1. MURI High-Level Control Biomimetic Robots - ONR Site Visit - August 9, 2000 1 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? Learning and Compliance Strategies for Unstructured Environments (Harvard & Johns Hopkins) Implications for biomimetic robots (Harvard, Johns Hopkins, Stanford) Guiding questions

2. MURI High-Level Control Biomimetic Robots - ONR Site Visit - August 9, 2000 2 Biological Motor 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 Preflexes

3. MURI High-Level Control Biomimetic Robots - ONR Site Visit - August 9, 2000 3 Human Arm Model Simplifies experiments –Excellent adaptability –Instructable subjects –Simple apparatus Manipulation application –Role of impedance less understood

4. MURI High-Level Control Biomimetic Robots - ONR Site Visit - August 9, 2000 Learning Impedance Strategies in Unstructured Environments Robert D. Howe and Yoky Matsuoka Division of Engineering and Applied Sciences Harvard University

5. MURI High-Level Control Biomimetic Robots - ONR Site Visit - August 9, 2000 5 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

6. MURI High-Level Control Biomimetic Robots - ONR Site Visit - August 9, 2000 6 Impedance “preflex” can produce robust behavior (Full) Preflexes are tailored to specific tasks and environments Goal: Understand relationship between impedance value and task/environment Approach: Measure impedances and adaptation strategies in realistic settings Understanding Impedance Change over Time

7. MURI High-Level Control Biomimetic Robots - ONR Site Visit - August 9, 2000 7 Develop a system that identifies impedance during execution of various tasks. –Virtual Environment Characterize impedance change over time –“Instantaneous” identification technique Investigate impedance adaptation characteristics –How do humans adapt to a required impedance for the task? –What is the initial strategy for a novel task? –What does the initial strategy depend on? Experimental Technique

8. MURI High-Level Control Biomimetic Robots - ONR Site Visit - August 9, 2000 8 Assumptions for System Identification Work with the end-point impedance Represent hand as a linear, second- order system. k b m F Parameter identification is easy for time- invariant systems - Assume constant m,b, and k - Apply perturbation, repeat, and average.

9. MURI High-Level Control Biomimetic Robots - ONR Site Visit - August 9, 2000 9 Previous System Identification Technique for Time Varying Systems Time varying system –Requires multiple perturbations for each data point. –PRBS (Bennett et al. 1992, Lacquaniti et al. 1993) –Repetition hides learning –Single task

10. MURI High-Level Control Biomimetic Robots - ONR Site Visit - August 9, 2000 10 Creating a Task-Based Environment Use a PHANToM haptic interface (3 DOF) to apply task-based force feedback Permits software control of task parameters Use force and acceleration sensors near the hand. Handle & accelerometer Force sensor Robot

11. MURI High-Level Control Biomimetic Robots - ONR Site Visit - August 9, 2000 11 Data Acquisition System (10kHz) Processor (servo loop 1kHz) Human Subject Controller Interactions Computer Monitor (30Hz) Handle & accelerometer Force sensor Robot Motors and Encoders Virtual Environment Dynamic Simulation

12. MURI High-Level Control Biomimetic Robots - ONR Site Visit - August 9, 2000 12 Using Impulse-Based “Instantaneous” System Identification Use task-based force feedback if task interaction is impulse like Use added impulse force perturbation otherwise Identify within 40 msec, prior to CNS involvement: - prefelexes only Assume passive impedance is constant during 40 msec identification window

13. MURI High-Level Control Biomimetic Robots - ONR Site Visit - August 9, 2000 13 Example Task: Bouncing a ball to a target height Handle corresponds to the paddle on the monitor Before During After VIEW ON MONITOR: Ball drops too quickly for visual reaction: bounce height set by hand impedance

14. MURI High-Level Control Biomimetic Robots - ONR Site Visit - August 9, 2000 14 Contact Task Model: Three Stages in Bouncing a Ball Stage 1: Ball falling (before contact) –given Stage 2: During contact Stage 3: Ball rising (after contact) –given ball

15. MURI High-Level Control Biomimetic Robots - ONR Site Visit - August 9, 2000 15 Task-Based Impulsive Force 01020304050 -3 -2 0 01020304050 -10 -5 0 5 01020304050 -0.1 -0.05 0 0.05 01020304050 -3 -2 Time (msec) Force (N) (measured) Accel. (m/s^2) (measured) Velocity (m/s) Position (mm) Using the virtual environment contact task force

16. MURI High-Level Control Biomimetic Robots - ONR Site Visit - August 9, 2000 16 Confirmation of the Technique 0 10203040 F m*a k*x b*v Time (msec) Least Square Fit r = 0.988 (mean) Accuracy –mass+/- 8.1 % –spring +/- 2.5% 2 -3 -2.5 -2 -1.5 -0.5 0.5 1 1.5 2 0 Force (N)

17. MURI High-Level Control Biomimetic Robots - ONR Site Visit - August 9, 2000 17 Contact Task Experimental Design 1 Used wrist movement to bounce the ball up to a target height Impedance too high bounces too high Impedance too low bounces too low Visual feedback of success/ failure each trial Six sets of 40 bounces Group1: low, high, …, low, high; Group2: high, low, …, high, low

18. MURI High-Level Control Biomimetic Robots - ONR Site Visit - August 9, 2000 18 Group2 (high, low) Group1 (low, high) Typical Stiffness Learning Curve (n=1) K (N/m) trials Low Target High Target

19. MURI High-Level Control Biomimetic Robots - ONR Site Visit - August 9, 2000 19 Group2 (high, low) Group1 (low, high) Typical Damping Learning Curve (n=1) 010203040 10 15 20 25 30 010203040 10 15 20 25 30 010203040 10 15 20 25 30 010203040 10 15 20 25 30 B (N.s/m) trials High Target Low Target

20. MURI High-Level Control Biomimetic Robots - ONR Site Visit - August 9, 2000 20 010203040 0 200 400 600 800 1000 010203040 0 200 400 600 800 1000 010203040 0 200 400 600 800 1000 010203040 First Exposure Second Exposure First versus Second Exposure to the Task (n=5) K (N/m) High Target Low Target trials A= - 0.08 A= - 0.3

21. MURI High-Level Control Biomimetic Robots - ONR Site Visit - August 9, 2000 21 Stiffness Adaptation Characteristics for Contact Task Experiment Initial stiffness: same (~200 N/m) regardless of target impedance Final stiffness: tuned to target (range 200-650 N/m) Learning follows exponential curve Adaptation is faster for the second exposure (for high target impedance) - First exposure: A= - 0.08 - Second exposure: A= - 0.3

22. MURI High-Level Control Biomimetic Robots - ONR Site Visit - August 9, 2000 22 Precision Limitations 02040 0 500 1000 02040 10 20 30 02040 500 1000 02040 10 20 30 02040 0 500 1000 02040 10 20 30 K(N/m) B(Ns/m) 02040 0 500 1000 30 02040 10 20 0 40 0 500 1000 30 02040 10 20 0 40 0 500 1000 02040 10 20 30 K(N/m) B(Ns/m) NARROWING TARGET STIFFNESS NARROWING TARGET DAMPING

23. MURI High-Level Control Biomimetic Robots - ONR Site Visit - August 9, 2000 23 200 400 600 800 Average Stiffness 12 14 16 18 20 123456 0 25 50 % Success rate with narrowing window Precision limitations Average Damping 123456 123456 NARROWING TARGET WINDOW

24. MURI High-Level Control Biomimetic Robots - ONR Site Visit - August 9, 2000 24 Position Task Experimental Design Handle corresponds to the paddle on the computer screen Used wrist movement to track a moving ball (const. velocity). Game over if ball dropped. 5 continuous minutes of recording with added perturbations. Group1: Large paddle; Group2: Small paddle

25. MURI High-Level Control Biomimetic Robots - ONR Site Visit - August 9, 2000 25 Stiffness Adaptation in Position Task (n=5) 01020304050 100 200 300 400 500 600 700 800 900 1000 01020304050 100 200 300 400 500 600 700 800 900 1000 Group 1: Large paddle Group 2: Small paddle K(N/m) time (1/10 min)

26. MURI High-Level Control Biomimetic Robots - ONR Site Visit - August 9, 2000 26 Stiffness Adaptation Characteristics for Position Task Experiment Initial stiffness: same (~740 N/m) regardless of paddle size. Amplitude of initial stiffness different for position and contact tasks. Final stiffness: for the easier task, stiffness dropped lower and faster. Group1: Large paddle Group2: Small paddle

27. MURI High-Level Control Biomimetic Robots - ONR Site Visit - August 9, 2000 27 Summary Developed new experimental technique - “instantaneous” impedance measurement permits examination of learning and adaptation - virtual environment allows easy examination of a wide range of tasks Initial strategy depends on the overall task Final strategy depends on the environmental parameters Damping cannot be independently controlled