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‎content/learning-paths/embedded-and-microcontrollers/device-connect-strands/_index.md‎

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@@ -17,10 +17,10 @@ learning_objectives:
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- Discover and invoke the robot using the Device Connect agent tools and the robot_mesh Strands tool.
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prerequisites:
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- An Arm Linux or macOS machine with Python 3.12 installed.
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- An development machine with Python 3.12 installed.
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- Git installed.
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- Basic familiarity with Python virtual environments and command-line tools.
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- (Optional) A Raspberry Pi for testing a full infrastructure setup
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- (Optional) A Raspberry Pi for testing a full device-to-device (D2D) setup.
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author:
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- Annie Tallund
@@ -47,6 +47,14 @@ further_reading:
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title: Strands Agents SDK documentation
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link: https://strandsagents.com/
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type: website
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- resource:
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title: Strands robots repository
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link: https://github.com/strands-labs/robots/tree/dev
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type: website
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- resource:
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title: Device Connect integration guide
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link: https://github.com/atsyplikhin/robots/blob/feat/device-connect-integration-draft/strands_robots/device_connect/GUIDE.md
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type: website
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### FIXED, DO NOT MODIFY
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# ================================================================================

‎content/learning-paths/embedded-and-microcontrollers/device-connect-strands/background.md‎

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@@ -14,8 +14,6 @@ Device Connect is Arm's answer to that question. It is a platform layer that han
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This Learning Path puts both tools through their paces. It starts with a single machine, for example a laptop, where a simulated robot and an agent discover each other automatically, then extends to a two-machine setup where a Raspberry Pi joins the same device mesh over the network.
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TODO: compatible devices? Mac and what else?
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## The two layers
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**Device layer**
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Two interfaces sit at this layer. The `device-connect-agent-tools` package exposes `discover_devices()` and `invoke_device()` as plain Python functions you can call directly from a script or REPL, with no LLM involved. The `robot_mesh` tool from `robots` wraps the same capabilities as a Strands agent tool, which means an LLM can also call them during a reasoning loop. Both share the same underlying Device Connect transport, so anything you can do with one you can do with the other.
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TODO: replace robots
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The diagram below shows how these layers communicate at runtime:
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```
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┌──────────────▼───────────────────────┐
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│ Device layer │
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│ Simulated SO-100 arm |
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| — so100_sim-abc123 │
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| — so100-abc123 │
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│ heartbeat · execute · getStatus │
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└──────────────────────────────────────┘
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```
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The next section covers the environment setup.
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TODO: add links to the Strands Robots docs, mesh.md, pypi?,
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TODO: replace robots and feat/device-connect-integration-draft. Update furhter reading links. Clarify device support.

‎content/learning-paths/embedded-and-microcontrollers/device-connect-strands/run-example.md‎

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@@ -55,10 +55,10 @@ When the `Robot('so100')` object is created, the SDK downloads the MuJoCo physic
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You should see INFO-level log output similar to:
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```output
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device_connect_sdk.device.so100-a3f1b2 - INFO - Using ZENOH messaging backend
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device_connect_sdk.device.so100-a3f1b2 - INFO - Connected to ZENOH broker: []
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device_connect_sdk.device.so100-a3f1b2 - INFO - Driver connected: strands_sim
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device_connect_sdk.device.so100-a3f1b2 - INFO - Subscribed to commands on device-connect.default.so100-abc123.cmd
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device_connect_sdk.device.so100-abc123 - INFO - Using ZENOH messaging backend
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device_connect_sdk.device.so100-abc123 - INFO - Connected to ZENOH broker: []
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device_connect_sdk.device.so100-abc123 - INFO - Driver connected: strands_sim
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device_connect_sdk.device.so100-abc123 - INFO - Subscribed to commands on device-connect.default.so100-abc123.cmd
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🤖 so100-abc123 is online. Ctrl+C to stop.
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```
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```output
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Discovered 1 device(s):
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[robot] so100-lab-1 — idle
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[robot] so100-abc123 — idle
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Functions: execute, getFeatures, getStatus, reset, step, stop
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```
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The peer ID (for example `so100_sim-abc123`) is assigned at startup and changes each run. Note the actual ID shown in your terminal - you will need it in the next step.
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The peer ID (for example `so100-abc123`) is assigned at startup and changes each run. Note the actual ID shown in your terminal - you will need it in the next step.
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### Execute an instruction
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Send a task to one of the discovered robots. Replace `so100_sim-abc123` with the peer ID shown in your `peers` output:
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Send a task to one of the discovered robots. Replace `so100-abc123` with the peer ID shown in your `peers` output:
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```python
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python <<'PY'
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from strands_robots.tools.robot_mesh import robot_mesh
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print(robot_mesh(
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action='tell',
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target='so100_sim-abc123',
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target='so100-abc123',
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instruction='pick up the cube',
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policy_provider='mock',
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))
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You will see the following output:
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```output
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-> so100-lab-1: pick up the cube
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-> so100-abc123: pick up the cube
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{"status": "success", "content": [...]}
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```
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```output
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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*** EVENT so100_sim-abc123::stateUpdate [111aaabb]
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*** EVENT so100-abc123::stateUpdate [111aaabb]
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payload: sim_time=4.34, step_count=2070, running_policies={'so100': {'steps': 814, 'instruction': 'pick up the cube'}}
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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```
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```output
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Found 1 robot(s):
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so100-lab-1 — idle
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so100-abc123 — idle
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Execute result: {'success': True, 'result': {'status': 'success', 'content': [...]}}
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Status: {'success': True, 'result': {...}} # full sim state dict
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```

‎content/learning-paths/embedded-and-microcontrollers/device-connect-strands/run-infra-example.md‎

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```output
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INFO:strands_robots.mesh:Zenoh session started
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INFO:strands_robots.mesh:Peer ID: so100_sim-abc123
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device_connect_sdk.device.so100_sim-abc123 - INFO - Using ZENOH messaging backend
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device_connect_sdk.device.so100_sim-abc123 - INFO - Connected to ZENOH broker: ['tcp/192.168.1.42:7447']
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device_connect_sdk.device.so100_sim-abc123 - INFO - Device registered: registration_id=ecfff6a7-...
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INFO:strands_robots.mesh:Peer ID: so100-abc123
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device_connect_sdk.device.so100-abc123 - INFO - Using ZENOH messaging backend
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device_connect_sdk.device.so100-abc123 - INFO - Connected to ZENOH broker: ['tcp/192.168.1.42:7447']
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device_connect_sdk.device.so100-abc123 - INFO - Device registered: registration_id=ecfff6a7-...
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```
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Note the peer ID (for example `so100_sim-abc123`). You will need it in the `tell` command below. Leave this process running on the Pi.
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Note the peer ID (for example `so100-abc123`). You will need it in the `tell` command below. Leave this process running on the Pi.
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## Discover and invoke using the robot_mesh Strands tool
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```output
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Discovered 1 device(s):
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[robot] so100_sim-abc123 — idle
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[robot] so100-abc123 — idle
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Functions: execute, getFeatures, getState, getStatus, stop
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```
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Send an instruction to the robot. Replace `so100_sim-abc123` with the peer ID shown in your output:
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Send an instruction to the robot. Replace `so100-abc123` with the peer ID shown in your output:
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```python
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python <<'PY'
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from strands_robots.tools.robot_mesh import robot_mesh
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print(robot_mesh(
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action='tell',
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target='so100_sim-abc123',
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target='so100-abc123',
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policy_provider='mock',
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The output is similar to:
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```output
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-> so100_sim-abc123: pick up the cube
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-> so100-abc123: pick up the cube
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{"status": "accepted"}
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```
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‎content/learning-paths/embedded-and-microcontrollers/device-connect-strands/setup.md‎

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The Device Connect integration code for `robots` lives on the `feat/device-connect-integration-draft` branch. This branch adds the `RobotDeviceDriver` adapter and the updated `robot_mesh` tool that routes calls through the Device Connect SDK rather than the raw Zenoh mesh.
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TODO: remove feature branch? replace robots and feat/device-connect-integration-draft
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```bash
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cd ~/strands-device-connect/robots
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git checkout feat/device-connect-integration-draft

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