Coevolutionary Robotics

• Authors: Jordan Pollack;Hod Lipson;Pablo Funes;Sevan Ficici;Greg Hornby
• Venue: EH '99 Proceedings of the 1st NASA/DOD workshop on Evolvable Hardware
• Year: 1999

We address the fundamental issue of fully automated design (FAD) and construction of inexpensive robots and their controllers. Rather than seek an intelligent general purpose robot - the humanoid robot, ubiquitous in today's research as the long term goal - we are developing the information technology that can design and fabricate special-purpose mechanisms and controllers to achieve specific short-term objectives. These robots will be constructed from reusable sensors, effectors, and computers held together with materials custom "printed" by rapid prototyping (RP) equipment. By releasing the goal of designing software controllers for EXISTING machines in favor of the automated co-design of software and hardware together, we will be replicating the principles used by biology in the creation of complex groups of animals adapted to specific environments.Programming control software has become so difficult as more degrees of freedom and task goals are added to robots, that the most advanced ones do not get past the stage of teleoperation or choreographed behavior. In other words, they are puppets, not robots. Our primary hypothesis is that the reason current approaches to robotics often fail is because of an underestimation of the complexity of the software design problem. Traditionally, engineers will build a complex robot, complete with powerful motors and sensors, and leave for the control programmers to write a program to make it run. But if we look into nature, we see animal brains of very high complexity, at least as complex as the bodies they inhabit, which have been precisely selected to be controllable. New sensor and effector technology - for example, the micromotor, the optical position sensor, memory wire, FPGA's, biomimetic materials, biologically inspired retinas, and lately, MEMS, despite radical claims, cannot produce the desired breakthroughs. True robot success is task specific, not general purpose, and would be recognizable even if built of old electromechanical components.In nature, the body and brain of a horse are tightly coupled, the fruit of a long series of small mutual adaptations - neither one was first. Today's horse brain was lifted, 99.9% complete, from the animal that preceded it. There is never a situation in which the hardware has no software, or where a growth or mutation - beyond the adaptive ability of a brain - survives. This chicken-egg problem of body-brain development is best understood as a form of co-evolution - agents learning in environments that respond to the agents by creating more challenging and diverse tasks.By using a combination of commercial off-the-shelf (COTS) CAD/CAM simulation software and our own physical simulators constrained to correspond to real physical devices, we have been developing the technology for the coevolution of body and brains: adaptive learning in body simulations, and the migration of "brains" from simpler to more complex simulated bodies until the virtual robot steps into reality using extensions of today's rapid prototyping technology. Finally, the robot's brains must be robust enough to learn how to bridge the transition from virtual to actual reality.