Creating artificial life via evolutionary robotics faces a chicken‑and‑egg problem: learning control is biased by sensors and effectors while building a controllable body requires a pre‑existing brain, and the reality gap further limits buildable structures, leaving a general framework for evolving physical form largely unexplored. The study aims to advance body evolution by applying evolutionary techniques to design Lego‑like structures assembled from parts. Evolution occurs in a custom simulator that computes forces, stresses, and predicts failure for 2‑D Lego structures, producing a schematic assembly that can be physically built. The method successfully evolved multiple distinct entities, demonstrating its functionality.
Creating artificial life forms through evolutionary robotics faces a “chicken and egg” problem: learning to control a complex body is dominated by inductive biases specific to its sensors and effectors, while building a body which is controllable is conditioned on the pre-existence of a brain. The idea of co-evolution of bodies and brains is becoming popular, but little work has been done in evolution of physical structure because of the lack of a general framework for doing it. Evolution of creatures in simulation has been constrained by the “reality gap” which implies that resultant objects are usually not buildable. The work we present takes a step in the problem of body evolution by applying evolutionary techniques to the design of structures assembled out of parts. Evolution takes place in a simulator we designed, which computes forces and stresses and predicts failure for 2-dimensional Lego structures. The final printout of our program is a schematic assembly, which can then be built physically. We demonstrate its functionality in several different evolved entities.
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