The last months Lucy has been assembled and debugged, therefore basic control strategies
were implemented. On high level a quasistatic trajectory generation was used to balance the
robot and to make it's first steps. On joint level an adapted feedback PI controller was
implemented to settle position. The output of this controller is a deltap signal, which will be
added by and subtracted from a chosen mean pressure resulting in two new pressure values for
both muscles of a joint. These new values are the set points for the bangbang pressure controllers.
In order to avoid overshoots the integral term was made adaptive. When pressure differences
are too high, the pressure controller won't be able to settle the pressure and thus the integral
term will be lowered. In addition different sets for P and I values were used depending
whether a leg is support leg or swing leg.
The graphs below show results of the first movements of Lucy. Here Lucy stands up from its
rest position with both feet on the ground, lifts up and positions the left leg 0.1m further than
the ankle of the stance leg. The same action is than performed by the right leg and next the left
leg lifts again and places the feet back together after which the robot finally goes to its rest
position.
First experimental steps: angle and pressure values for the left leg
At the left side of the figure angle, desired angle and the difference between them is given for
the hip, knee and ankle of the left leg. At the right the pressures in both muscles of each
corresponding joint and the control value deltap is depicted. The definition of the angles can
be found in this figure.
Range of motion for the joints
The graphs show clearly the control strategy of keeping the mean pressure constant, which in
this case is set at a value of 2.5 bar. One can have an understanding of the antagonistic
working principle of the muscles when looking at the pressures for the knee between 10 and
50 seconds. During this time period the left leg switches function from swing leg to stance leg.
From 10 to 30 seconds pressure 2, in the flexor muscle, must be higher than pressure 1, in the
extensor muscle, to lift the weight of the lower left leg while from 30 to 50 seconds the
pressure in the extensor muscle must be higher to hold the weight of the robot.
The results of this first control implementation with basic PID techniques show already
satisfactory behaviour. Following step will be the implementation of a dynamic control
scheme to induce faster and smoother motion for which the local feedback controller has to be
redesigned with nonlinear control techniques.
