jetson/Dockerfile

@@ -1,12 +1,15 @@
-# Jetson Nano — ROS2 Humble dev container
+# Jetson Orin Nano Super — ROS2 Humble dev container
-# Base: JetPack 4.6 (L4T R32.6.1) + CUDA 10.2
+# Base: JetPack 6 (L4T R36.2.0) + CUDA 12.x / Ubuntu 22.04
-# 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-base:r32.6.1
+FROM nvcr.io/nvidia/l4t-jetpack:r36.2.0
 
-LABEL maintainer="sl-jetson <saltylab>"
+LABEL maintainer="sl-perception <saltylab>"
-LABEL description="ROS2 Humble + SLAM stack for Jetson Nano self-balancing robot"
+LABEL description="ROS2 Humble + SLAM stack for Jetson Orin Nano Super self-balancing robot"
-LABEL jetpack="4.6"
+LABEL jetpack="6.0"
+LABEL l4t="r36.2.0"
 LABEL ros_distro="humble"
 
 ENV DEBIAN_FRONTEND=noninteractive
@@ -15,32 +18,29 @@ ENV ROS_ROOT=/opt/ros/${ROS_DISTRO}
 ENV PYTHONDONTWRITEBYTECODE=1
 ENV PYTHONUNBUFFERED=1
 
-# ── System deps ────────────────────────────────────────────────────────────────
+# ── Locale ─────────────────────────────────────────────────────────────────────
+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 \
-    # Misc
+    htop tmux nano \
-    locales tzdata htop tmux nano \
-    # Networking
     net-tools iputils-ping \
     && rm -rf /var/lib/apt/lists/*
 
-RUN locale-gen en_US.UTF-8
+# ── ROS2 Humble (Ubuntu 22.04 native — standard apt, no ARM64 workarounds) ─────
-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 \
-        | apt-key add - && \
+        | gpg --dearmor -o /usr/share/keyrings/ros-archive-keyring.gpg && \
-    echo "deb [arch=arm64] http://packages.ros.org/ros2/ubuntu focal main" \
+    echo "deb [arch=arm64 signed-by=/usr/share/keyrings/ros-archive-keyring.gpg] \
+        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 \
@@ -51,50 +51,45 @@ RUN curl -sSL https://raw.githubusercontent.com/ros/rosdistro/master/ros.asc \
     && rosdep init && rosdep update \
     && rm -rf /var/lib/apt/lists/*
 
-# ── Nav / SLAM / sensor packages ──────────────────────────────────────────────
+# ── SLAM / Nav / Sensor packages ───────────────────────────────────────────────
 RUN apt-get update && apt-get install -y --no-install-recommends \
-    ros-humble-nav2-bringup \
+    ros-humble-rtabmap-ros \
     ros-humble-slam-toolbox \
+    ros-humble-nav2-bringup \
     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 \
+    Jetson.GPIO pyserial smbus2 numpy scipy
-    pyserial \
-    smbus2 \
-    adafruit-blinka \
-    RPi.GPIO \
-    numpy \
-    scipy
 
-# ── RealSense SDK (librealsense2 ARM64) ───────────────────────────────────────
+# ── RealSense SDK (librealsense2 ARM64 for JetPack 6) ─────────────────────────
-# 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

@@ -1,53 +1,33 @@
-# RealSense D435i configuration — Jetson Nano (power-budget tuned)
+# RealSense D435i configuration — Jetson Orin Nano Super
 #
-# Profile format: WxHxFPS
+# Previous Nano 4GB settings (640x480x15, no point cloud) replaced.
-# Constraint: ~10W total budget. 640x480x15 saves ~0.4W vs 30fps.
+# Orin Nano Super has ample Ampere GPU headroom for 848x480x30fps + point cloud.
 #
-# Reference topics at these settings:
+# Reference topics:
-#   /camera/color/image_raw               640x480  15 Hz   RGB8
+#   /camera/color/image_raw               848x480  30 Hz   RGB8
-#   /camera/depth/image_rect_raw          640x480  15 Hz   Z16
+#   /camera/depth/image_rect_raw          848x480  30 Hz   Z16
-#   /camera/aligned_depth_to_color/image_raw  640x480  15 Hz  Z16
+#   /camera/aligned_depth_to_color/image_raw  848x480  30 Hz  Z16
-#   /camera/imu                           6-axis   ~200 Hz  (accel@100Hz + gyro@400Hz fused)
+#   /camera/color/camera_info             848x480  30 Hz
-#   /camera/color/camera_info             640x480  15 Hz
+#   /camera/depth/camera_info             848x480  30 Hz
-#   /camera/depth/camera_info             640x480  15 Hz
+#   /camera/imu                           ~400 Hz  (gyro@400Hz + accel@100Hz fused)
-#
+#   /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:
-    # ── Streams ──────────────────────────────────────────────────────────────
+    depth_module.profile: "848x480x30"
-    depth_module.profile: "640x480x15"
+    rgb_camera.profile:   "848x480x30"
-    rgb_camera.profile:   "640x480x15"
 
     enable_depth:   true
     enable_color:   true
-    enable_infra1:  false    # not needed for RGB-D SLAM
+    enable_infra1:  false
     enable_infra2:  false
 
-    # ── IMU ──────────────────────────────────────────────────────────────────
     enable_gyro:          true
     enable_accel:         true
-    # 0=none  1=copy  2=linear_interpolation
+    unite_imu_method:     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    # 0 = publish static transforms only (no redundant timer)
+    tf_publish_rate:  0.0
-
-    # ── Device ───────────────────────────────────────────────────────────────
-    # Leave serial_no empty to auto-select first found device
-    # serial_no: ''
-    # device_type: d435i

jetson/config/rtabmap_params.yaml

@@ -0,0 +1,78 @@
+# 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

@@ -1,44 +1,37 @@
 # slam_toolbox — online async SLAM configuration
-# Tuned for Jetson Nano 4GB (constrained CPU/RAM, indoor mapping)
+# Jetson Orin Nano Super — all Nano rate caps removed.
+#
+# 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, updated every map_update_interval seconds)
+# Output: /map   (OccupancyGrid)
-#
-# 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    # 'mapping' or 'localization'
+    mode:         mapping
 
-    # ── Map params ───────────────────────────────────────────────────────────
+    resolution:               0.05
-    resolution:            0.05    # 5 cm/cell — good balance for A1M8 angular res
+    max_laser_range:          8.0
-    max_laser_range:       8.0     # clip to reliable range of A1M8 (spec: 12m)
+    map_update_interval:      1.0     # 1s (was 5s on Nano)
-    map_update_interval:   5.0     # seconds between full map publishes (saves CPU)
+    minimum_travel_distance:  0.2
-    minimum_travel_distance:  0.3  # only update after moving 30 cm
+    minimum_travel_heading:   0.2
-    minimum_travel_heading:   0.3  # or rotating ~17°
 
-    # ── Performance (Nano-specific) ───────────────────────────────────────────
+    minimum_time_interval:  0.1    # ~10Hz processing (was 0.5s on Nano)
-    # 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   # 40 MB stack
+    stack_size_to_use:      40000000
-    enable_interactive_mode: false     # disable interactive editing (saves CPU)
+    enable_interactive_mode: false
 
-    # ── Scan matching ─────────────────────────────────────────────────────────
     use_scan_matching:    true
     use_scan_barycenter:  true
-    scan_buffer_size:     10
+    scan_buffer_size:     20
     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
@@ -46,31 +39,25 @@ 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    # ~0.2°
+    fine_search_angle_offset:         0.00349
-    coarse_search_angle_offset: 0.349     # ~20°
+    coarse_search_angle_offset:       0.349
-    coarse_angle_resolution:   0.0349     # ~2°
+    coarse_angle_resolution:          0.0349
     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-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 ────────────────────────────────────────────────────

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

@@ -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
+    ])

projects/saltybot/SLAM-SETUP-PLAN.md

@@ -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
+**Bead:** bd-wax (plan), bd-a2j (sensor drivers done PR #17)
-**Phase:** 2 (lower priority than Phase 1 balance)
+**Phase:** 2 | **Owner:** sl-perception
-**Owner:** sl-perception
+**Updated:** 2026-03-01 — revised for Jetson Orin Nano Super (replaces Nano 4GB)
-**Hardware:** Jetson Nano 4GB + Intel RealSense D435i + RPLIDAR A1M8
+
-**Goal:** Indoor SLAM, mapping, and autonomous navigation (person-following)
+> 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 |
+| AI Brain | **Jetson Orin Nano Super 8GB** — 6-core A78AE, 1024-core Ampere, **67 TOPS**, JetPack 6 |
-| RealSense D435i | Stereo depth (0.1–10m), 848×480 @ 90fps, BMI055 IMU (accel+gyro) |
+| Depth Cam | Intel RealSense D435i — 848×480 @ 90fps, BMI055 IMU |
-| RPLIDAR A1M8 | 360° 2D LIDAR, 12m range, 8000 samples/s, ~5.5Hz scan rate |
+| 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)
+Docker still supported for CI. Updated `Dockerfile` uses `nvcr.io/nvidia/l4t-jetpack:r36.2.0`.
-- 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 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 |
+Fusion: RPLIDAR `/scan` (fast 2D loop closure) + D435i depth (3D reconstruction + visual odometry).
-|-----------|-----------|----------|
-| 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 |
 
-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.
+### Secondary: slam_toolbox (LIDAR-only localization / pre-built map mode)
-
-**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. Software Architecture
+## 3. 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°
-│  │ realsense2_   │    │     rplidar_ros2          │  │
+  /camera/color              │
-│  │ camera node   │    │  /scan (LaserScan)        │  │
+  /camera/depth              │
-│  │               │    │  5.5Hz, 360°, 12m range   │  │
+  /camera/imu ~400Hz         │
-│  │ /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  │                        │
-│         └──────────────────┘                        │
-└─────────────────────────────────────────────────────┘
         │                    │
-    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 |
+## 4. Phases
-|------|---------|------------|
+
-| `camera/realsense2_camera_node` | `realsense2_camera` | `/camera/depth/image_rect_raw`, `/camera/color/image_raw`, `/camera/imu` |
+| Phase | Status | Description |
-| `rplidar_node` | `rplidar_ros` | `/scan` |
+|-------|--------|-------------|
-| `rtabmap` | `rtabmap_ros` | `/map`, `/rtabmap/odom`, `/rtabmap/cloud_map` |
+| 2a | ✅ Done (PR #17) | Sensor drivers — `saltybot_bringup` package |
-| `robot_state_publisher` | `robot_state_publisher` | `/tf` (static transforms) |
+| 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)
+Full config: `jetson/config/rtabmap_params.yaml`
-
-**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_ros params — power/performance tradeoffs for Nano
+Rtabmap/DetectionRate: "10"     # was 2 on Nano
-rtabmap:
+Kp/MaxFeatures:        "1000"   # was 400
-  Rtabmap/DetectionRate: "2"          # Process keyframes at 2Hz (not every frame)
+RGBD/LinearUpdate:     "0.05"   # 5cm  (was 10cm)
-  Rtabmap/TimeThr: "700"              # Max processing time 700ms per iteration
+RGBD/AngularUpdate:    "0.05"   # ~3°  (was 5°)
-  Kp/MaxFeatures: "400"               # Reduce keypoints from default 1000
+Grid/3D:               "true"   # 3D cloud enabled  (was false)
-  Vis/MaxFeatures: "400"
+Rtabmap/TimeThr:       "0"      # no limit  (was 700ms)
-  RGBD/LinearUpdate: "0.1"            # Only update map if moved 10cm
+Mem/STMSize:           "0"      # unlimited  (was 30)
-  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. Static TF / URDF Robot Frame
+## 6. 4× IMX219 Layout (Phase 2c)
-
-Robot coordinate frame (`base_link`) transforms needed:
 
 ```
-base_link
+      FRONT (CSI0) 160°
-├── laser_frame      (RPLIDAR A1M8 — top center of robot)
+LEFT  (CSI3) ×  RIGHT (CSI1)
-├── camera_link      (RealSense D435i — front, ~camera_height above base)
+      REAR  (CSI2) 160°
-│   ├── camera_depth_frame
-│   └── camera_imu_frame
-└── imu_link         (STM32 IMU — FC board location)
 ```
 
-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 |
+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.
-| 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. Milestone Checklist
+## 8. Milestones
 
-- [ ] Flash JetPack 4.6 on Nano (or verify existing install)
+- [ ] Flash JetPack 6 on Orin (arriving March 1)
-- [ ] Install Docker + NVIDIA Container Runtime on Nano
+- [ ] `sudo apt install ros-humble-desktop ros-humble-rtabmap-ros ...`
-- [ ] Pull `dustynv/ros:humble-ros-base-l4t-r32.7.1` container
+- [ ] Verify D435i: `lsusb | grep "8086:0b3a"`
-- [ ] Verify D435i recognized: `realsense-viewer` or `rs-enumerate-devices`
+- [ ] Verify RPLIDAR: `ls /dev/rplidar`
-- [ ] Verify RPLIDAR port: `ls /dev/ttyUSB*`
+- [ ] `colcon build --packages-select saltybot_bringup`
-- [ ] Build/pull `realsense2_camera` ROS2 package in container
+- [ ] `ros2 launch saltybot_bringup sensors.launch.py` — verify topics
-- [ ] Build/pull `rplidar_ros` ROS2 package in container
+- [ ] `ros2 launch saltybot_bringup slam_rtabmap.launch.py` — verify `/rtabmap/map`
-- [ ] Build/pull `rtabmap_ros` ROS2 package in container
+- [ ] `ros2 topic hz /rtabmap/cloud_map` — verify 3D cloud
-- [ ] Test individual sensor topics with `ros2 topic echo`
+- [ ] Record rosbag, monitor `tegrastats` for thermal headroom
-- [ ] Run SLAM launch file — verify `/map` published
+- [ ] Update static TF with real mount measurements
-- [ ] Record rosbag for offline tuning
+- [ ] Open bead: Phase 2b Nav2
-- [ ] Document measured TF offsets (physical mount positions)
+- [ ] Open bead: Phase 2c IMX219 (after hardware arrives)
-- [ ] Write Phase 2b bead for Nav2 integration
 
 ---
 
-## 9. Repo Structure (to be created)
+## 9. References
 
-```
+- [Jetson Orin Nano Super](https://www.nvidia.com/en-us/autonomous-machines/embedded-systems/jetson-orin/)
-saltylab-firmware/
+- [JetPack 6 / L4T R36](https://developer.nvidia.com/embedded/jetpack)
-└── projects/
+- [dusty-nv/jetson-containers JetPack 6](https://github.com/dusty-nv/jetson-containers)
-    └── saltybot/
+- [rtabmap_ros ROS2](https://github.com/introlab/rtabmap_ros)
-        ├── SLAM-SETUP-PLAN.md         ← this file
+- [realsense-ros](https://github.com/IntelRealSense/realsense-ros)
-        ├── SALTYLAB.md                ← main design doc (TBD)
+- [IMX219 / nvarguscamerasrc on Jetson](https://developer.ridgerun.com/wiki/index.php/NVIDIA_Jetson_ISP_Control)
-        └── 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)