Building a Roaming Dinosaur: Why is Policy Learning Not Used ?

Dubai is going to host a Jurassic Park. It is about time: the current display of Animatronics are very much underwhelming and certainly do not yield the type of magic moment as displayed by Laura Dern's face in Jurassic Park. Yet, all over the world, kids and families line up to pay from $10 to $100 for the privilege of being wowed. The most interesting feature of the Dubai 'Resteless Planet' undertaking will be the claimed ability for the dinosaurs to be roaming. This is no small feat as none of the current animatronics are able to do that. I have a keen interest in this as you probably have noticed from the different entries on muscles, scaling and various autonomous robotics undertaking.

So over the years, I have kept an eye on the current understanding of dinosaur gait. Examples on the web can be found here and here. A sentence seems to be pretty much a good summary:

When the American Museum of Natural History wanted to create a digital walking Tyrannosaurus rex for a new dinosaur exhibit, it turned to dinosaur locomotion experts John Hutchinson and Stephen Gatesy for guidance.

The pair found the process humbling.

With powerful computers and sophisticated modeling software, animators can take a pile of digital bones and move them in any way they want. This part is easy; but choosing the most likely motion from the myriad of possibilities proved difficult......

The researchers think that one way to narrow down the possibilities of dinosaur movement is to use more rigorous physical constraints in computer models. These constraints fall into two broad categories: kinematic (motion-based) and kinetic (force-based). One simple kinematic constraint, for example, is that the ankle and knee cannot bend backwards.

So in short, it is one thing to know the skeleton, it is another one to devise how the movement goes. Yet, the current methods devised to figure gait are relying on not so sophisticated methods. As it turns out, we have a similar problem in robotics and machine learning. Because robots are becoming increasingly complex, there needs to be new methods of collecting data and summarizing them in what are called 'policies'. New methods are able to learn behavior for robots even though they have many degrees of freedom though some type of supervised learning. Some of the techniques include Non-Negative Matrix Factorization (NMF), diffusion processes and some of the techniques we tried in our unsuccesful attempt in DARPA's race in the future.

[ Update: a dinosaur finding showing preserved organic parts shows us that basing our intuition on just bones is not enough. It looks as though dinosaurs may have been much larger. Ona different note, it is one thing to model human behavior (and by extension dinosaur behavior) using Differential equations,but the problem you are trying to solve is 'given a certain behavior, how can it fit the model set forth by the differential equations?'. This is what is called an inverse problem and while a set of differential equations may give you a sentiment that you are modeling everything right, they generally are simplification of the real joint behavior and their interaction with the environment (soil,...). In short, to give a sense of realness, you have to go beyond a description with differential equations alone, for these reasons alone. For this reason, building a real roaming dinosaur need the type of undertaking mentioned above in this entry ]