2,196 research outputs found
Integration of vertical COM motion and angular momentum in an extended Capture Point tracking controller for bipedal walking
In this paper, we demonstrate methods for bipedal walking control based on the Capture Point (CP) methodology.
In particular, we introduce a method to intuitively derive a CP
reference trajectory from the next three steps and extend the
linear inverted pendulum (LIP) based CP tracking controller
introduced in [1], generalizing it to a model that contains
vertical CoM motions and changes in angular momentum.
Respecting the dynamics of general multibody systems, we
propose a measurement-based compensation of multi-body
effects, which leads to a stable closed-loop dynamics of bipedal walking robots. In addition we propose a ZMP projection method, which prevents the robots feet from tilting and ensures the best feasible CP tracking. The extended CP controller’s performance is validated in OpenHRP3 [2] simulations and compared to the controller proposed in [1]
Straight-Leg Walking Through Underconstrained Whole-Body Control
We present an approach for achieving a natural, efficient gait on bipedal
robots using straightened legs and toe-off. Our algorithm avoids complex height
planning by allowing a whole-body controller to determine the straightest
possible leg configuration at run-time. The controller solutions are biased
towards a straight leg configuration by projecting leg joint angle objectives
into the null-space of the other quadratic program motion objectives. To allow
the legs to remain straight throughout the gait, toe-off was utilized to
increase the kinematic reachability of the legs. The toe-off motion is achieved
through underconstraining the foot position, allowing it to emerge naturally.
We applied this approach of under-specifying the motion objectives to the Atlas
humanoid, allowing it to walk over a variety of terrain. We present both
experimental and simulation results and discuss performance limitations and
potential improvements.Comment: Submitted to 2018 IEEE International Conference on Robotics and
Automatio
Push recovery with stepping strategy based on time-projection control
In this paper, we present a simple control framework for on-line push
recovery with dynamic stepping properties. Due to relatively heavy legs in our
robot, we need to take swing dynamics into account and thus use a linear model
called 3LP which is composed of three pendulums to simulate swing and torso
dynamics. Based on 3LP equations, we formulate discrete LQR controllers and use
a particular time-projection method to adjust the next footstep location
on-line during the motion continuously. This adjustment, which is found based
on both pelvis and swing foot tracking errors, naturally takes the swing
dynamics into account. Suggested adjustments are added to the Cartesian 3LP
gaits and converted to joint-space trajectories through inverse kinematics.
Fixed and adaptive foot lift strategies also ensure enough ground clearance in
perturbed walking conditions. The proposed structure is robust, yet uses very
simple state estimation and basic position tracking. We rely on the physical
series elastic actuators to absorb impacts while introducing simple laws to
compensate their tracking bias. Extensive experiments demonstrate the
functionality of different control blocks and prove the effectiveness of
time-projection in extreme push recovery scenarios. We also show self-produced
and emergent walking gaits when the robot is subject to continuous dragging
forces. These gaits feature dynamic walking robustness due to relatively soft
springs in the ankles and avoiding any Zero Moment Point (ZMP) control in our
proposed architecture.Comment: 20 pages journal pape
Pattern Generation for Walking on Slippery Terrains
In this paper, we extend state of the art Model Predictive Control (MPC)
approaches to generate safe bipedal walking on slippery surfaces. In this
setting, we formulate walking as a trade off between realizing a desired
walking velocity and preserving robust foot-ground contact. Exploiting this
formulation inside MPC, we show that safe walking on various flat terrains can
be achieved by compromising three main attributes, i. e. walking velocity
tracking, the Zero Moment Point (ZMP) modulation, and the Required Coefficient
of Friction (RCoF) regulation. Simulation results show that increasing the
walking velocity increases the possibility of slippage, while reducing the
slippage possibility conflicts with reducing the tip-over possibility of the
contact and vice versa.Comment: 6 pages, 7 figure
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