /scan ~5.5Hz 360°
|
||||
/camera/color │
|
||||
/camera/depth │
|
||||
/camera/imu ~400Hz │
|
||||
│ │
|
||||
USB3 (D435i) USB2 (RPLIDAR)
|
||||
└──────────┬─────────┘
|
||||
▼
|
||||
rtabmap_ros
|
||||
10Hz | 3D cloud | 1000 features
|
||||
→ /rtabmap/map (OccupancyGrid)
|
||||
→ /rtabmap/cloud_map (PointCloud2)
|
||||
→ /rtabmap/odom (Odometry)
|
||||
│
|
||||
▼
|
||||
Nav2 stack (Phase 2b)
|
||||
20Hz costmap
|
||||
/cmd_vel → STM32
|
||||
|
||||
4× IMX219 CSI (Phase 2c — pending hardware)
|
||||
front/right/rear/left 160°
|
||||
→ panoramic stitch, person tracking
|
||||
```
|
||||
|
||||
### ROS2 Node Graph
|
||||
---
|
||||
|
||||
| Node | Package | Key Topics |
|
||||
|------|---------|------------|
|
||||
| `camera/realsense2_camera_node` | `realsense2_camera` | `/camera/depth/image_rect_raw`, `/camera/color/image_raw`, `/camera/imu` |
|
||||
| `rplidar_node` | `rplidar_ros` | `/scan` |
|
||||
| `rtabmap` | `rtabmap_ros` | `/map`, `/rtabmap/odom`, `/rtabmap/cloud_map` |
|
||||
| `robot_state_publisher` | `robot_state_publisher` | `/tf` (static transforms) |
|
||||
## 4. Phases
|
||||
|
||||
| Phase | Status | Description |
|
||||
|-------|--------|-------------|
|
||||
| 2a | ✅ Done (PR #17) | Sensor drivers — `saltybot_bringup` package |
|
||||
| 2a+ | This PR | Orin update: Dockerfile JetPack 6, RTAB-Map launch + config |
|
||||
| 2b | Pending | Nav2 integration (separate bead, after Phase 1 balance) |
|
||||
| 2c | Pending | 4× IMX219 surround vision (new bead, after hardware arrives) |
|
||||
|
||||
---
|
||||
|
||||
## 4. Implementation Phases
|
||||
## 5. RTAB-Map Config (Orin)
|
||||
|
||||
### Phase 2a — SLAM Bring-up (this bead, bd-wax)
|
||||
|
||||
**Deliverables:**
|
||||
- [ ] Docker Compose file (`docker/slam/docker-compose.yml`)
|
||||
- [ ] ROS2 Humble container with RTAB-Map + RealSense + RPLIDAR packages
|
||||
- [ ] Launch file: `launch/slam.launch.py` (RTAB-Map + both sensor nodes)
|
||||
- [ ] URDF/static TF: D435i and RPLIDAR positions on robot frame
|
||||
- [ ] `README.md` for Jetson setup instructions
|
||||
|
||||
**Out of scope (Phase 2b):**
|
||||
- Nav2 autonomous navigation
|
||||
- Person-following
|
||||
- Integration with STM32 motor commands (needs Phase 1 balance complete first)
|
||||
|
||||
### Phase 2b — Nav2 Integration (separate bead)
|
||||
|
||||
- Nav2 stack with pre-built occupancy maps
|
||||
- 5–10Hz costmap updates (reduced from desktop default 20Hz)
|
||||
- Velocity command bridge: Nav2 `/cmd_vel` → STM32 via serial/ROS2 bridge
|
||||
- Person detection (YOLOv5 on Nano, or TensorRT-optimized)
|
||||
|
||||
---
|
||||
|
||||
## 5. Key Configuration Parameters
|
||||
|
||||
### RTAB-Map Tuning for Jetson Nano
|
||||
Full config: `jetson/config/rtabmap_params.yaml`
|
||||
|
||||
```yaml
|
||||
# rtabmap_ros params — power/performance tradeoffs for Nano
|
||||
rtabmap:
|
||||
Rtabmap/DetectionRate: "2" # Process keyframes at 2Hz (not every frame)
|
||||
Rtabmap/TimeThr: "700" # Max processing time 700ms per iteration
|
||||
Kp/MaxFeatures: "400" # Reduce keypoints from default 1000
|
||||
Vis/MaxFeatures: "400"
|
||||
RGBD/LinearUpdate: "0.1" # Only update map if moved 10cm
|
||||
RGBD/AngularUpdate: "0.09" # Or rotated ~5 degrees
|
||||
Mem/STMSize: "30" # Short-term memory limit (saves RAM)
|
||||
Grid/3D: "false" # Use 2D occupancy only (lighter)
|
||||
Grid/RangeMin: "0.5" # Ignore points closer than 0.5m
|
||||
Grid/RangeMax: "5.0" # Limit to 5m (A1M8 is reliable to ~8m)
|
||||
```
|
||||
|
||||
### RealSense D435i Launch Params
|
||||
|
||||
```yaml
|
||||
# realsense2_camera — reduce load on Nano
|
||||
depth_module.profile: "640x480x15" # 15fps depth (not 90fps)
|
||||
rgb_camera.profile: "640x480x15" # 15fps color
|
||||
enable_gyro: true
|
||||
enable_accel: true
|
||||
unite_imu_method: 2 # Publish unified /camera/imu topic
|
||||
align_depth.enable: true
|
||||
```
|
||||
|
||||
### RPLIDAR
|
||||
|
||||
```yaml
|
||||
serial_port: "/dev/ttyUSB0"
|
||||
serial_baudrate: 115200
|
||||
scan_mode: "Standard" # A1M8 only supports Standard mode
|
||||
frame_id: "laser_frame"
|
||||
Rtabmap/DetectionRate: "10" # was 2 on Nano
|
||||
Kp/MaxFeatures: "1000" # was 400
|
||||
RGBD/LinearUpdate: "0.05" # 5cm (was 10cm)
|
||||
RGBD/AngularUpdate: "0.05" # ~3° (was 5°)
|
||||
Grid/3D: "true" # 3D cloud enabled (was false)
|
||||
Rtabmap/TimeThr: "0" # no limit (was 700ms)
|
||||
Mem/STMSize: "0" # unlimited (was 30)
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## 6. Static TF / URDF Robot Frame
|
||||
|
||||
Robot coordinate frame (`base_link`) transforms needed:
|
||||
## 6. 4× IMX219 Layout (Phase 2c)
|
||||
|
||||
```
|
||||
base_link
|
||||
├── laser_frame (RPLIDAR A1M8 — top center of robot)
|
||||
├── camera_link (RealSense D435i — front, ~camera_height above base)
|
||||
│ ├── camera_depth_frame
|
||||
│ └── camera_imu_frame
|
||||
└── imu_link (STM32 IMU — FC board location)
|
||||
FRONT (CSI0) 160°
|
||||
LEFT (CSI3) × RIGHT (CSI1)
|
||||
REAR (CSI2) 160°
|
||||
```
|
||||
|
||||
Transforms will be defined in `urdf/saltybot.urdf.xacro` with measured offsets once hardware is physically mounted.
|
||||
90° between cameras, 160° FOV → ~70° overlap at each boundary, full 360° coverage.
|
||||
|
||||
ROS topics (planned): `/camera/{front,right,rear,left}/image_raw` @ 30Hz,
|
||||
`/camera/panoramic/image_raw` @ 15Hz (stitched equirectangular).
|
||||
|
||||
---
|
||||
|
||||
## 7. Power Budget Concern
|
||||
## 7. Power Budget (Orin Nano Super)
|
||||
|
||||
Jetson Nano 4GB maximum draw: **10W** (5V/2A barrel jack mode)
|
||||
| Scenario | Total |
|
||||
|----------|-------|
|
||||
| SLAM active (RTAB-Map + D435i + RPLIDAR) | ~16W |
|
||||
| + 4× IMX219 | ~17W |
|
||||
| + Nav2 + TensorRT person detection | ~22W |
|
||||
|
||||
| Component | Estimated Draw |
|
||||
|-----------|---------------|
|
||||
| Jetson Nano (under SLAM load) | 7–8W |
|
||||
| RealSense D435i (USB3) | 1.5W |
|
||||
| RPLIDAR A1M8 (USB) | 0.5W |
|
||||
| **Total** | **~10W** |
|
||||
|
||||
**Risk:** Marginal power budget. Recommend:
|
||||
1. Use 5V/4A supply (requires Jetson J48 header, not USB-C)
|
||||
2. Disable Jetson display output (`sudo systemctl disable gdm3`)
|
||||
3. Use `nvpmodel -m 1` (5W mode) during mapping-only tasks
|
||||
4. External powered USB hub for peripherals
|
||||
Orin Nano Super TDP: **25W max**. Recommended PSU: 5V 5A (25W) from robot buck converter.
|
||||
No power gating needed. Run `sudo nvpmodel -m 0 && sudo jetson_clocks` for full performance.
|
||||
|
||||
---
|
||||
|
||||
## 8. Milestone Checklist
|
||||
## 8. Milestones
|
||||
|
||||
- [ ] Flash JetPack 4.6 on Nano (or verify existing install)
|
||||
- [ ] Install Docker + NVIDIA Container Runtime on Nano
|
||||
- [ ] Pull `dustynv/ros:humble-ros-base-l4t-r32.7.1` container
|
||||
- [ ] Verify D435i recognized: `realsense-viewer` or `rs-enumerate-devices`
|
||||
- [ ] Verify RPLIDAR port: `ls /dev/ttyUSB*`
|
||||
- [ ] Build/pull `realsense2_camera` ROS2 package in container
|
||||
- [ ] Build/pull `rplidar_ros` ROS2 package in container
|
||||
- [ ] Build/pull `rtabmap_ros` ROS2 package in container
|
||||
- [ ] Test individual sensor topics with `ros2 topic echo`
|
||||
- [ ] Run SLAM launch file — verify `/map` published
|
||||
- [ ] Record rosbag for offline tuning
|
||||
- [ ] Document measured TF offsets (physical mount positions)
|
||||
- [ ] Write Phase 2b bead for Nav2 integration
|
||||
- [ ] Flash JetPack 6 on Orin (arriving March 1)
|
||||
- [ ] `sudo apt install ros-humble-desktop ros-humble-rtabmap-ros ...`
|
||||
- [ ] Verify D435i: `lsusb | grep "8086:0b3a"`
|
||||
- [ ] Verify RPLIDAR: `ls /dev/rplidar`
|
||||
- [ ] `colcon build --packages-select saltybot_bringup`
|
||||
- [ ] `ros2 launch saltybot_bringup sensors.launch.py` — verify topics
|
||||
- [ ] `ros2 launch saltybot_bringup slam_rtabmap.launch.py` — verify `/rtabmap/map`
|
||||
- [ ] `ros2 topic hz /rtabmap/cloud_map` — verify 3D cloud
|
||||
- [ ] Record rosbag, monitor `tegrastats` for thermal headroom
|
||||
- [ ] Update static TF with real mount measurements
|
||||
- [ ] Open bead: Phase 2b Nav2
|
||||
- [ ] Open bead: Phase 2c IMX219 (after hardware arrives)
|
||||
|
||||
---
|
||||
|
||||
## 9. Repo Structure (to be created)
|
||||
## 9. References
|
||||
|
||||
```
|
||||
saltylab-firmware/
|
||||
└── projects/
|
||||
└── saltybot/
|
||||
├── SLAM-SETUP-PLAN.md ← this file
|
||||
├── SALTYLAB.md ← main design doc (TBD)
|
||||
└── slam/
|
||||
├── docker/
|
||||
│ ├── docker-compose.yml
|
||||
│ └── Dockerfile.slam
|
||||
├── launch/
|
||||
│ └── slam.launch.py
|
||||
├── config/
|
||||
│ ├── rtabmap_params.yaml
|
||||
│ └── realsense_params.yaml
|
||||
└── urdf/
|
||||
└── saltybot.urdf.xacro
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## 10. References
|
||||
|
||||
- [dusty-nv/jetson-containers](https://github.com/dusty-nv/jetson-containers) — official NVIDIA ROS2 Docker containers for Jetson
|
||||
- [rtabmap_ros](https://github.com/introlab/rtabmap_ros) — RTAB-Map ROS2 wrapper
|
||||
- [realsense-ros](https://github.com/IntelRealSense/realsense-ros) — Intel RealSense ROS2 wrapper
|
||||
- [rplidar_ros](https://github.com/Slamtec/rplidar_ros) — Slamtec RPLIDAR ROS2 package
|
||||
- [reedjacobp/JetsonBot](https://github.com/reedjacobp/JetsonBot) — Nano + D435i + RPLIDAR reference implementation
|
||||
- [RTAB-Map D435 + RPLidar discussion](https://answers.ros.org/question/367019/using-2-d435-cameras-and-an-rplidar-with-rtabmap/)
|
||||
- [Comparative SLAM evaluation (2024)](https://arxiv.org/html/2401.02816v1)
|
||||
- [Jetson Orin Nano Super](https://www.nvidia.com/en-us/autonomous-machines/embedded-systems/jetson-orin/)
|
||||
- [JetPack 6 / L4T R36](https://developer.nvidia.com/embedded/jetpack)
|
||||
- [dusty-nv/jetson-containers JetPack 6](https://github.com/dusty-nv/jetson-containers)
|
||||
- [rtabmap_ros ROS2](https://github.com/introlab/rtabmap_ros)
|
||||
- [realsense-ros](https://github.com/IntelRealSense/realsense-ros)
|
||||
- [IMX219 / nvarguscamerasrc on Jetson](https://developer.ridgerun.com/wiki/index.php/NVIDIA_Jetson_ISP_Control)
|
||||
|
||||
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Reference in New Issue
Block a user