A lot of the cool books and papers on AI I’ve read have focused on the role of the hippocampus and neocortex in human cognition. This seems right since the hippocampus is key in initial short term memory formation and the neocortex in long term memory, as well as the latter’s famous role in thought, language and other areas considered essential to being human. But it seems to me an area of the brain often overlooked is the cerebellum, especially when trying to produce a software/hardware architecture that can enable smooth movements.
The cerebellum appears to act like a sort of differential correction subsystem, like some elaborate phased locked loop or comparator circuit that continually and unconsciously makes corrections to signals emanating from the neocortex that direct the body. Damage or disease to this area typically results in jerky, stiff or wildly over-corrected movements: symptoms not unfamiliar to embedded programmers attempting to make servos smoothly operate a robot’s arms or pseudo hands. Similarly, walking robots still appear unnatural or wooden and always limited. I don’t think this is for lack of effort on the part of designers. Usually progress is a function of faster processors/more efficient programming or an improved solution to the differential equations governing the dynamics of the system.
Yet it’s obvious insects and animals are not solving high order math problems while traveling around. There is normally no effort required for them to move seemingly beyond picking a direction. This is a characteristic of all living creatures irrespective of whether they have fins, legs or wings. Humans from toddler age and on are ambulatory without conscious thought, having committed to ‘muscle memory’ in the cerebellum the motor learning skills required for smooth walking.
There are other more basic problems facing a designer attempting to emulate creature movements, not the least of which is finding a suitable power supply that can sustain a skeletal framework hosting the gear required for the equivalent of legs, sockets, hoofs etc. Still, the purely mechanical issues I expect will be solved with technology that exists or is nascent. An unsolved problem is the real-time computational control of such systems as well as how to direct smooth, fine motor movement for any situation. Given the decades of work that have preceded with still no good solution at hand a different paradigm for programming the system may be required to make progress. An exemplary system to mimic in my mind is the self-organizing, neuron architecture of the cerebellum; its hard to argue with such amazing success.
Not unlike training an infant first to roll over or learn to crawl one could expect some sort of feedback system with a cerebellum inspired governor to ‘teach’ machines to ‘walk’. The payoff is that such systems can be copied, not unlike the genetic wiring that enables a colt to stumble to its feet on its first day after being born. This magic seems to me yet another in a long train of instances where self-organizing systems, like the neocerebellum and its relationship to the neocortex, are a likely prerequisite to move from gawky, barely stumbling robots we’ve all seen on YouTube to free flowing systems that can begin to move a fraction as well as a lizard. I mean to take nothing anything away from engineers working on making robots move using traditional approaches, it’s an incredibly difficult problem and the widespread use of robotic arms for manufacturing and similar jobs with a finite locus of movement are a testament to their success. They have only my respect and I wish anyone taking on this challenge in their career or spare time the best. I certainly could be wrong on my fascination with self-organizing systems as a key component of a ubiquitous solution, but that’s my belief and pursuit.
What I am looking forward to is the day when we’ll finally acheive smooth walking systems that can help the elderly and sick folks with simple physical tasks through a voice command or save a life after a fire or disaster by scampering over debris too difficult for rolling robots. There’s much to be done in order to emulate biological movement; a good starting place in my opinion is with the cerebellum and how it controls so much of the body automatically and with such incredible precision.