sl-perception c620dc51a7 feat: Add Issue #363 — P0 person tracking for follow-me mode
Implements real-time person detection + tracking pipeline for the
follow-me motion controller on Jetson Orin Nano Super (D435i).

Core components
- TargetTrack.msg: bearing_deg, distance_m, confidence, bbox, vel_bearing_dps,
  vel_dist_mps, depth_quality (0-3)
- _person_tracker.py (pure-Python, no ROS2/runtime deps):
  · 8-state constant-velocity Kalman filter [cx,cy,w,h,vcx,vcy,vw,vh]
  · Greedy IoU data association
  · HSV torso colour histogram re-ID (16H×8S, Bhattacharyya similarity)
    with fixed saturation clamping (s = (cmax−cmin)/cmax, clipped to [0,1])
  · FollowTargetSelector: nearest person auto-lock, hold_frames hysteresis
  · TENTATIVE→ACTIVE after min_hits; LOST track removal after max_lost_frames
    with per-frame lost_age increment across all LOST tracks
  · bearing_from_pixel, depth_at_bbox (median, quality flags)
- person_tracking_node.py:
  · YOLOv8n via ultralytics (TRT FP16 on first run) → HOG+SVM fallback
  · Subscribes colour + depth + camera_info + follow_start/stop
  · Publishes /saltybot/target_track at ≤30 fps
- test/test_person_tracker.py: 59/59 tests passing

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-03-03 15:19:02 -05:00
..

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

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.