In order for a higher layer of software to perform necessary monitoring, and eventual modification, of the locomotion layer, we have been following two approaches. The first is to extract a simplified predictive model of the walking controller. The upper layer of software can make short-range predictions about the trajectory of the lower layer controller in the configuration space, and in particular can predict entering a particularly bad region of configuration space before it happens. Our intent is for the upper layer to intervene in a minimal way to alter the behavior of the lower layer. The consequence is mechanical instability and stumbling in the gait.
Minimal intervention consists of slowing the gait, or commanding a leg to enter return stroke early.
As mentioned above, brute force intervention such as freezing the motion by interrupting the controller is contrary to our goals. The second approach to enabling higher layer monitoring is to extract additional information from sensory data that is used by the lower layer. This information may consist of correlations, clusters, or other long time scale measurements. We intend this information to be used mostly for modifying the lower layer in response to environmental changes. However much more information is available, both in time and in force resolution.