Control of Humanoid Robots

1. Control of Humanoid Robots Personal robotics Guidance of gait 12 November 2009, UT Austin, CS Department Luis Sentis, Ph.D.

2. Assessment of Disruptive Technologies by 2025 (Global Trends)

3. Human-Centered Robotics • Human on the loop: • Personal / Assitive robotics (health) • Unmanned surveillance systems (defense / IT) • Modeling and guidance of human movement (health)

4. Current Projects: Compliant Control of Humanoid Robots

5. Recent Project:Guidance of Gait Using Functional Electrical Stimulation

6. CONTROL OF HUMANOID ROBOTS

7. General Control Challenges • Dexterity: How can we create and execute advanced skills that coordinate motion, force, and compliant multi-contact behaviors • Interaction: How can we model and respond to the constrained physical interactions associated with human environments? • Autonomy:How can we create action primitives that encapsulate advance skills and interface them with high level planners PARKOUR

8. The Problem (Interactions) Coordination of complex skills using compliant multi-contact interactions • Operate efficiently under arbitrary multi-contact constraints • Respond compliantly to dynamic changes of the environment • Plan multi-contact maneuvers

9. Key Challenges (Interactions) • Find representations of the robot internal contact state • Express contact dependencies with respect to frictional properties of contact surfaces • Develop controllers that can generate compliant whole-body skills • Plan feasible multi-contact behaviors

10. Approach (8 years of development) • Models of multi-contact and CoM interactions • Methodology for whole-body compliant control • Planners of optimal maneuvers under friction • Embedded control architecture

11. Humanoids as Underactuated Systems in Contact • Model-based approach: Euler-Lagrange Non-holonomic Constraints(Underactuated DOFs) External Forces Torque commands Whole-bodyAccelerations External forces

12. Model of multi-contact constraints Assigning stiff model: • Accelerations are spanned by the contact null-space multiplied by the underactuated model:

13. Model of Task Kinematics Under Multi-Contact Constraints • Operational point (task to joints) qarms • Differential kinematics xbase x • Reduced contact-consistent Jacobian qlegs

14. Modeling of Internal Forces and Moments

15. Variables representing the contact state

16. Aid using the virtual linkage model (predict what robot can do) C C C C Internal tensions Center of Mass Center of pressure points Grasp / Contact Matrix Normal moments

17. Properties Grasp/Contact Matrix • Models simultaneously the internal contact state and Center of Mass inter-dependencies • Provides a medium to analyze feasible Center of Mass behavior • Emerges as an operator to plan dynamic maneuvers in 3d surfaces

18. Example on human motion analysis(is the runner doing his best?)

19. More Details of the Grasp / Contact Matrix • Balance of forces and moments: • Underdetermined relationship between reaction forces and CoM behavior: Optimal solution wrt friction forces

20. Example on analysis of stability regions (planning locomotion / climbing)

21. Approach • Models of multi-contact and CoM interactions • Methodology for whole-body compliant control • Planners of optimal maneuvers under friction • Embedded control architecture

22. Torque control: unified force and motion control(compliant control) Control of the task forces (pple virtual work) Control of the task motion Stanford robotics / AI lab Linear Control Potential Fields

23. Inverse kinematics vs. torque control Torque control: Inverse kinematics: duality Pros: Forces appear Compliant because of dynamics Cons: Requires torque control Pros: Trajectory based Cons: Ignores dynamics Forces don’t appear

24. Highly Redundant Systems Under Constraints

25. Prioritized Whole-Body Torque Control • Prioritization (Constraints first): • Gradient descent is in the manifold of the constraint

26. Constrained-consistent gradient descent x un-constrained x task • Constrained kinematics: • Optimal gradient descent:

27. Constrained Multi-Objective Torque Control • Lightweight optimization • Decends optimally in constrained-consistent space • Resolves conflicts between competing tasks

28. Torque control of humanoids under contact

29. Control of Advanced Skills

30. Example: Interactive Manipulation

31. Control of internal forces • Manifold of closed loops • Unified motion / force / contact control

32. Compliant Control of Internal Forces • Using previous torque control structure, estimation of contact forces, and the virtual linkage model:

33. Simulation results

35. Approach • Models of multi-contact and CoM interactions • Methodology for whole-body compliant control • Planners of optimal maneuvers under friction • Embedded control architecture

36. Contact Requisites: Avoid Rotations and Friction Slides Rotational Contact Constraints: Need to maintain CoP in support area C Frictional Contact Constraints: Need to control tensions and CoM behavior to remain in friction cones

37. Automatic control of CoP’s and internal forces Motion control

38. CoM control

39. Example: CoM Oscillations

40. Specifications

41. Multiple steps: forward trajectories

42. Results: lateral steps

43. Approach • Models of multi-contact and CoM interactions • Methodology for whole-body compliant control • Planners of optimal maneuvers under friction • Embedded control architecture

47. Demos Asimo • Upper body compliant behaviors • Honda’s balance controller • Torque to position transformer

48. Summary • Models of multi-contact and CoM interactions • Methodology for whole-body compliant control • Planners of optimal maneuvers under friction • Embedded control architecture Grasp Matrix

49. PRESENTATION’S END