| dc.description.abstract | Currently, passive robots are designed following a trial and error process
in which the existence of a stable walking cycle for a given passive robot’s model
is analyzed using Poincaré maps. The standard stability analysis procedure suffers
from discretization aliasing, and it is not able to deal with complex passive models.
In this paper a methodology that allows finding conditions on the robot’s parameters
of a given passive model in order to obtain a stable walking cycle is proposed. The
proposed methodology overcomes the aliasing problem that arises when Poincaré
sections are discretized. Basically, it implements a search process that allows finding
stable subspaces in the parameters’ space (i.e., regions with parameters’ combinations
that produce stable walking cycles), by simulating the robot dynamics for
different parameters’ combinations. After initial conditions are randomly selected,
the robot’s dynamics is modeled step by step, and in the Poincaré section the
existence of a walking cycle is verified. The methodology includes the definition of a
search algorithm for exploring the parameters’ space, a method for the partition of
the space in hypercubes and their efficient management using proper data structures,and the use of so-called design value functions that quantify the feasibility of the
resulting parameters. Among the main characteristics of the proposed methodology
are being robot independent (it can be used with any passive robot model, regardless
of its complexity), and robust (stable subspaces incorporate a stability margin value
that deals with differences between the robot’s model and its physical realization).
The methodology is validated in the design process of a complex semi-passive robot
that includes trunk, knees, and non-punctual feet. The robot also considers the use
of actuators, controllers and batteries for its actuation. | |
