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saltylab-firmware/projects/saltybot/SLAM-SETUP-PLAN.md
sl-uwb bb35ddd56d chore: resolve git conflict markers and complete legacy STM32/Mamba → ESP32-S3 rename 
- Resolve 73 committed conflict markers (bulk resolution taking theirs/ESP32 side)
- Rename all MAMBA_CMD_* → BALANCE_CMD_*, MAMBA_TELEM_* → BALANCE_TELEM_*
- Rename FC_STATUS/VESC/IMU/BARO → BALANCE_STATUS/VESC/IMU/BARO in protocol_defs.py
- Update can_bridge_node.py: fix imports, replace legacy encode/decode calls with
  balance_protocol equivalents (encode_velocity_cmd, encode_mode_cmd, decode_imu_telem,
  decode_battery_telem, decode_vesc_state); fix watchdog and destroy_node
- Rename stm32_protocol.py/stm32_cmd_node.py → esp32_protocol.py/esp32_cmd_node.py
- Delete mamba_protocol.py; stm32_cmd.launch.py/stm32_cmd_params.yaml archived
- Update can_bridge_params.yaml: mamba_can_id → balance_can_id
- Update docs/AGENTS.md, SALTYLAB.md, wiring-diagram.md for ESP32-S3 architecture
- Update test/test_ota.py sys.path to legacy/stm32/scripts/flash_firmware.py
- No legacy STM32/Mamba refs remain outside legacy/ and SAUL-TEE-SYSTEM-REFERENCE.md

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-04-04 09:11:24 -04:00

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SLAM Setup Plan — Jetson Orin Nano Super

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

Component Specs
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 ESP32-S3 — UART bridge /dev/ttyACM0 @ 921600

1. OS & ROS2

JetPack 6 = Ubuntu 22.04 → ROS2 Humble via native apt (no Docker workarounds needed).

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.

2. SLAM Stack

Primary: RTAB-Map (RGB-D + 2D LIDAR fusion)

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

Fusion: RPLIDAR /scan (fast 2D loop closure) + D435i depth (3D reconstruction + visual odometry).

Secondary: slam_toolbox (LIDAR-only localization / pre-built map mode)

3. Architecture

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         │
        │                    │
        └──────────┬─────────┘
                   ▼
            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 → ESP32-S3
  4× IMX219 CSI               (Phase 2c — pending hardware)
  front/right/rear/left 160°
  → panoramic stitch, person tracking

4. Phases

Phase Status Description
2a ✅ Done (PR #17) Sensor drivers — saltybot_bringup package
2a+ ✅ Done (PR #36) Orin update: Dockerfile JetPack 6, RTAB-Map launch + config
2b ✅ Done (PR #49) Nav2 integration — path planning + obstacle avoidance
2c ✅ Done (PR #52) 4× IMX219 surround vision + Nav2 camera obstacle layer
2d ✅ Done (this PR) Outdoor navigation — OSM routing + GPS waypoints + geofence

5. RTAB-Map Config (Orin)

Full config: jetson/config/rtabmap_params.yaml

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. 4× IMX219 Layout (Phase 2c)

      FRONT (CSI0) 160°
LEFT  (CSI3) ×  RIGHT (CSI1)
      REAR  (CSI2) 160°

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 (Orin Nano Super)

Scenario Total
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. No power gating needed. Run sudo nvpmodel -m 0 && sudo jetson_clocks for full performance.

8. Milestones

  • 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. References