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Building Whole-Body Control for Humanoid Robots

Building Whole-Body Control for Humanoid Robots

Humanoid robots have many joints that must coordinate simultaneously. Moving one joint can affect balance, contact forces, and the configuration of the entire body.

Whole-body control (WBC) addresses this problem by coordinating multiple objectives under the robot's kinematic and dynamic constraints.

The Humanoid Control Problem

A humanoid may need to control:

Head
Arms
Torso
Hips
Knees
Ankles
Hands
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while simultaneously maintaining:

  • Balance
  • Foot contacts
  • Joint limits
  • Collision avoidance
  • End-effector goals

1. Think in Tasks

Instead of commanding every joint independently, define tasks:

Task 1: Keep center of mass stable
Task 2: Maintain left foot contact
Task 3: Maintain right foot contact
Task 4: Move right hand
Task 5: Keep torso orientation
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The whole-body controller finds joint commands that satisfy these objectives as well as possible.

2. Kinematic Model

Let:

q = joint positions
q̇ = joint velocities
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An end-effector velocity can be approximated as:

ẋ = J(q) q̇
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where J(q) is the Jacobian.

A controller can use this relationship to convert Cartesian task goals into joint-space motion.

3. Hierarchical Control

Some tasks are more important than others.

For example:

Priority 1
Balance / Safety

Priority 2
Foot Contacts

Priority 3
Manipulation

Priority 4
Posture
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A lower-priority task should not violate a higher-priority constraint.

4. Optimization-Based Whole-Body Control

A simplified optimization objective can be written as:

minimize:

||J q̇ - ẋ_des||²
+
λ ||q̇||²
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subject to:

joint limits
velocity limits
contact constraints
collision constraints
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Real humanoid controllers may use more sophisticated task, force, and dynamics formulations.

5. Center of Mass Control

Balance is fundamental.

The controller monitors:

Center of Mass
      ↓
Support Polygon
      ↓
Balance Error
      ↓
Corrective Motion
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If the robot shifts its upper body, it may need to move its feet or adjust its joints to maintain stability.

6. Contact Constraints

When a foot is planted:

Foot position ≈ constant
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The controller must ensure that commanded motion does not unintentionally move the contact point.

This creates constraints that couple multiple joints.

7. Integrate with ROS 2

A humanoid architecture might be:

Perception
    ↓
State Estimation
    ↓
Task Planner
    ↓
Whole-Body Controller
    ↓
Joint Commands
    ↓
ros2_control
    ↓
Actuators
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ros2_control provides standardized command and state interfaces that can form the low-level integration boundary. ros2_control

8. Separate Planning from Control

A task planner might say:

"Reach for the object."
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The whole-body controller handles:

Hand trajectory
Torso posture
Balance
Joint limits
Contact constraints
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This separation keeps high-level reasoning independent from low-level control.

9. Add Joint Limits

Every command should respect:

q_min ≤ q ≤ q_max
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and often:

|q̇| ≤ q̇_max
|τ| ≤ τ_max
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These limits should be enforced close to the actuator boundary.

10. Handle Conflicting Goals

Suppose:

Task A: Keep feet fixed
Task B: Reach far forward
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If both cannot be satisfied, the controller should prioritize stability.

This is why hierarchical priorities or constrained optimization are important for humanoids.

11. Test in Simulation

Use:

Kinematic Tests
      ↓
Dynamic Simulation
      ↓
Hardware-in-the-Loop
      ↓
Low-Energy Hardware Tests
      ↓
Full Robot
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Start with conservative motion and verify joint limits and emergency-stop behavior.

Conclusion

Whole-body control turns a humanoid from a collection of independently controlled joints into a coordinated system.

The central idea is to express balance, contacts, manipulation, posture, and other requirements as tasks and constraints, then solve for joint-level commands while respecting physical limits.

Useful Links

Website: www.v-modal.com
SDK Flutter: https://github.com/v-modal/vmodal_sdk_flutter
SDK Android: https://github.com/v-modal/vmodal_sdk_android
Discord: https://discord.gg/K72z28KUx

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