4 research outputs found
On the Hardware Feasibility of Nonlinear Trajectory Optimization for Legged Locomotion based on a Simplified Dynamics
Simplified models are useful to increase the computational efficiency of a
motion planning algorithm, but their lack of accuracy have to be managed. We
propose two feasibility constraints to be included in a Single Rigid Body
Dynamicsbased trajectory optimizer in order to obtain robust motions in
challenging terrain. The first one finds an approximate relationship between
joint-torque limits and admissible contact forces, without requiring the joint
positions. The second one proposes a leg model to prevent leg collision with
the environment. Such constraints have been included in a simplified nonlinear
nonconvex trajectory optimization problem. We demonstrate the feasibility of
the resulting motion plans both in simulation and on the Hydraulically actuated
Quadruped (HyQ) robot, considering experiments on an irregular terrain
Post-Impact Adaptive Compliance for Humanoid Falls Using Predictive Control of a Reduced Model
International audienceWe consider control of a humanoid robot in active compliance just after the impact consecutive to a fall. The goal of this post-impact braking is to absorb undesired linear momentum accumulated during the fall, using a limited supply of time and actuation power. The gist of our method is an optimal distribution of undesired momentum between the robot's hand and foot contact points, followed by the parallel resolution of Linear Model Predictive Control (LMPC) at each contact. This distribution is made possible thanks to \emph{torque-limited friction polytopes}, an extension of friction cones that takes actuation limits into account. Individual LMPC results are finally combined back into a feasible CoM trajectory sent to the robot's whole-body controller. We validate the solution in full-body dynamics simulation of an HRP-4 humanoid falling on a wall