Growing Fine-Grained Multicellular Robots

Doursat, R and Sánchez, C (2014) Growing Fine-Grained Multicellular Robots. Soft Robotics, 1. ISSN 2169-5172

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Abstract

Engineers are torn between an attitude of strong design and dreams of autonomous devices. They want full mastery of their artifacts while wishing these were much more adaptive or “intelligent.” Today, while we must still spoon-feed (program, repair, upgrade) our most sophisticated computer and robotic systems, insatiable demand for novelty has created an escalation in system size and complexity. In this context, the tradition of rigid top-down planning and implementation in every detail has become unsustainable. Natural complex systems, large sets of elements interacting locally and producing nontrivial collective behaviors, offer a powerful alternative and source of innovative ideas. Going beyond metaheuristic disciplines based on “neurons” (machine learning), “genes” (genetic algorithms), or “ants” (ant colony optimization), this article highlights a new avenue of bioinspired engineering that simulates the growth of fine-grained multicellular organisms. It presents a brief overview of morphogenetic engineering and one of its instances, embryomorphic engineering, which are two fields that explore the decentralized self-organization of artificial complex morphologies and behaviors. MapDevo3D, an embryomorphic engineering model of developmental animats in a 3D virtual physics world, is described in more detail. Bodies are composed of several hundreds of cells, giving them a quasi-continuous texture close to the tenets of “soft robotics.” Motion results from local muscle twitching without a central nervous system. Altogether, the challenge is not to build a system directly but find the rules that its components must follow to build it for us.