History

sl-perception c68b751590 feat: Person-following head tracking (Issue #549 )

Add saltybot_head_tracking — ROS2 Python node for automatic person-
following using dual-axis PID control targeting the pan/tilt camera head.

Pipeline:
  1. Subscribe to /saltybot/objects (DetectedObjectArray from YOLOv8n)
  2. Filter for class_id==0 (person); select best target by score:
       score = 0.6 * 1/(1+dist_m)  +  0.4 * confidence
     (falls back to confidence-only when distance_m==0 / unknown)
  3. Compute pixel error of bbox centre from image centre
  4. Apply dead-zone (10 px default) to suppress micro-jitter
  5. Convert pixel error to angle error via camera FOV
  6. Independent PID controllers for pan and tilt axes
  7. Accumulate PID output into absolute angle setpoint
  8. Publish geometry_msgs/Point to /saltybot/gimbal/cmd:
       x = pan_angle_deg, y = tilt_angle_deg, z = confidence

State machine:
  IDLE      -> waiting for first detection
  TRACKING  -> active PID
  LOST      -> hold last angle for hold_duration_s (3 s)
  CENTERING -> return to (0, 0) at 20 deg/s -> IDLE

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

2026-03-14 10:28:17 -04:00

calibration

feat(calibration): IMX219 intrinsic + extrinsic calibration workflow (Issue #106 )

2026-03-02 08:38:24 -05:00

config

Merge remote-tracking branch 'origin/sl-jetson/issue-477-urdf'

2026-03-06 11:43:31 -05:00

docs

feat: Add Issue #502 - Headscale VPN auto-connect on Orin

2026-03-06 10:25:04 -05:00

models

feat(social): Orin dev environment — JetPack 6 + TRT conversion + systemd (#88 )

2026-03-02 08:08:57 -05:00

ros2_ws/src

feat: Person-following head tracking (Issue #549 )

2026-03-14 10:28:17 -04:00

scripts

feat: Add Issue #502 - Headscale VPN auto-connect on Orin

2026-03-06 10:25:04 -05:00

systemd

feat: Add Issue #502 - Headscale VPN auto-connect on Orin

2026-03-06 10:25:04 -05:00

docker-compose.yml

feat(social): Orin dev environment — JetPack 6 + TRT conversion + systemd (#88 )

2026-03-02 08:08:57 -05:00

Dockerfile

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

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

Dockerfile.social

feat(social): Orin dev environment — JetPack 6 + TRT conversion + systemd (#88 )

2026-03-02 08:08:57 -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.