1,204 research outputs found
Push Recovery of a Position-Controlled Humanoid Robot Based on Capture Point Feedback Control
In this paper, a combination of ankle and hip strategy is used for push
recovery of a position-controlled humanoid robot. Ankle strategy and hip
strategy are equivalent to Center of Pressure (CoP) and Centroidal Moment Pivot
(CMP) regulation respectively. For controlling the CMP and CoP we need a
torque-controlled robot, however most of the conventional humanoid robots are
position controlled. In this regard, we present an efficient way for
implementation of the hip and ankle strategies on a position controlled
humanoid robot. We employ a feedback controller to compensate the capture point
error. Using our scheme, a simple and practical push recovery controller is
designed which can be implemented on the most of the conventional humanoid
robots without the need for torque sensors. The effectiveness of the proposed
approach is verified through push recovery experiments on SURENA-Mini humanoid
robot under severe pushes
Imprecise dynamic walking with time-projection control
We present a new walking foot-placement controller based on 3LP, a 3D model
of bipedal walking that is composed of three pendulums to simulate falling,
swing and torso dynamics. Taking advantage of linear equations and closed-form
solutions of the 3LP model, our proposed controller projects intermediate
states of the biped back to the beginning of the phase for which a discrete LQR
controller is designed. After the projection, a proper control policy is
generated by this LQR controller and used at the intermediate time. This
control paradigm reacts to disturbances immediately and includes rules to
account for swing dynamics and leg-retraction. We apply it to a simulated Atlas
robot in position-control, always commanded to perform in-place walking. The
stance hip joint in our robot keeps the torso upright to let the robot
naturally fall, and the swing hip joint tracks the desired footstep location.
Combined with simple Center of Pressure (CoP) damping rules in the low-level
controller, our foot-placement enables the robot to recover from strong pushes
and produce periodic walking gaits when subject to persistent sources of
disturbance, externally or internally. These gaits are imprecise, i.e.,
emergent from asymmetry sources rather than precisely imposing a desired
velocity to the robot. Also in extreme conditions, restricting linearity
assumptions of the 3LP model are often violated, but the system remains robust
in our simulations. An extensive analysis of closed-loop eigenvalues, viable
regions and sensitivity to push timings further demonstrate the strengths of
our simple controller
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