1. Biomimetic Robots for Robust Operation in Unstructured Environments M. Cutkosky and T. Kenny Stanford University R. Full and H. Kazerooni U.C. Berkeley R. Howe Harvard University R. Shadmehr Johns Hopkins University http://cdr.stanford.edu/touch/biomimetics Site visit -- Stanford University, Sept. 2, 1990

2. Main ideas: Study insects to understand role of passive impedance (structure and control), study humans to understand adaptation and learning (Full, Howe,Shadmehr) Use novel layered prototyping methods to create compliant biomimetic structures with embedded sensors and actuators (Cutkosky, Full, Kenny) Develop biomimetic actuation and control schemes that exploit “preflexes” and reflexes for robust locomotion and manipulation (Full, Cutkosky, Howe, Kazerooni, Shadmehr) BioMimetic Robotics MURI Berkeley-Harvard Hopkins-Stanford

3. Low-Level Control Design & Fabrication High-Level Control MURI Biomimetic Robots Issues in studying, designing and building biomimetic robots (and the basic outline for today’s site visit) 1. 2. 3.

4. Low-Level Control Fabrication High-Level Control MURI What passive properties are found in Nature? What properties in mechanical design? How should properties be varied for changing tasks, conditions ? Matching ideal impedance for unstructured dynamic tasks (Harvard) Guiding questions Preflexes: Muscle and Exoskeleton Impedance Measurements (Berkeley Bio.) Biological implications for Robotics Basic Compliant Mechanisms for Locomotion (Stanford) Variable compliance joints (Harvard, Stanford) Fast runner with biomimetic trajectory (Berkeley ME)

5. Fabrication MURI Low-Level Control High-Level Control What strategies are used in insect locomotion and what are their implications? Insect locomotion studies (Berkeley Bio) New measurement capabilities (Stanford) What motor control adaptation strategies do people use and how can they be applied to robots? Compliance Learning and Strategies for Unstructured Environments (Harvard & Johns Hopkins) Implications for biomimetic robots (Harvard, Stanford) Guiding questions Are preflexes enough?

6. High-Level Control MURI Low-Level Control Fabrication How do we build robust biomimetic structures and systems? Shape deposition manufacturing of integrated parts, with embedded actuators and sensors (Stanford) How do we build-in tailored compliance and damping? Effects of Compliance in simple running machine (Stanford, Berkeley ME) Structures with functionally graded material properties (Stanford) Guiding questions

7. 9:30-11:00 Low Level Biomimetic Control Results on measurements of muscles, exoskeleton, compliance, damping (Full ~30) Implications for biomimetic robots (Bailey ~20min) Matching leg trajectory and scaling (Kazerooni ~15) Matching impedance to dynamic task (Matsuoka ~15)

8. Low-Level Control Fabrication High-Level Control MURI What passive properties are found in Nature? What properties in mechanical design? How should properties be varied for changing tasks, conditions ? Matching ideal impedance for unstructured dynamic tasks (Harvard) Preflexes: Muscle and Exoskeleton Impedance Measurements (Berkeley Bio.) Biological implications for Robotics Basic Compliant Mechanisms for Locomotion (Stanford) Variable compliance joints (Harvard, Stanford) Fast runner with biomimetic trajectory (Berkeley ME)

9. MURI Year One Meeting 1999 University of California at Berkeley Department of Integrative Biology rjfull@socrates.berkeley.edu http://polypedal.berkeley.edu University of California at Berkeley Department of Integrative Biology rjfull@socrates.berkeley.edu http://polypedal.berkeley.edu Lower Level Control Professor Robert J. Full Daniel Dudek Dr. Kenneth Meijer

10. Lower Level Control Mechanical Higher Centers Environment aero-, hydro, terra-dynamic Feedforward Controller (CPG) Adaptive Controller Sensors Closed-loop Open-loop System (Actuators, limbs) Feedback Controller Sensors Behavior

11. Chain of Reflexes Cruse Controller Inspired by Stick Insects

12. Rough Terrain Fractal Surface Variation - 3 times the height of the center of mass

13. Control Challenge Neural Mechanical Precise Novel Slow Static Feedforward Continuous Feedback (Reflexes) Control Dynamic Feedforward Gross Repetitive Rapid Continuous Feedback (Preflexes)

14. PolyPEDAL Control Musculoskeletal units, leg segments and legs do computations on their own. Control results from properties of parts and their morphology. Control algorithms embedded in the form of animal itself.

15. Lower Level Control Mechanical Higher Centers Environment aero-, hydro, terra-dynamic Feedforward Controller (CPG) Adaptive Controller Sensors Closed-loop Open-loop System (Actuators, limbs) Feedback Controller Sensors Behavior

16. Contribution to Control Feedforward Intrinsic musculo-skeletal properties Preflex Motor program acting through moment arms Passive Dynamic Self-stabilization Mechanical System PredictiveRapid acting Neural System Reflex Active Stabilization Neural feedback loops Slow acting

17. MURI Interactions Muscles and Rapid Prototyping Stanford Motor Control & Learning Johns Hopkins Sensors / MEMS Stanford Manipulation Harvard MURI Locomotion UC Berkeley Robot & Leg Mechanisms UC Berkeley

18. Manufactured Legs What properties should legs possess? Why? Act as springs to store and return energy? How? Act to reject disturbances? What properties should legs possess? Why? Act as springs to store and return energy? How? Act to reject disturbances?

19. Road Map 1. System Impedance 2. Leg Impedance 3. Muscle Impedance

20. Spring-Mass Systems LeggedSIX-

21. Virtual Leg Stiffness 10 100 0.010.0010.1110 100 Mass (kg) 1 Cockroach Crab Quail Hare Human Kangaroo Dog rel,leg k HOPPERS TROTTERS RUNNERS k rel = F mg xx x Blickhan and Full, 1993

22. Sagittal Plane Model O RGANISM Multi-Leg Spring Loaded Inverted Pendulum  k m Leg Springs ?

23. Road Map 1. System Impedance 2. Leg Impedance 3. Muscle Impedance

24. Leg as Spring & Damper ∆x∆x Force Stiffness, k Damping coefficient, c Restorative Forces and Perturbation Damping... For an Oscillating System: Force = force due to + force due to + force due to mass stiffness damping Force = kx + cx + mx

25. Experimental Setup Oscillate Leg At Multiple Frequencies To Determine k and c Oscillate Leg At Multiple Frequencies To Determine k and c Servo Motor Roach leg Length and Force recording

26. Leg Oscillation Experiments Time (s) Displacement (mm) Force (N) Small Deflection at 12 Hz

27. Leg Is Spring and Damper Displacement (mm) Force (N) Small Deflection at 12 Hz Slope ≈ Impedance

28. Effect of Frequency Displacement (mm) Force (N) k 25 Hz > k 0.08 Hz Impedance Increases with Frequency

29. Impedance Preferred Stride Frequency 12 Hz Impedance of Metathoracic Limb of Cockroach Impedance (N/m) Frequency (Hz)

30. Leg Model At high frequencies: Force  (k 1 +k 2 )*(displacement) At low frequencies: Force  k 2 *(displacement) Standard Linear Solid c k1k1 k2k2

31. Frequency vs Speed Speed (m/sec) 0 5 10 15 20 00.20.40.6 Cockroach Stride frequency (Hz) Impedance Increases Impedance Constant Alter Leg Spring Angle Take Longer Strides * Natural Frequency?

32. Impedance k 24 Hz > k 0.25 Hz Large Deflection Non-linear

33. Perturbation Rejection Restorative Force 4x Body Mass Perturbation

34. Discoveries 1. Insect leg behaves like a spring and damper system. 2. Strain energy is stored in the leg and returned. 3. Force – displacement relationship shows hysteresis with significant energy dissipation (50% or more).

35. Discoveries 4. Leg impedance increases with frequency up to 12 Hz, the preferred speed of the animal. 5. Leg impedance remains constant at frequencies above 12 Hz. 6. The leg’s natural frequency is near the frequency used by the animal at its preferred speed.

36. Discoveries 7. Insect leg could simplify control by rejecting perturbations. For a deflection of only one mm, the leg produces a force of 0.75- 4x body mass.

37. Road Map 1. System Impedance 2. Leg Impedance 3. Muscle Impedance

38. MURI Interactions Muscles and Rapid Prototyping Stanford Motor Control & Learning Johns Hopkins Sensors / MEMS Stanford Manipulation Harvard MURI Locomotion UC Berkeley Robot & Leg Mechanisms UC Berkeley

39. Manufactured Legs What properties should actuators possess? Why? Act as springs to store and return energy? How? Act to reject disturbances? Power generation? What properties should actuators possess? Why? Act as springs to store and return energy? How? Act to reject disturbances? Power generation?

40. Horizontal Plane Model O RGANISM Multi-Leg Lateral Leg Spring Muscle- Apodeme Damped Springs ?  k m

41. Muscle Lever Servo and Force Transducer Stimulation Strain Frequency - pattern - magnitude - phase - pattern - magnitude Control

42. Workloop Technique

43. Muscle Capacity 468101214 + + in vivo conditions 2 Muscle Action Potentials in vivo conditions * * 20 51015 3 Muscle Action Potentials Muscle Strain % 179 Powerspace 100 80 60 40 20 0 -200.0 -100.0 0.0 Power (W/kg) 177c Powerspace Stimulation phase (%) Spring Damper Motor

44. Musculo-skeletal Model Force Velocity Insect Leg Intrinsic musculo-skeletal properties Preflexes Brown and Loeb, 1999

45. Active+Passive Force Passive Force Length Increase Perturbation Experiments Servo and Force Transducer Stimulation Passive Muscle Stiffness Significant

46. Effect of Step Length Increase Stimulated (Twitch) Relaxed Passive resistance is significant in muscle 177c (n = 4) 012 3 0 20 40 60 Step size (%) Force increase (mN)

47. Oscillatory Perturbations 0200 -5 0 5 0.5 % Muscle strain (%) Force (mN) Time (ms) -0.2500.25 -5 5 Muscle strain (%) Force (mN) Phase angle E complex =(  Force/Area)/strain E viscous /E elastic =tan(phase angle)

48. Visco-elastic Properties Passive Muscle Impedance increases with frequency in muscle 179 Impedance independent of frequency in muscle 177c Significant viscous damping in both muscles. Passive Muscle Impedance increases with frequency in muscle 179 Impedance independent of frequency in muscle 177c Significant viscous damping in both muscles. Frequency (Hz) tan(phase angle) E complex (N/m 2 ) Frequency (Hz)

49. Effect of Length Passive Muscle Impedance increases with length Contribution viscous damping decreases with length Passive Muscle Impedance increases with length Contribution viscous damping decreases with length

50. Perturbation experiments 0 0 300 100 Locomotion cycle (%) Force (mN) 0 100 + Locomotion cycle (%) Strain Locomotor pattern Sinusoid (A=0.5%,f=200 Hz ) 7% Impedance during workloop.

51. Multiple Muscle System Anatomically similar muscles provide impedance during different phases of the locomotion cycle! Anatomically similar muscles provide impedance during different phases of the locomotion cycle! Muscle strain (%)

52. Discoveries 1. Passive muscle can reject perturbations. 2. Preflexes comprise passive (fixed) and active components (adjustable). 3. Passive muscle acts like a visco-elastic actuator. (Viscous damping is responsible for a significant part of total force response to perturbation.) 4. Impedance of anatomically similar muscles is distributed over the locomotion cycle.

53. Impact on Deliverables 1. Energy storage 2. Reject perturbations 3. Simplify control 4. Penetrate new environments 5. Increase robustness 1. Energy storage 2. Reject perturbations 3. Simplify control 4. Penetrate new environments 5. Increase robustness

54. Low-Level Control Fabrication High-Level Control MURI What passive properties are found in Nature? What properties in mechanical design? How should properties be varied for changing tasks, conditions ? Matching ideal impedance for unstructured dynamic tasks (Harvard) Guiding questions Preflexes: Muscle and Exoskeleton Impedance Measurements (Berkeley Bio.) Basic Compliant Mechanisms for Locomotion Biological implications for Robotics (Stanford) Variable compliance joints (Harvard, Stanford) Fast runner with biomimetic trajectory (Berkeley ME)

55. Low-Level Control MURI Locomotion: Biomimetic Ideology Goal: –Navigate rough terrain with simple, robust, compliant robots Mindset shaped by Biology –Tunable, passive mechanical properties –Purpose-specific geometry –Simple control scheme –Robust components

56. Low-Level Control MURI Variable Compliance?: Interpreting Biological Findings Force Displacement Load Unload Idea –Desired reaction forces depend on the environment and locomotion speed How do we represent these findings? –Not traditional spring or damper elements –Energy spent per cycle independent of frequency (area enclosed by curve is the energy spent) Results suggest hysteretic damping

57. Low-Level Control MURI Variable Impedance: New Design Direction What’s the difference between compliance and impedance? –Impedance refers to the relationship: dF/dx –Stiffness refers to particular impedance relationship, namely: dF/dx = k Hysteretic Damping –Characteristic of some heterogeneous materials –Loading and unloading create different stress-strain paths –Stress-strain curve is independent of frequency Design Implications –Compliance is mainly a function of displacement –Damping has a significant frequency dependant term

58. Low-Level Control MURI Variable Impedance: Design Approach Traditional Robotic Compliance –Actuator powered –Proportional feedback control - variable compliance –Complex multiple control laws with different objectives must work together Low bandwidth - controller delays

59. Low-Level Control MURI Variable Impedance: Design Approach Different Approach –Compliant member powered –Adjustable geometry - variable impedance –Simple mechanical properties are more predictable separate from control law intrinsic low level stability Biology is telling us what mechanical properties we really need SDM robot limb with compliance and damping Variable Stiffness Joint Concept

60. Low-Level Control MURI Sprawl 1.0: Legged Testbed Capture the essential locomoting elements in a low DOF robot Explore the roles of compliance and damping in locomotion Identify areas which can be improved by SDM

61. Low-Level Control MURI Sprawl 1.0: Biomimetic, not just a copy Full’s research highlights certain important locomoting components –Power-producing thrust muscles –Supporting/repositioning hip joints

62. Low-Level Control MURI Sprawl 1.0: Thrusting Full’s research on power-producing muscles 177a,c,d,e (Ahn, Meijer) Thrust production - Decoupled, compliant system Cockroach Geometry Force and Workspace Femur Tibia 11 22 Force and Workspace Robotics Analysis Force and Workspace Sprawl 1.0 Geometry Very Low Friction Pneumatic Piston

63. Sprawl 1.0 Geometry Damped, Compliant RC Servo Actuator Low-Level Control MURI Sprawl 1.0: Repositioning/Supporting Full’s research on Trochanter-Femur joint (Dudek) Repositioning/Supporting - Decoupled, compliant system Cockroach Geometry g Actuated Body-Coxa joint Compliant Trochanter-Femur joint

64. Low-Level Control MURI Sprawl 1.0: Findings Good design and passive mechanical properties take burden off control –Compliance and damping –Simple alternating tripod locomotion scheme –Built-in posture control Low bandwidth geometry changes –Walking, stopping, turning, and running Need for robust components –Traditional components are not robust - poster child for SDM

65. Low-Level Control MURI Sprawl 1.0: Future Work Suggestions from Full –Change location of center of mass –Increase gait frequency –Dynamically control middle leg set points –Weaken front leg force Work in Progress –Add compliant springs in parallel with constant force pistons –Replace RC servo hip actuators with more biomimetic components