History

sl-controls fa0162fadc feat(social): multi-modal tracking fusion — UWB+camera Kalman filter (Issue #92 )

New packages:
  saltybot_social_msgs   — FusedTarget.msg custom message
  saltybot_social_tracking — 4-state Kalman fusion node

saltybot_social_tracking/tracking_fusion_node.py
  Subscribes to /uwb/target (PoseStamped, ~10 Hz) and /person/target
  (PoseStamped, ~30 Hz) and publishes /social/tracking/fused_target
  (FusedTarget) at 20 Hz.

  Source arbitration:
    • "fused"     — both UWB and camera are fresh; confidence-weighted blend
    • "uwb"       — UWB fresh, camera stale
    • "camera"    — camera fresh, UWB stale
    • "predicted" — all sources stale; KF coasts for up to predict_timeout (3 s)

  Kalman filter (kalman_tracker.py):
    State [x, y, vx, vy] with discrete Wiener acceleration noise model
    (process_noise=3.0 m/s²) sized for EUC speeds (20-30 km/h, ≈5.5-8.3 m/s).
    Separate UWB (0.20 m) and camera (0.12 m) measurement noise.
    Velocity estimate converges after ~3 s of 10 Hz UWB measurements.

  Confidence model (source_arbiter.py):
    Per-source confidence = quality × max(0, 1 - age/timeout).
    Composite confidence accounts for KF positional uncertainty and
    is capped at 0.4 during dead-reckoning ("predicted") mode.

Tests: 58/58 pass (no ROS2 runtime required).

Note: saltybot_social_msgs here adds FusedTarget.msg; PR #98
(Issue #84) adds PersonalityState.msg + QueryMood.srv to the same
package. The maintainer should squash-merge #98 first and rebase
this branch on top of it before merging to avoid the package.xml
conflict.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

2026-03-01 23:59:10 -05:00

config

feat: 4x IMX219 surround vision + Nav2 camera obstacle layer (Phase 2c)

2026-02-28 23:19:23 -05:00

docs

feat: Orin Nano Super platform update + 4x IMX219 CSI cameras

2026-02-28 22:59:13 -05:00

ros2_ws/src

feat(social): multi-modal tracking fusion — UWB+camera Kalman filter (Issue #92 )

2026-03-01 23:59:10 -05:00

scripts

feat: Orin Nano Super platform update + 4x IMX219 CSI cameras

2026-02-28 22:59:13 -05:00

docker-compose.yml

feat(safety): remote e-stop over 4G MQTT (Issue #63 )

2026-03-01 04:55:54 -05:00

Dockerfile

feat: update SLAM stack for Jetson Orin Nano Super (67 TOPS, JetPack 6)

2026-02-28 21:46:27 -05:00

README.md

feat: Jetson Nano platform setup and Docker env (bd-1hcg)

2026-02-28 12:46:14 -05:00

README.md

Jetson Nano — AI/SLAM Platform Setup

Self-balancing robot: Jetson Nano dev environment for ROS2 Humble + SLAM stack.

Stack

Component	Version / Part
Platform	Jetson Nano 4GB
JetPack	4.6 (L4T R32.6.1, CUDA 10.2)
ROS2	Humble Hawksbill
DDS	CycloneDDS
SLAM	slam_toolbox
Nav	Nav2
Depth camera	Intel RealSense D435i
LiDAR	RPLIDAR A1M8
MCU bridge	STM32F722 (USB CDC @ 921600)

Quick Start

# 1. Host setup (once, on fresh JetPack 4.6)
sudo bash scripts/setup-jetson.sh

# 2. Build Docker image
bash scripts/build-and-run.sh build

# 3. Start full stack
bash scripts/build-and-run.sh up

# 4. Open ROS2 shell
bash scripts/build-and-run.sh shell

Docs

docs/pinout.md — GPIO/I2C/UART pinout for all peripherals
docs/power-budget.md — 10W power envelope analysis

Files

jetson/
├── Dockerfile              # L4T base + ROS2 Humble + SLAM packages
├── docker-compose.yml      # Multi-service stack (ROS2, RPLIDAR, D435i, STM32)
├── README.md               # This file
├── docs/
│   ├── pinout.md           # GPIO/I2C/UART pinout reference
│   └── power-budget.md     # Power budget analysis (10W envelope)
└── scripts/
    ├── entrypoint.sh       # Docker container entrypoint
    ├── setup-jetson.sh     # Host setup (udev, Docker, nvpmodel)
    └── build-and-run.sh    # Build/run helper

Power Budget (Summary)

Scenario	Total
Idle	2.9W
Nominal (SLAM active)	~10.2W
Peak	15.4W

Target: 10W (MAXN nvpmodel). Use RPLIDAR standby + 640p D435i for compliance. See docs/power-budget.md for full analysis.