jetson/Dockerfile

@@ -1,15 +1,12 @@
-# Jetson Orin Nano Super — ROS2 Humble dev container
+# Jetson Nano — ROS2 Humble dev container
-# Base: JetPack 6 (L4T R36.2.0) + CUDA 12.x / Ubuntu 22.04
+# Base: JetPack 4.6 (L4T R32.6.1) + CUDA 10.2
-#
+# Arch: ARM64 (aarch64)
-# Hardware: Jetson Orin Nano Super 8GB (67 TOPS, 1024-core Ampere)
-# Previous: Jetson Nano 4GB (JetPack 4.6 / L4T R32.6.1) — see git history
 
-FROM nvcr.io/nvidia/l4t-jetpack:r36.2.0
+FROM nvcr.io/nvidia/l4t-base:r32.6.1
 
-LABEL maintainer="sl-perception <saltylab>"
+LABEL maintainer="sl-jetson <saltylab>"
-LABEL description="ROS2 Humble + SLAM stack for Jetson Orin Nano Super self-balancing robot"
+LABEL description="ROS2 Humble + SLAM stack for Jetson Nano self-balancing robot"
-LABEL jetpack="6.0"
+LABEL jetpack="4.6"
-LABEL l4t="r36.2.0"
 LABEL ros_distro="humble"
 
 ENV DEBIAN_FRONTEND=noninteractive
@@ -18,29 +15,32 @@ ENV ROS_ROOT=/opt/ros/${ROS_DISTRO}
 ENV PYTHONDONTWRITEBYTECODE=1
 ENV PYTHONUNBUFFERED=1
 
-# ── Locale ─────────────────────────────────────────────────────────────────────
+# ── System deps ────────────────────────────────────────────────────────────────
-RUN apt-get update && apt-get install -y --no-install-recommends \
-    locales tzdata \
-    && locale-gen en_US.UTF-8 \
-    && rm -rf /var/lib/apt/lists/*
-ENV LANG=en_US.UTF-8
-
-# ── System deps ─────────────────────────────────────────────────────────────────
 RUN apt-get update && apt-get install -y --no-install-recommends \
+    # Build tools
     build-essential cmake git wget curl \
+    # Python
     python3-dev python3-pip python3-setuptools python3-wheel \
+    # Serial / I2C / SPI
     i2c-tools libi2c-dev python3-smbus \
     picocom minicom setserial \
+    # USB
     usbutils libusb-1.0-0-dev \
-    htop tmux nano \
+    # Misc
+    locales tzdata htop tmux nano \
+    # Networking
     net-tools iputils-ping \
     && rm -rf /var/lib/apt/lists/*
 
-# ── ROS2 Humble (Ubuntu 22.04 native — standard apt, no ARM64 workarounds) ─────
+RUN locale-gen en_US.UTF-8
+ENV LANG=en_US.UTF-8
+
+# ── ROS2 Humble (from ROS2 apt repo — ARM64 build) ─────────────────────────────
+# Note: official humble debs for ARM64/L4T are provided via NVIDIA Isaac ROS
+# or via ros2-apt-source for 20.04 focal.
 RUN curl -sSL https://raw.githubusercontent.com/ros/rosdistro/master/ros.asc \
-        | gpg --dearmor -o /usr/share/keyrings/ros-archive-keyring.gpg && \
+        | apt-key add - && \
-    echo "deb [arch=arm64 signed-by=/usr/share/keyrings/ros-archive-keyring.gpg] \
+    echo "deb [arch=arm64] http://packages.ros.org/ros2/ubuntu focal main" \
-        http://packages.ros.org/ros2/ubuntu jammy main" \
         > /etc/apt/sources.list.d/ros2.list && \
     apt-get update && apt-get install -y --no-install-recommends \
         ros-humble-ros-base \
@@ -51,45 +51,50 @@ RUN curl -sSL https://raw.githubusercontent.com/ros/rosdistro/master/ros.asc \
     && rosdep init && rosdep update \
     && rm -rf /var/lib/apt/lists/*
 
-# ── SLAM / Nav / Sensor packages ───────────────────────────────────────────────
+# ── Nav / SLAM / sensor packages ──────────────────────────────────────────────
 RUN apt-get update && apt-get install -y --no-install-recommends \
-    ros-humble-rtabmap-ros \
-    ros-humble-slam-toolbox \
     ros-humble-nav2-bringup \
+    ros-humble-slam-toolbox \
     ros-humble-robot-localization \
     ros-humble-rplidar-ros \
     ros-humble-realsense2-camera \
     ros-humble-realsense2-description \
     ros-humble-tf2-tools \
-    ros-humble-robot-state-publisher \
     ros-humble-rqt \
     ros-humble-rqt-common-plugins \
     ros-humble-rviz2 \
     ros-humble-rosbridge-server \
-    ros-humble-image-transport-plugins \
-    ros-humble-v4l2-camera \
     && rm -rf /var/lib/apt/lists/*
 
-# ── GPIO / serial Python libs ───────────────────────────────────────────────────
+# ── GPIO / serial Python libs ──────────────────────────────────────────────────
 RUN pip3 install --no-cache-dir \
-    Jetson.GPIO pyserial smbus2 numpy scipy
+    Jetson.GPIO \
+    pyserial \
+    smbus2 \
+    adafruit-blinka \
+    RPi.GPIO \
+    numpy \
+    scipy
 
-# ── RealSense SDK (librealsense2 ARM64 for JetPack 6) ─────────────────────────
+# ── RealSense SDK (librealsense2 ARM64) ───────────────────────────────────────
+# Pre-built for L4T — install from Jetson Hacks script or apt source
 RUN apt-get update && apt-get install -y --no-install-recommends \
     libssl-dev libusb-1.0-0-dev pkg-config libgtk-3-dev \
     && rm -rf /var/lib/apt/lists/*
 
+# librealsense2 ARM64 wheel (NVIDIA-patched for L4T)
 RUN pip3 install --no-cache-dir pyrealsense2
 
-# ── Workspace setup ────────────────────────────────────────────────────────────
+# ── Workspace setup ───────────────────────────────────────────────────────────
 RUN mkdir -p /ros2_ws/src
 WORKDIR /ros2_ws
 
+# Source ROS2 in every shell
 RUN echo "source /opt/ros/${ROS_DISTRO}/setup.bash" >> /root/.bashrc && \
     echo "source /ros2_ws/install/local_setup.bash 2>/dev/null || true" >> /root/.bashrc && \
     echo "export RMW_IMPLEMENTATION=rmw_cyclonedds_cpp" >> /root/.bashrc
 
-# ── Entrypoint ─────────────────────────────────────────────────────────────────
+# ── Entrypoint ────────────────────────────────────────────────────────────────
 COPY scripts/entrypoint.sh /entrypoint.sh
 RUN chmod +x /entrypoint.sh
 

jetson/config/realsense_d435i.yaml

@@ -1,33 +1,53 @@
-# RealSense D435i configuration — Jetson Orin Nano Super
+# RealSense D435i configuration — Jetson Nano (power-budget tuned)
 #
-# Previous Nano 4GB settings (640x480x15, no point cloud) replaced.
+# Profile format: WxHxFPS
-# Orin Nano Super has ample Ampere GPU headroom for 848x480x30fps + point cloud.
+# Constraint: ~10W total budget. 640x480x15 saves ~0.4W vs 30fps.
 #
-# Reference topics:
+# Reference topics at these settings:
-#   /camera/color/image_raw               848x480  30 Hz   RGB8
+#   /camera/color/image_raw               640x480  15 Hz   RGB8
-#   /camera/depth/image_rect_raw          848x480  30 Hz   Z16
+#   /camera/depth/image_rect_raw          640x480  15 Hz   Z16
-#   /camera/aligned_depth_to_color/image_raw  848x480  30 Hz  Z16
+#   /camera/aligned_depth_to_color/image_raw  640x480  15 Hz  Z16
-#   /camera/color/camera_info             848x480  30 Hz
+#   /camera/imu                           6-axis   ~200 Hz  (accel@100Hz + gyro@400Hz fused)
-#   /camera/depth/camera_info             848x480  30 Hz
+#   /camera/color/camera_info             640x480  15 Hz
-#   /camera/imu                           ~400 Hz  (gyro@400Hz + accel@100Hz fused)
+#   /camera/depth/camera_info             640x480  15 Hz
-#   /camera/points                        PointCloud2  30 Hz
+#
+# Hardware IMU: Bosch BMI055
+#   Accelerometer native rate: 100 Hz
+#   Gyroscope native rate:     400 Hz
+#   unite_imu_method=2: linearly interpolates accel to match gyro timestamps
 
 camera:
   ros__parameters:
-    depth_module.profile: "848x480x30"
+    # ── Streams ──────────────────────────────────────────────────────────────
-    rgb_camera.profile:   "848x480x30"
+    depth_module.profile: "640x480x15"
+    rgb_camera.profile:   "640x480x15"
 
     enable_depth:   true
     enable_color:   true
-    enable_infra1:  false
+    enable_infra1:  false    # not needed for RGB-D SLAM
     enable_infra2:  false
 
+    # ── IMU ──────────────────────────────────────────────────────────────────
     enable_gyro:          true
     enable_accel:         true
-    unite_imu_method:     2    # linear_interpolation
+    # 0=none  1=copy  2=linear_interpolation
+    # Use 2: aligns accel timestamps to gyro rate, required for sensor fusion
+    unite_imu_method:     2
 
+    # ── Alignment ────────────────────────────────────────────────────────────
+    # Projects depth pixels into RGB frame — required for rtabmap_ros rgbd input
     align_depth.enable:   true
-    pointcloud.enable:    true    # Orin Ampere GPU handles this without issue
 
+    # ── Point cloud ──────────────────────────────────────────────────────────
+    # Disabled: rtabmap_ros generates its own from aligned depth.
+    # Maxwell GPU cannot handle both simultaneously at budget.
+    pointcloud.enable:    false
+
+    # ── TF ───────────────────────────────────────────────────────────────────
     publish_tf:       true
-    tf_publish_rate:  0.0
+    tf_publish_rate:  0.0    # 0 = publish static transforms only (no redundant timer)
+
+    # ── Device ───────────────────────────────────────────────────────────────
+    # Leave serial_no empty to auto-select first found device
+    # serial_no: ''
+    # device_type: d435i

jetson/config/rtabmap_params.yaml

@@ -1,78 +0,0 @@
-# RTAB-Map configuration — Jetson Orin Nano Super
-#
-# Hardware context: 67 TOPS, 1024-core Ampere GPU, 8GB RAM
-# All Nano-era constraints (2Hz cap, 400 features, no 3D) removed.
-#
-# Sensor inputs:
-#   /scan                    LaserScan from RPLIDAR A1M8    ~5.5 Hz
-#   /camera/color/image_raw  RGB from RealSense D435i       30 Hz
-#   /camera/depth/image_rect_raw  Depth from D435i          30 Hz
-#   /camera/color/camera_info    Camera intrinsics          30 Hz
-#
-# Outputs:
-#   /rtabmap/map             OccupancyGrid (2D occupancy)
-#   /rtabmap/cloud_map       PointCloud2   (3D point cloud, enabled)
-#   /rtabmap/odom            Odometry      (visual-inertial odometry)
-#   /rtabmap/mapData         Map data for serialization/loop closure
-#
-# Frame assumptions (match sensors.launch.py static TF):
-#   map → odom → base_link → laser
-#                          → camera_link
-
-rtabmap:
-  ros__parameters:
-    # ── Core rate and timing ───────────────────────────────────────────────────
-    # Process at 10Hz — far below D435i 30fps ceiling, still 5x faster than Nano
-    Rtabmap/DetectionRate:    "10"
-    # No processing time limit — Orin has headroom (Nano was 700ms)
-    Rtabmap/TimeThr:          "0"
-    # Update map every 5cm or ~3° rotation (was 10cm / 5°)
-    RGBD/LinearUpdate:        "0.05"
-    RGBD/AngularUpdate:       "0.05"
-
-    # ── Visual features ────────────────────────────────────────────────────────
-    # 1000 ORB features per frame (Nano was 400)
-    Kp/MaxFeatures:           "1000"
-    Vis/MaxFeatures:          "1000"
-
-    # ── Memory ────────────────────────────────────────────────────────────────
-    # Unlimited short-term memory — 8GB RAM (Nano was 30 keyframes)
-    Mem/STMSize:              "0"
-    # Keep full map in working memory
-    Mem/IncrementalMemory:    "true"
-
-    # ── Map generation ────────────────────────────────────────────────────────
-    # 3D occupancy grid enabled — Ampere GPU handles point cloud generation
-    Grid/3D:                  "true"
-    Grid/CellSize:            "0.05"    # 5cm voxels
-    Grid/RangeMin:            "0.3"     # ignore points closer than 30cm
-    Grid/RangeMax:            "8.0"     # clip at A1M8 reliable range
-
-    # ── Sensor subscriptions ──────────────────────────────────────────────────
-    # Subscribe to both RPLIDAR scan (fast 2D) and D435i depth (3D)
-    subscribe_scan:           "true"
-    subscribe_rgbd:           "true"
-    subscribe_odom_info:      "false"
-
-    # ── Loop closure ──────────────────────────────────────────────────────────
-    # More aggressive loop closure — Orin can handle it
-    RGBD/LoopClosureReextractFeatures: "true"
-    Kp/IncrementalFlann:      "true"
-
-    # ── Odometry ──────────────────────────────────────────────────────────────
-    # Use F2M (frame-to-map) visual odometry — more accurate on Orin
-    Odom/Strategy:            "0"        # 0=F2M, 1=F2F
-    Odom/ResetCountdown:      "1"
-    OdomF2M/MaxSize:          "2000"
-
-    # ── RGBD node input topics ─────────────────────────────────────────────────
-    rgb_topic:              /camera/color/image_raw
-    depth_topic:            /camera/depth/image_rect_raw
-    camera_info_topic:      /camera/color/camera_info
-    depth_camera_info_topic: /camera/depth/camera_info
-    scan_topic:             /scan
-
-    # ── Output ────────────────────────────────────────────────────────────────
-    # Publish 3D point cloud map
-    cloud_output_voxelized: "true"
-    cloud_voxel_size:       "0.05"      # match Grid/CellSize

jetson/config/slam_toolbox_params.yaml

@@ -1,37 +1,44 @@
 # slam_toolbox — online async SLAM configuration
-# Jetson Orin Nano Super — all Nano rate caps removed.
+# Tuned for Jetson Nano 4GB (constrained CPU/RAM, indoor mapping)
-#
-# Primary SLAM is now RTAB-Map (slam_rtabmap.launch.py).
-# slam_toolbox retained for LIDAR-only localization against pre-built maps.
 #
 # Input:  /scan  (LaserScan from RPLIDAR A1M8, ~5.5 Hz)
-# Output: /map   (OccupancyGrid)
+# Output: /map   (OccupancyGrid, updated every map_update_interval seconds)
+#
+# Frame assumptions (must match sensors.launch.py static TF):
+#   map → odom → base_link → laser
+#   (odom not yet published — slam_toolbox handles this via scan matching)
 
 slam_toolbox:
   ros__parameters:
+    # ── Frames ───────────────────────────────────────────────────────────────
     odom_frame:   odom
     map_frame:    map
     base_frame:   base_link
     scan_topic:   /scan
-    mode:         mapping
+    mode:         mapping    # 'mapping' or 'localization'
 
-    resolution:               0.05
+    # ── Map params ───────────────────────────────────────────────────────────
-    max_laser_range:          8.0
+    resolution:            0.05    # 5 cm/cell — good balance for A1M8 angular res
-    map_update_interval:      1.0     # 1s (was 5s on Nano)
+    max_laser_range:       8.0     # clip to reliable range of A1M8 (spec: 12m)
-    minimum_travel_distance:  0.2
+    map_update_interval:   5.0     # seconds between full map publishes (saves CPU)
-    minimum_travel_heading:   0.2
+    minimum_travel_distance:  0.3  # only update after moving 30 cm
+    minimum_travel_heading:   0.3  # or rotating ~17°
 
-    minimum_time_interval:  0.1    # ~10Hz processing (was 0.5s on Nano)
+    # ── Performance (Nano-specific) ───────────────────────────────────────────
+    # Reduce scan processing rate to stay within ~3.5W CPU budget
+    minimum_time_interval:  0.5   # max 2 Hz scan processing (A1M8 is ~5.5 Hz)
     transform_timeout:      0.2
     tf_buffer_duration:     30.0
-    stack_size_to_use:      40000000
+    stack_size_to_use:      40000000   # 40 MB stack
-    enable_interactive_mode: false
+    enable_interactive_mode: false     # disable interactive editing (saves CPU)
 
+    # ── Scan matching ─────────────────────────────────────────────────────────
     use_scan_matching:    true
     use_scan_barycenter:  true
-    scan_buffer_size:     20
+    scan_buffer_size:     10
     scan_buffer_maximum_scan_distance: 10.0
 
+    # ── Loop closure ──────────────────────────────────────────────────────────
     do_loop_closing:                      true
     loop_match_minimum_chain_size:        10
     loop_match_maximum_variance_coarse:   3.0
@@ -39,25 +46,31 @@ slam_toolbox:
     loop_match_minimum_response_fine:     0.45
     loop_search_maximum_distance:         3.0
 
+    # ── Correlation (coarse scan matching) ───────────────────────────────────
     correlation_search_space_dimension:      0.5
     correlation_search_space_resolution:     0.01
     correlation_search_space_smear_deviation: 0.1
 
+    # ── Loop search space ─────────────────────────────────────────────────────
     loop_search_space_dimension:      8.0
     loop_search_space_resolution:     0.05
     loop_search_space_smear_deviation: 0.03
 
+    # ── Response expansion ────────────────────────────────────────────────────
     link_match_minimum_response_fine:  0.1
     link_scan_maximum_distance:        1.5
     use_response_expansion:            true
+
+    # ── Penalties (scan matcher quality thresholds) ───────────────────────────
     distance_variance_penalty: 0.5
     angle_variance_penalty:    1.0
-    fine_search_angle_offset:         0.00349
+    fine_search_angle_offset:  0.00349    # ~0.2°
-    coarse_search_angle_offset:       0.349
+    coarse_search_angle_offset: 0.349     # ~20°
-    coarse_angle_resolution:          0.0349
+    coarse_angle_resolution:   0.0349     # ~2°
     minimum_angle_penalty:     0.9
     minimum_distance_penalty:  0.5
 
+    # ── Solver ────────────────────────────────────────────────────────────────
     solver_plugin:           solver_plugins::CeresSolver
     ceres_linear_solver:     SPARSE_NORMAL_CHOLESKY
     ceres_preconditioner:    SCHUR_JACOBI

jetson/docker-compose.yml

@@ -8,7 +8,7 @@ services:
 
   # ── Core ROS2 + SLAM node ─────────────────────────────────────────────────
   saltybot-ros2:
-    image: saltybot/ros2-humble:jetson-orin
+    image: saltybot/ros2-humble:jetson-nano
     build:
       context: .
       dockerfile: Dockerfile
@@ -51,7 +51,7 @@ services:
     command: >
       bash -c "
         source /opt/ros/humble/setup.bash &&
-        ros2 launch saltybot_bringup slam_rtabmap.launch.py
+        ros2 launch saltybot_bringup slam.launch.py
       "
 
   # ── RPLIDAR driver node ────────────────────────────────────────────────────

jetson/ros2_ws/src/saltybot_bringup/launch/slam_rtabmap.launch.py

@@ -1,114 +0,0 @@
-"""
-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
-    ])

projects/saltybot/SLAM-SETUP-PLAN.md

@@ -1,167 +1,264 @@
-# SLAM Setup Plan — Jetson Orin Nano Super
+# bd-wax: Jetson Nano + RealSense D435i + RPLIDAR SLAM Setup — Technical Plan
 
-**Bead:** bd-wax (plan), bd-a2j (sensor drivers done PR #17)
+**Bead:** bd-wax
-**Phase:** 2 | **Owner:** sl-perception
+**Phase:** 2 (lower priority than Phase 1 balance)
-**Updated:** 2026-03-01 — revised for Jetson Orin Nano Super (replaces Nano 4GB)
+**Owner:** sl-perception
-
+**Hardware:** Jetson Nano 4GB + Intel RealSense D435i + RPLIDAR A1M8
-> All Nano-era constraints (10W cap, 2Hz detection, 400 features, no 3D) are obsolete.
+**Goal:** Indoor SLAM, mapping, and autonomous navigation (person-following)
 
 ---
 
-## Hardware
+## Hardware Summary
 
 | Component | Specs |
 |-----------|-------|
-| AI Brain | **Jetson Orin Nano Super 8GB** — 6-core A78AE, 1024-core Ampere, **67 TOPS**, JetPack 6 |
+| Jetson Nano 4GB | Quad-core ARM Cortex-A57 @ 1.43GHz, 128-core Maxwell GPU, 4GB LPDDR4 |
-| Depth Cam | Intel RealSense D435i — 848×480 @ 90fps, BMI055 IMU |
+| RealSense D435i | Stereo depth (0.1–10m), 848×480 @ 90fps, BMI055 IMU (accel+gyro) |
-| LIDAR | RPLIDAR A1M8 — 360° 2D, 12m range, ~5.5 Hz |
+| RPLIDAR A1M8 | 360° 2D LIDAR, 12m range, 8000 samples/s, ~5.5Hz scan rate |
-| Wide Cams | 4× IMX219 160° CSI — front/right/rear/left 90° intervals *(arriving)* |
-| FC | STM32F722 — UART bridge `/dev/ttyACM0` @ 921600 |
 
 ---
 
-## 1. OS & ROS2
+## 1. OS & ROS2 Environment
 
-JetPack 6 = Ubuntu 22.04 → ROS2 Humble via **native apt** (no Docker workarounds needed).
+### Recommended: Docker on JetPack 4.6 (Ubuntu 18.04 / L4T 32.x)
 
-```bash
+Jetson Nano ships with JetPack 4.6 (Ubuntu 18.04). Native ROS2 Humble requires Ubuntu 22.04, so **Docker is the correct approach**:
-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
-```
 
-Docker still supported for CI. Updated `Dockerfile` uses `nvcr.io/nvidia/l4t-jetpack:r36.2.0`.
+- 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.
 
 ---
 
-## 2. SLAM Stack
+## 2. SLAM Stack Recommendation
 
-### Primary: RTAB-Map (RGB-D + 2D LIDAR fusion)
+### Recommendation: RTAB-Map (primary) with ORB-SLAM3 as fallback
 
-| Parameter | Nano 4GB (old) | **Orin Nano Super** |
+#### Why RTAB-Map
-|-----------|---------------|---------------------|
-| 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** |
 
-Fusion: RPLIDAR `/scan` (fast 2D loop closure) + D435i depth (3D reconstruction + visual odometry).
+| 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 |
 
-### Secondary: slam_toolbox (LIDAR-only localization / pre-built map mode)
+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.
 
 ---
 
-## 3. Architecture
+## 3. Software Architecture
 
 ```
-Jetson Orin Nano Super (Ubuntu 22.04 / JetPack 6 / CUDA 12.x)
+┌─────────────────────────────────────────────────────┐
-
+│                  Jetson Nano (Docker)                │
-  realsense2_camera          rplidar_ros
-  848×480×30fps              /scan ~5.5Hz 360°
-  /camera/color              │
-  /camera/depth              │
-  /camera/imu ~400Hz         │
 │                                                     │
-        └──────────┬─────────┘
+│  ┌───────────────┐    ┌──────────────────────────┐  │
-                   ▼
+│  │ realsense2_   │    │     rplidar_ros2          │  │
-            rtabmap_ros
+│  │ camera node   │    │  /scan (LaserScan)        │  │
-            10Hz | 3D cloud | 1000 features
+│  │               │    │  5.5Hz, 360°, 12m range   │  │
-            → /rtabmap/map         (OccupancyGrid)
+│  │ /depth/image  │    └──────────┬───────────────┘  │
-            → /rtabmap/cloud_map   (PointCloud2)
+│  │ /color/image  │               │                  │
-            → /rtabmap/odom        (Odometry)
+│  │ /imu          │               │                  │
-                   │
+│  └──────┬────────┘               │                  │
-                   ▼
+│         │                        │                  │
-             Nav2 stack            (Phase 2b)
+│         └──────────┬─────────────┘                  │
-             20Hz costmap
+│                    ▼                                 │
-             /cmd_vel → STM32
+│         ┌──────────────────┐                        │
-
+│         │   rtabmap_ros    │                        │
-  4× IMX219 CSI               (Phase 2c — pending hardware)
+│         │                  │                        │
-  front/right/rear/left 160°
+│         │ subscribe_scan=true (RPLIDAR)              │
-  → panoramic stitch, person tracking
+│         │ subscribe_rgbd=true (D435i depth)          │
+│         │                  │                        │
+│         │ → /map (OccupancyGrid)                    │
+│         │ → /rtabmap/odom                           │
+│         │ → /rtabmap/cloud_map (3D)                 │
+│         └──────────┬────────┘                       │
+│                    │                                │
+│                    ▼                                │
+│         ┌──────────────────┐                        │
+│         │   nav2 stack     │  (Phase 2b)            │
+│         │  (reduced freq)  │                        │
+│         │  5-10Hz costmap  │                        │
+│         └──────────────────┘                        │
+└─────────────────────────────────────────────────────┘
+         │                        │
+    USB3 (D435i)             USB2 (RPLIDAR)
 ```
 
----
+### ROS2 Node Graph
 
-## 4. Phases
+| Node | Package | Key Topics |
-
+|------|---------|------------|
-| Phase | Status | Description |
+| `camera/realsense2_camera_node` | `realsense2_camera` | `/camera/depth/image_rect_raw`, `/camera/color/image_raw`, `/camera/imu` |
-|-------|--------|-------------|
+| `rplidar_node` | `rplidar_ros` | `/scan` |
-| 2a | ✅ Done (PR #17) | Sensor drivers — `saltybot_bringup` package |
+| `rtabmap` | `rtabmap_ros` | `/map`, `/rtabmap/odom`, `/rtabmap/cloud_map` |
-| 2a+ | This PR | Orin update: Dockerfile JetPack 6, RTAB-Map launch + config |
+| `robot_state_publisher` | `robot_state_publisher` | `/tf` (static transforms) |
-| 2b | Pending | Nav2 integration (separate bead, after Phase 1 balance) |
-| 2c | Pending | 4× IMX219 surround vision (new bead, after hardware arrives) |
 
 ---
 
-## 5. RTAB-Map Config (Orin)
+## 4. Implementation Phases
 
-Full config: `jetson/config/rtabmap_params.yaml`
+### 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
 
 ```yaml
-Rtabmap/DetectionRate: "10"     # was 2 on Nano
+# rtabmap_ros params — power/performance tradeoffs for Nano
-Kp/MaxFeatures:        "1000"   # was 400
+rtabmap:
-RGBD/LinearUpdate:     "0.05"   # 5cm  (was 10cm)
+  Rtabmap/DetectionRate: "2"          # Process keyframes at 2Hz (not every frame)
-RGBD/AngularUpdate:    "0.05"   # ~3°  (was 5°)
+  Rtabmap/TimeThr: "700"              # Max processing time 700ms per iteration
-Grid/3D:               "true"   # 3D cloud enabled  (was false)
+  Kp/MaxFeatures: "400"               # Reduce keypoints from default 1000
-Rtabmap/TimeThr:       "0"      # no limit  (was 700ms)
+  Vis/MaxFeatures: "400"
-Mem/STMSize:           "0"      # unlimited  (was 30)
+  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"
 ```
 
 ---
 
-## 6. 4× IMX219 Layout (Phase 2c)
+## 6. Static TF / URDF Robot Frame
+
+Robot coordinate frame (`base_link`) transforms needed:
 
 ```
-      FRONT (CSI0) 160°
+base_link
-LEFT  (CSI3) ×  RIGHT (CSI1)
+├── laser_frame      (RPLIDAR A1M8 — top center of robot)
-      REAR  (CSI2) 160°
+├── camera_link      (RealSense D435i — front, ~camera_height above base)
+│   ├── camera_depth_frame
+│   └── camera_imu_frame
+└── imu_link         (STM32 IMU — FC board location)
 ```
 
-90° between cameras, 160° FOV → ~70° overlap at each boundary, full 360° coverage.
+Transforms will be defined in `urdf/saltybot.urdf.xacro` with measured offsets once hardware is physically mounted.
-
-ROS topics (planned): `/camera/{front,right,rear,left}/image_raw` @ 30Hz,
-`/camera/panoramic/image_raw` @ 15Hz (stitched equirectangular).
 
 ---
 
-## 7. Power Budget (Orin Nano Super)
+## 7. Power Budget Concern
 
-| Scenario | Total |
+Jetson Nano 4GB maximum draw: **10W** (5V/2A barrel jack mode)
-|----------|-------|
-| SLAM active (RTAB-Map + D435i + RPLIDAR) | ~16W |
-| + 4× IMX219 | ~17W |
-| + Nav2 + TensorRT person detection | ~22W |
 
-Orin Nano Super TDP: **25W max**. Recommended PSU: 5V 5A (25W) from robot buck converter.
+| Component | Estimated Draw |
-No power gating needed. Run `sudo nvpmodel -m 0 && sudo jetson_clocks` for full performance.
+|-----------|---------------|
+| 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
 
 ---
 
-## 8. Milestones
+## 8. Milestone Checklist
 
-- [ ] Flash JetPack 6 on Orin (arriving March 1)
+- [ ] Flash JetPack 4.6 on Nano (or verify existing install)
-- [ ] `sudo apt install ros-humble-desktop ros-humble-rtabmap-ros ...`
+- [ ] Install Docker + NVIDIA Container Runtime on Nano
-- [ ] Verify D435i: `lsusb | grep "8086:0b3a"`
+- [ ] Pull `dustynv/ros:humble-ros-base-l4t-r32.7.1` container
-- [ ] Verify RPLIDAR: `ls /dev/rplidar`
+- [ ] Verify D435i recognized: `realsense-viewer` or `rs-enumerate-devices`
-- [ ] `colcon build --packages-select saltybot_bringup`
+- [ ] Verify RPLIDAR port: `ls /dev/ttyUSB*`
-- [ ] `ros2 launch saltybot_bringup sensors.launch.py` — verify topics
+- [ ] Build/pull `realsense2_camera` ROS2 package in container
-- [ ] `ros2 launch saltybot_bringup slam_rtabmap.launch.py` — verify `/rtabmap/map`
+- [ ] Build/pull `rplidar_ros` ROS2 package in container
-- [ ] `ros2 topic hz /rtabmap/cloud_map` — verify 3D cloud
+- [ ] Build/pull `rtabmap_ros` ROS2 package in container
-- [ ] Record rosbag, monitor `tegrastats` for thermal headroom
+- [ ] Test individual sensor topics with `ros2 topic echo`
-- [ ] Update static TF with real mount measurements
+- [ ] Run SLAM launch file — verify `/map` published
-- [ ] Open bead: Phase 2b Nav2
+- [ ] Record rosbag for offline tuning
-- [ ] Open bead: Phase 2c IMX219 (after hardware arrives)
+- [ ] Document measured TF offsets (physical mount positions)
+- [ ] Write Phase 2b bead for Nav2 integration
 
 ---
 
-## 9. References
+## 9. Repo Structure (to be created)
 
-- [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)
+saltylab-firmware/
-- [dusty-nv/jetson-containers JetPack 6](https://github.com/dusty-nv/jetson-containers)
+└── projects/
-- [rtabmap_ros ROS2](https://github.com/introlab/rtabmap_ros)
+    └── saltybot/
-- [realsense-ros](https://github.com/IntelRealSense/realsense-ros)
+        ├── SLAM-SETUP-PLAN.md         ← this file
-- [IMX219 / nvarguscamerasrc on Jetson](https://developer.ridgerun.com/wiki/index.php/NVIDIA_Jetson_ISP_Control)
+        ├── 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)