OpenClaw Navigation Transfer

1. Course Content

Learning Objectives

• This section is a comprehensive course that combines robotic arm visual grasping and intelligent navigation functions for complex long-flow tasks. Please complete the basic courses [02-OpenClaw Robotic Arm Tracking Grasp], [05-OpenClaw Slam Mapping and Navigation], and [Road Network Planning Navigation] first.

2. Preparation

• Complete grid map construction, pose map construction, and road network file annotation. For details, refer to the tutorial [Road Network Planning Navigation - Building Pose Maps and Road Network Annotation]
• Complete the prerequisite tutorials, mastering map construction, road network annotation, and map mapping marking functions in advance.
• Start the MicroROS chassis agent (no need to restart if already started)

sh start_agent.sh

• Start odometry, tf, robotic arm assistance, camera nodes, etc. If you need to enable visual relocalization, add the startup parameter relocation:=True
• Start with relocalization (start from host)

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ros2 launch m3pro_bringup car_base.launch.py relocation:=True

• Start road network navigation (start inside roadnet container)

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ros2 launch road_net_route roadnet_nav2.launch.py rviz_config_file:=/root/volumes/code_ws/src/road_net_route/rviz/nav2_relocaton.rviz

• Start the MCP service

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ros2 launch m3pro_bringup mcp_service.launch.py

• If you need voice reply, you need to start openclaw_bridge additionally, otherwise it can be omitted

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ros2 run multi_brains_pre openclaw_bridge

3. Demonstration Case

[!TIP]

• You can freely edit commands based on actual conditions. The following is a reference case.

• Transport a purple block from the raw material warehouse to the blue shelf area of the processing center

• Use the robot_control CLI to pre-mark the map mapping for "raw material warehouse" and "processing center"

• Then assign a specific task to OpenClaw, choose any interaction method
• Transport a purple cube from the raw material warehouse to the blue shelf area of the processing center.

• OpenClaw will call tools to first grasp the color block and then navigate to the location for placement

4. Parameter Tuning and Source Code Analysis

• This section is a comprehensive course. Debugging parameters and functional source code are detailed in [02-OpenClaw Robotic Arm Tracking Grasp] and [05-OpenClaw Slam Mapping and Navigation].