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