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Safwan Choudhury
April 25, 2012
Research
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2
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Bipedal Locomotion
ME 780 Graduate Course Presentation
Safwan Choudhury
April 25, 2012
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Transcript
Bipedal Locomotion ME 780: Course Project Safwan Choudhury
Biped Locomotion ★ Motivations ★ Project Goals ★ Bipedal Locomotion
★ Control Strategy ★ Next Steps
Motivations ★ Navigating Human Environments
ZMP Example 2011 Honda Asimo Video
Passive Dynamics Passive Dynamic Walker Video
MASc Research Goals ★ Virtual Passive Dynamics ★ Foot Placement
Estimator ★ Minimizing energy consumption ★ Human-Like Gait Cycles
MASc Research Platform
MASc Research Platform
Project Goals ★ ZMP-Based Walking Controller ★ Sensory Inputs: •
Inertial Measurement Units (IMU) • Force/Contact Sensors
Zero-Moment Point ★ Point where the inertial and gravity moments
cancel out (i.e. the moment is zero). ★ Guarantees stability if this point is within the support polygon.
Support Polygon
Linear Inverted Pendulum ★ Models entire biped as a single
point mass located at the center of gravity (COM)
ZMP Equation
Contact Model
Control Strategy ★ Joint Space Control ★ Operational Space Control
★ Center-of-Mass (COM) Control ★ ZMP-Based Control
qref [−0.8 0.3] Kp 0.1 Kd 0.02 ForwardDynamics u q
qd qdd Error Signal Command Torque Angular Velocites Angular Positions Joint Space Control
Operational Space Control ★ Jacobian matrix provides the mapping between
joint space and operational space.
Operational Space
Operational Space
Force Sensors
Gravity Compensation q x_com x = Jq qd = inv(Jcom)
xd Kp 10 Kd 2 CF qdd qd q u Forward Dynamics u q qd qdd CF qd xd xd qd q com COM Reference (−0.0039 0.0086 0.4022) COM Control
Gravity Compensation q x_com x = Jq qd = inv(Jcom)
xd x_com x_zmp Stable COM Generator ZMP Reference −C− Kp 10 Kd 2 CF qdd qd q u Forward Dynamics u q qd qdd CF zmp com com zmp qd xd xd qd q com ZMP Control
Walking Simulation
Walking Simulation
Next Steps ★ IMU Modelling + Additive Noise ★ Implementing
EKF-Based Estimation ★ State Machine for Cyclic Gait
Questions?