Lesson 3.3: Nav2 for Humanoids

Introduction to Nav2

Navigation2 (Nav2) is a powerful and flexible robotics navigation framework for ROS 2. While originally designed for wheeled robots, its modular architecture makes it adaptable for various robot types, including humanoids, with appropriate configuration and sensor integration.

Key Concepts in Nav2

• State Estimation: Using sensor data (IMUs, LiDAR, cameras) to determine the robot's current position and orientation.
• Path Planning: Generating a global path from the robot's current location to a desired goal, avoiding known obstacles.
• Local Planning: Adapting the global path in real-time to avoid dynamic obstacles and ensure smooth, collision-free movement.
• Control: Executing the planned movements by sending commands to the robot's actuators.

Adapting Nav2 for Humanoids

For humanoids, adapting Nav2 often involves:

• Footstep Planning: Instead of continuous paths, humanoids require discrete footstep plans. This involves integrating specialized planners that can generate stable gait patterns.
• Balance Control: Humanoids must maintain balance, especially during movement. This requires sophisticated control systems that can adjust joint torques and body posture.
• Complex Kinematics: Humanoid kinematics are more complex than those of wheeled robots, necessitating advanced inverse kinematics solvers.

Simple Example (Conceptual)

While a full humanoid navigation setup is complex, here's a conceptual outline of how you might think about using Nav2 components:

1. Map Creation: Use SLAM (Simultaneous Localization and Mapping) to build a map of the environment.
2. Localization: Use an AMCL (Adaptive Monte Carlo Localization) equivalent to estimate the humanoid's position on the map.
3. Global Planner: A global planner (e.g., NavFn, SmacPlanner) generates a high-level path. For humanoids, this would be a sequence of goal poses, not necessarily a detailed trajectory.
4. Footstep Planner (Custom): A custom footstep planner (not part of standard Nav2) would take the global path and generate a sequence of valid foot placements.
5. Local Planner & Controller (Custom/Adapted): A local planner and controller would then execute these footstep plans, managing balance and avoiding local obstacles.

# Conceptual Python code to illustrate interaction with Nav2's goal setting
import rclpy
from rclpy.node import Node
from geometry_msgs.msg import PoseStamped
from nav2_simple_commander.robot_navigator import BasicNavigator

def main():
    rclpy.init()
    navigator = BasicNavigator()

    # Set initial pose
    initial_pose = PoseStamped()
    initial_pose.header.frame_id = 'map'
    initial_pose.header.stamp = navigator.get_clock().now().to_msg()
    initial_pose.pose.position.x = 0.0
    initial_pose.pose.position.y = 0.0
    initial_pose.pose.orientation.w = 1.0
    navigator.setInitialPose(initial_pose)

    # Wait for Nav2 to become active
    navigator.waitUntilNav2Active()

    # Set our demo goal poses
    goal_pose = PoseStamped()
    goal_pose.header.frame_id = 'map'
    goal_pose.header.stamp = navigator.get_clock().now().to_msg()
    goal_pose.pose.position.x = 2.0
    goal_pose.pose.position.y = 0.0
    goal_pose.pose.orientation.w = 1.0

    # Go to our goal
    navigator.goToPose(goal_pose)

    while not navigator.isTaskComplete():
        # Do something during navigation if desired
        feedback = navigator.getFeedback()
        if feedback and feedback.navigation_time > 10:
            navigator.cancelTask()

    result = navigator.getResult()
    if result == BasicNavigator.CANCELED:
        print('Goal was canceled!')
    elif result == BasicNavigator.SUCCEEDED:
        print('Goal succeeded!')
    elif result == BasicNavigator.FAILED:
        print('Goal failed!')

    rclpy.shutdown()

if __name__ == '__main__':
    main()

Note: The Python example above uses nav2_simple_commander.robot_navigator which simplifies interaction with Nav2 goals. For actual humanoid navigation, the underlying plugins (global_planner, local_planner, controller) would need significant customization or replacement.

How to Run (Conceptual)

1. ROS 2 Setup: Ensure you have a ROS 2 environment and Nav2 installed.
2. Humanoid Specific Stack: You would need a separate ROS 2 package containing:
   • A URDF/SDF model of your humanoid.
   • A custom footstep planner node.
   • A custom balance controller node.
   • Appropriate transformations (tf2) for your humanoid's joints and sensors.
   • A Nav2 configuration file (params.yaml) adapted for your humanoid, potentially disabling default planners and integrating your custom ones.
3. Launch Nav2: Launch Nav2 with your custom configuration:

   ros2 launch nav2_bringup bringup_launch.py # ... with custom params ...

4. Send Goals: Use RViz2 or a Python script (like the conceptual one above) to send navigation goals.