MIT Artificial Intelligence Laboratory — Research Directions
Legged Robots
Gill Pratt
MIT Artificial Intelligence Laboratory — Research Directions
Why Do Robot Systems Emphasize Stiff Trajectories Instead of Forces?
• Trajectories are more easily seen than forces
• Most Industrial Robot Tasks (to date) are Trajectory tasks– Painting
– Welding
• Humans, even when trying to be stiff, are soft when walking or doing other tasks
• Our Thesis: Most Natural Robotic Tasks require “low (mechanical) impedance” thinking
MIT Artificial Intelligence Laboratory — Research Directions
Can Legged Robots Work This Way?
• A: Yes! But requires that forces, as well as trajectories be considered
• First, this requires actuators that have:– Low minimum (mechanical) impedance (i.e. can be soft)
– High force fidelity + dynamic range
– Robustness to Shock
– Energy Storage
MIT Artificial Intelligence Laboratory — Research Directions
But We’re Stuck with Electric-Magnetic Actuators
• Electric actuators have decent power if run at high speed, but force/torque is low– Direct drive is too heavy for autonomous robots.
– Gears are necessary to multiply force/torque and allow the actuator to run at high speed.
– But gears introduce a number of terrible disadvantages …
MIT Artificial Intelligence Laboratory — Research Directions
Disadvantages of Gear Reduction
• N2 increase in apparent inertia for N:1 speed reduction
» Low output impedances are impossible to achieve
• Backlash / Friction » Output force control has low resolution
» Can be improved with novel gears (e.g. Artisan) but not inexpensively
• Economical Gear Reductions are intolerant to shock– Output teeth break due to single tooth contacts
– Can be improved (e.g. harmonic drive) but not inexpensively
• Poor regeneration (back-drive) efficiency
MIT Artificial Intelligence Laboratory — Research Directions
• Spring in series with motor output
• Spring converts motor position into output force
• Measure spring deflection to control output force
• Series elasticity intentionally used to obtain good force control
Motor andGearbox
Spring
Bearing
Actuatoroutput
Our Solution: Series-Elastic Actuators
MIT Artificial Intelligence Laboratory — Research Directions
Series-Elastic Actuators(Tendon Elastic)
MIT Artificial Intelligence Laboratory — Research Directions
Series-Elastic Actuators
Torsion spring
Revolute/Stiffening
Linear
Compact DC brushless
MIT Artificial Intelligence Laboratory — Research Directions
Spring Flamingo — Low Impedance
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MIT Artificial Intelligence Laboratory — Research Directions
Walking Algorithms: Motivations for the Virtual Model Control language
• (almost) all of us have good physical intuition
• (very) few of us have formal control intuition
• Passive walkers work using physical components
• Q: Can active walker algorithms be expressed using physical metaphors?
– A: Yes, and they perform surprisingly well
• Key Idea: Add Control in Parallel with natural dynamics of mechanism
MIT Artificial Intelligence Laboratory — Research Directions
Virtual Model ControlPeg-Leg 2-D Walking
• Body Height / Posture maintained via a virtual wheeled “walker”, regardless of # of legs on ground
MIT Artificial Intelligence Laboratory — Research Directions
Virtual Model ControlPeg-Leg 2-D Walking
• Speed is Controlled by “food placement” of a virtual dog-track rabbit instead of “foot placement”.
• Double-support speed control is possible only because we have good force control on each leg.
MIT Artificial Intelligence Laboratory — Research Directions
Simulated Pole-Balancing Hexapod under VMC
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MIT Artificial Intelligence Laboratory — Research Directions
“Spring Turkey” under VMC
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MIT Artificial Intelligence Laboratory — Research Directions
“Spring Flamingo” Walking Over Rough Terrain Blindly
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MIT Artificial Intelligence Laboratory — Research Directions
Informal Robustness(see papers for real numbers)
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MIT Artificial Intelligence Laboratory — Research Directions
Recent News:M2 – A Human Sized Biped Robot
12 Degrees of Freedom28 kg(62 lbs)0.97 m(38 in) hip height
MIT Artificial Intelligence Laboratory — Research Directions
M2 Hardware First Steps
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