Let’s say that you took care of all of that mechanical engineering, using the MICE principle, and now you are looking at your handiwork. Now what? You’ve got to build another flipper, for the other side of … an underwater robot. Yikes! You’ve put the robot part on hold while you earned your PhD designing and building the biomimetic flipper. Okay, no big deal. Now you build a robot to anchor the two sea lion flippers and hold the batteries to power the motors. Done? Not quite. Now you need to design and test the software to control and coordinate the twenty motors. Twenty degrees of freedom aren’t too much of a problem because you are just getting the flipper to flap down and back and then recover to the position needed to repeat the motion. Your software controller works great in the lab, in air, on the bench. But then you put the robot in the water. The moment it starts to flap and move, the long flippers undergo drag that tends to push back and bend the flippers. You realize that if the flippers are going to maintain a specific shape and change shape in a way that you specify during the stroke, you’ve got to have sensors at each joint.
Maybe this is why animals have proprioception, the internal positional sensory system that allows you to touch your nose with your index finger with your eyes closed. Thinking with your MICE hat on, you curse yourself for not making the flippers complicated enough from the get-go! You rip open the flippers and put potentiometers at each joint, and wire those twenty sensors to the computer controlling the motion of the flipper. You build a new software module that takes the sensor input as feedback to the motors. Now, when you tell the flipper to have a certain shape and position, you are certain it will do so.
Back at the pool, you put your system, now dubbed SeaLioTron, into the water and are overjoyed to see it swim slowly with a symmetrical and controlled motion of the flippers. Great. Now let’s get SeaLioTron to turn. You’d thought about that aspect of control, but because you were working on the flippers, you saved that problem for later. When you revisit the videotapes that you’ve got of real sea lions, you notice that they have tremendous turning agility because they can bend, using their bodies as big rudders in the water. Because having a flexible body was not part of your project and raises all kinds of issues with the internal payload of batteries, motors, and computers, you either (a) call the SeaLioTron project a success and consider it done, (b) figure out how to turn SeaLioTron with flexible flippers and a rigid body, or (c) start a whole new project to build a flexible body-as-rudder.
Although I’ve made up this MICE counterexample, the idea that someone might tackle SeaLioTron is not complete fantasy. You would certainly encounter the problems that I’ve outlined and you’d probably, along the way, generate some really clever solutions that I can’t fathom. And all that difficulty might be worth it: the SeaLioTron would easily produce a handful of PhD projects and, likely, a bunch of cool patents for flexible, actuated propulsors and multijoint neural controllers. You might even get NSF to fund the project. So what am I doing? I bring up SeaLioTron as an example of the MICE principle to make the following point about Maddie’s one-degree-of-freedom Nektors: yes, Maddie’s flippers are inaccurate as models of sea lion or sea turtle or plesiosaur flippers, but at the time that Maddie was built (2003 to 2004), they were the most bio-realistic flappers around (generating thrust by flapping with a flexible foil), and they are relatively easy to actuate and control. With the KISS principle, you do the simple stuff first. And the simple stuff turns out to be plenty complicated.
So back to the big question: why do all living aquatic tetrapods favor two powered flippers over four, when four seems to be the key to better performance? Even though ETs make answering the question easier than if we tried to explore the morphospace of flippers and the likely evolutionary processes, we still need to proceed with the extreme prejudice that a physically embodied robot will produce results that we failed to anticipate.
Let’s first define our “simple,” two-dimensional morphospace. The traits that we could vary in Madeleine were the number of flippers used and the pattern of flipper use. In the first set of experiments, however, we only changed and investigated the pattern of use in what we might call the neural-control space (Figure 7.7). Although that simplifies matters, the patterns are still awfully complex, a result of the fact that each of Maddie’s flippers is independently controlled.
When one flipper reaches its most downward position, another flipper may be reaching its uppermost position. The difference in the time that two flippers take to reach the same position is called “phase.” If two flippers are in phase, what we’ll label as 0 degrees out of 360, then they are flapping together, perfectly synchronizing their swimming. If two flippers are out of phase, the easiest pattern to see is a phase of 180 degrees, like drumming a steady beat by alternating your left and right hands striking the table top. Unfortunately, there are many other ways to be out of phase, so then the combinatorial world of our experiment explodes. If you think about testing every ten degrees of phase, a crude resolution for this dimension that contains 360 degrees, that gives you thirty-six different conditions to go along with four flippers or—ouch!—more than a million total combinations (Figure 7.7, bottom). Cruel irony. Even with just two dimensions, number of flippers and the phase between them, we can’t exhaustively explore this “simple” neural control space.
FIGURE 7.7. Two flippers or four? (facing page) Terrestrial tetrapods—mammals, reptiles, and birds—have repeatedly spawned lineages that returned to the sea. These aquatic tetrapods evolved in different ways, improving their submerged swimming performance over generational time by shifting from a terrestrial pattern of back-and-forth limb movement to an up-and-down or side-to-side motion. Those changes in motion are associated with a change from drag-based paddling to lift-based flapping. Living flappers, like sea lions of the genus Zalophusor the seals of the genus Phoca, use only two flippers for propulsion. In contrast, extinct flappers like short-necked plesiosaurs of the genus Kronosaurusor long-necked plesiosaurs of the genus Plesiosaurus have four nearly identical flippers that appear, from their wing-like shape and anatomical connections to the body, to have been used in lift-based propulsion. How swimming performance is connected to the motion of the flippers quickly becomes complicated, with millions of possible flipper patterns in four-flippered swimmers. This figure is inspired by the research of Frank Fish.
FIGURE 7.8. Experiments with the Evolutionary Trekker, Madeleine. To test the hypothesis that Robot Madeleine should swim faster and with greater acceleration using four flippers rather than two, we ran her through a series of experiments. In this example Madeleine is using her two rear flippers to start from a stop, swim as fast as she can, and then stop as quickly as she can. These images were taken from underwater video that had been analyzed to show Madeleine’s position (point on her bow traced frame by frame to create the path) over the whole experiment. The snorkeler in the water (that’s me, ahem) makes sure that Madeleine is stationary and located at a depth of two meters before the topside experimenters start the experiment.
In the face of this daunting complexity we sought the refuge of the KISS principle once again. In terms of number of flippers, we had three conditions to test: (1) two front flippers, (2) two rear flippers, and (3) all four flippers. Within each of these conditions, we varied the phase in the following ways. With two flippers, they flapped either in-phase (0 degrees) or 180 degrees out of phase. Simple. With four flippers, we borrowed a page from Frank Fish’s evolutionary model and used four patterns of limb movements, called gaits, that are seen in terrestrial tetrapods: (1) pronk (all four in phase), (2) gallop (front in phase, rear in phase, front 180 degrees out of phase with rear), (3) trot (left front in phase with right rear, right front in phase with left rear, those diagonal pairings 180 degrees out of phase with each other), and (4) pace (left in phase, right in phase, left 180 degrees out of phase with the right).