Efficient automatic design of robots.

Robots are notoriously difficult to design because of complex interdependencies between their physical structure, sensory and motor layouts, and behavior. Despite this, almost every detail of every robot built to date has been manually determined by a human designer after several months or years of iterative ideation, prototyping, and testing. Inspired by evolutionary design in nature, the automated design of robots using evolutionary algorithms has been attempted for two decades, but it too remains inefficient: days of supercomputing are required to design robots in simulation that, when manufactured, exhibit desired behavior.

Biological Robots: Perspectives on an Emerging Interdisciplinary Field.

Advances in science and engineering often reveal the limitations of classical approaches initially used to understand, predict, and control phenomena. With progress, conceptual categories must often be re-evaluated to better track recently discovered invariants across disciplines. It is essential to refine frameworks and resolve conflicting boundaries between disciplines such that they better facilitate, not restrict, experimental approaches and capabilities.

Kinematic self-replication in reconfigurable organisms.

All living systems perpetuate themselves via growth in or on the body, followed by splitting, budding, or birth. We find that synthetic multicellular assemblies can also replicate kinematically by moving and compressing dissociated cells in their environment into functional self-copies. This form of perpetuation, previously unseen in any organism, arises spontaneously over days rather than evolving over millennia.

A cellular platform for the development of synthetic living machines.

Robot swarms have, to date, been constructed from artificial materials. Motile biological constructs have been created from muscle cells grown on precisely shaped scaffolds. However, the exploitation of emergent self-organization and functional plasticity into a self-directed living machine has remained a major challenge.

Shape Changing Robots: Bioinspiration, Simulation, and Physical Realization.

One of the key differentiators between biological and artificial systems is the dynamic plasticity of living tissues, enabling adaptation to different environmental conditions, tasks, or damage by reconfiguring physical structure and behavioral control policies. Lack of dynamic plasticity is a significant limitation for artificial systems that must robustly operate in the natural world. Recently, researchers have begun to leverage insights from regenerating and metamorphosing organisms, designing robots capable of editing their own structure to more efficiently perform tasks under changing demands and creating new algorithms to control these changing anatomies.

A scalable pipeline for designing reconfigurable organisms.

Living systems are more robust, diverse, complex, and supportive of human life than any technology yet created. However, our ability to create novel lifeforms is currently limited to varying existing organisms or bioengineering organoids in vitro. Here we show a scalable pipeline for creating functional novel lifeforms: AI methods automatically design diverse candidate lifeforms in silico to perform some desired function, and transferable designs are then created using a cell-based construction toolkit to realize living systems with the predicted behaviors.

Publisher Correction: How morphological development can guide evolution.

A correction to this article has been published and is linked from the HTML and PDF versions of this paper. The error has been fixed in the paper.

How morphological development can guide evolution.

Organisms result from adaptive processes interacting across different time scales. One such interaction is that between development and evolution. Models have shown that development sweeps over several traits in a single agent, sometimes exposing promising static traits.