name	yahboom-robots-expert
description	Use this skill when you need domain expertise on Yahboom Raspbot v2 hardware, ROS 2 setup, mecanum kinematics, or integration architecture.

Yahboom Robots Expert Skill

Use this skill when you need domain expertise on Yahboom Raspbot v2 hardware, ROS 2 setup, mecanum kinematics, or integration architecture—beyond routine operator procedures (see yahboom-operator for day-to-day tool use).

🛠️ Hardware Specifications

Platform: Yahboom Raspbot v2. Main compute: Raspberry Pi 5 (ARM64). OS: Ubuntu 24.04 + ROS 2 Humble.
Drive: Four mecanum wheels (32.5 mm radius). Layout: front_left, front_right, back_left, back_right; axles parallel to robot X (forward). Enables holonomic motion: forward/back, strafe left/right, rotate in place.
Sensors: 2D LIDAR (laser_link), camera (camera_link); IMU and wheel encoders for odometry.
Power: Onboard battery; monitor via read_battery / telemetry. Low battery (< 20%) limits recommended motion duration.

📐 Frames and URDF

base_footprint: Ground plane (z = 0).
base_link: Body frame; z offset = +wheel_radius (0.0325 m) above ground. Wheel joints at z = -wheel_radius relative to base_link.
Wheel positions (joint xyz): x = ±0.08, y = ±0.0745 (half track), z = -0.0325.
LIDAR: Offset (0, 0, 0.0825) from base_link.
Camera: Offset (0.105, 0, 0.05).

🤖 ROS 2 Architecture

ROS 2: Humble on Ubuntu 24.04. Topics/services follow ROS 2 naming (e.g. cmd_vel, odom, scan, image).
MCP ↔ Robot: yahboom-mcp server talks to a REST bridge (or direct ROS 2 node) on the robot network. Robot IP and bridge port configurable (env or settings).
Dual mode: Server can run --mode stdio (MCP only) or --mode dual --port 10892 (REST API + MCP). Dashboard (Vite) uses REST on 10892; frontend dev server on 10893.

⚙️ Kinematics and Motion

Mecanum rollers: rollers at 45°; combined wheel velocities yield body linear and angular velocity.
Odometry: from encoders + IMU; heading from IMU.
Trajectory recording: start_recording → run motions → stop_recording(basename).

🌐 Integration and Fleet

Federated fleet: Yahboom-MCP is one node; others include Dreame-MCP (mapping/sweeping), Virtual-Robotics-MCP (simulation), central hub (orchestration).
3D viz: Dashboard loads real STL meshes from URDF (base_link, wheels, LIDAR, camera).

⚖️ Skill Application Matrix

Use yahboom-robots-expert when	Use yahboom-operator when
Explaining hardware, frames, or kinematics	Running tools and following workflows
Debugging connection, URDF, or frame issues	Choosing which tool/prompt to call
Designing integrations or fleet behaviour	Doing health_check → motion → recording
Answering “how does the robot work?”	Answering “how do I make it patrol?”

🔗 Quick References

Tools: yahboom, yahboom_help, yahboom_agentic_workflow.
Prompts: yahboom_quick_start(robot_ip), yahboom_patrol(duration_seconds), yahboom_diagnostics().
Scripts: scripts/check_health.py (REST health/telemetry), scripts/run_patrol_square.ps1 (run server + dashboard hint).
Docs: docs/CONNECTIVITY.md, docs/architecture.md, docs/fleet_overview.md.

Yahboom Robots Expert Skill

🛠️ Hardware Specifications

Platform: Yahboom Raspbot v2. Main compute: Raspberry Pi 5 (ARM64). OS: Ubuntu 24.04 + ROS 2 Humble.

Drive: Four mecanum wheels (32.5 mm radius). Layout: front_left, front_right, back_left, back_right; axles parallel to robot X (forward). Enables holonomic motion: forward/back, strafe left/right, rotate in place.

Sensors: 2D LIDAR (laser_link), camera (camera_link); IMU and wheel encoders for odometry.

Power: Onboard battery; monitor via read_battery / telemetry. Low battery (< 20%) limits recommended motion duration.

📐 Frames and URDF

base_footprint: Ground plane (z = 0).

base_link: Body frame; z offset = +wheel_radius (0.0325 m) above ground. Wheel joints at z = -wheel_radius relative to base_link.

Wheel positions (joint xyz): x = ±0.08, y = ±0.0745 (half track), z = -0.0325.

LIDAR: Offset (0, 0, 0.0825) from base_link.

Camera: Offset (0.105, 0, 0.05).

🤖 ROS 2 Architecture

ROS 2: Humble on Ubuntu 24.04. Topics/services follow ROS 2 naming (e.g. cmd_vel, odom, scan, image).

MCP ↔ Robot: yahboom-mcp server talks to a REST bridge (or direct ROS 2 node) on the robot network. Robot IP and bridge port configurable (env or settings).

Dual mode: Server can run --mode stdio (MCP only) or --mode dual --port 10892 (REST API + MCP). Dashboard (Vite) uses REST on 10892; frontend dev server on 10893.

⚙️ Kinematics and Motion

Mecanum rollers: rollers at 45°; combined wheel velocities yield body linear and angular velocity.

Odometry: from encoders + IMU; heading from IMU.

Trajectory recording: start_recording → run motions → stop_recording(basename).

🌐 Integration and Fleet

Federated fleet: Yahboom-MCP is one node; others include Dreame-MCP (mapping/sweeping), Virtual-Robotics-MCP (simulation), central hub (orchestration).

3D viz: Dashboard loads real STL meshes from URDF (base_link, wheels, LIDAR, camera).

⚖️ Skill Application Matrix

Use yahboom-robots-expert when

Use yahboom-operator when

Explaining hardware, frames, or kinematics

Running tools and following workflows

Debugging connection, URDF, or frame issues

Choosing which tool/prompt to call

Designing integrations or fleet behaviour

Doing health_check → motion → recording

Answering “how does the robot work?”

Answering “how do I make it patrol?”

🔗 Quick References

Tools: yahboom, yahboom_help, yahboom_agentic_workflow.

Prompts: yahboom_quick_start(robot_ip), yahboom_patrol(duration_seconds), yahboom_diagnostics().

Scripts: scripts/check_health.py (REST health/telemetry), scripts/run_patrol_square.ps1 (run server + dashboard hint).

Docs: docs/CONNECTIVITY.md, docs/architecture.md, docs/fleet_overview.md.

yahboom-robots-expert