Physics

Nonlinear system

Zero moment point

Inverted pendulum

Motion capture

Humanoid robot

Motion (physics)

Algorithm

Inertia

Epistemology

Philosophy

Artificial intelligence

Angular momentum

Control (management)

Computer science

Computation

Simple (philosophy)

Quantum mechanics

Kinematics

Simulation

Control theory (sociology)

Classical mechanics

Robot

Ground reaction force

It is known that for a large magnitude push a human or a humanoid robot must take a step to avoid a fall. Despite some scattered results, a principled approach towards "when and where to take a step" has not yet emerged. Towards this goal, we present methods for computing capture points and the capture region, the region on the ground where a humanoid must step to in order to come to a complete stop. The intersection between the capture region and the base of support determines which strategy the robot should adopt to successfully stop in a given situation. Computing the capture region for a humanoid, in general, is very difficult. However, with simple models of walking, computation of the capture region is simplified. We extend the well-known linear inverted pendulum model to include a flywheel body and show how to compute exact solutions of the capture region for this model. Adding rotational inertia enables the humanoid to control its centroidal angular momentum, much like the way human beings do, significantly enlarging the capture region. We present simulations of a simple planar biped that can recover balance after a push by stepping to the capture region and using internal angular momentum. Ongoing work involves applying the solution from the simple model as an approximate solution to more complex simulations of bipedal walking, including a 3D biped with distributed mass.

Capture Point: A Step toward Humanoid Push Recovery