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Showing 1–9 of 9 results
Advanced filters: Author: Josh Bongard Clear advanced filters

  • Combining soft robotics with neuromorphic engineering is a promising approach in embodied intelligence. Giulia d’Angelo et al. contribute to progress in this field by developing a framework for benchmarking neuromorphic controllers on soft robotic platforms.

    • Giulia D’Angelo
    • Jens E. Pedersen
    • Elisa Donati
    Reviews
    Nature Machine Intelligence
    Volume: 8, P: 300-312

  • Inspired by many examples in nature where organisms change shape to concur environments, there is much interest in designing robots that are capable of shape change. Shah et al. demonstrate a method for automatically discovering shape and gait changes for soft robots that can adapt to different terrains.

    • Dylan S. Shah
    • Joshua P. Powers
    • Rebecca Kramer-Bottiglio
    Research
    Nature Machine Intelligence
    Volume: 3, P: 51-59

  • The concept of 'Embodied Energy'—in which the components of a robot or device both store energy and provide a mechanical or structural function—is put forward, along with specific robot-design principles.

    • Cameron A. Aubin
    • Benjamin Gorissen
    • Robert F. Shepherd
    Reviews
    Nature
    Volume: 602, P: 393-402

  • To meet the physical demands of a new environment, organisms evolve morphological and behavioural adaptations that specialize their locomotor performance to that niche. This Perspective discusses how robots can emulate — and perhaps even exceed — biological levels of adaptability through shape-morphing mechanisms and complementary control strategies to achieve compressed, rapid and reversible ‘evolution on demand’.

    • Robert Baines
    • Frank Fish
    • Rebecca Kramer-Bottiglio
    Reviews
    Nature Reviews Materials
    Volume: 9, P: 822-835

  • Understanding the behaviour of the machines powered by artificial intelligence that increasingly mediate our social, cultural, economic and political interactions is essential to our ability to control the actions of these intelligent machines, reap their benefits and minimize their harms.

    • Iyad Rahwan
    • Manuel Cebrian
    • Michael Wellman
    Reviews
    Nature
    Volume: 568, P: 477-486

  • It is an outstanding challenge to develop intelligent machines that can learn continually from interactions with their environment, throughout their lifetime. Kudithipudi et al. review neuronal and non-neuronal processes in organisms that address this challenge and discuss pathways to developing biologically inspired approaches for lifelong learning machines.

    • Dhireesha Kudithipudi
    • Mario Aguilar-Simon
    • Hava Siegelmann
    Reviews
    Nature Machine Intelligence
    Volume: 4, P: 196-210