Paper ID: 2411.11192

Robot Metabolism: Towards machines that can grow by consuming other machines

Philippe Martin Wyder, Riyaan Bakhda, Meiqi Zhao, Quinn A. Booth, Matthew E. Modi, Andrew Song, Simon Kang, Jiahao Wu, Priya Patel, Robert T. Kasumi, David Yi, Nihar Niraj Garg, Pranav Jhunjhunwala, Siddharth Bhutoria, Evan H. Tong, Yuhang Hu, Judah Goldfeder, Omer Mustel, Donghan Kim, Hod Lipson

Biological lifeforms can heal, grow, adapt, and reproduce -- abilities essential for sustained survival and development. In contrast, robots today are primarily monolithic machines with limited ability to self-repair, physically develop, or incorporate material from their environments. A key challenge to such physical adaptation has been that while robot minds are rapidly evolving new behaviors through AI, their bodies remain closed systems, unable to systematically integrate new material to grow or heal. We argue that open-ended physical adaptation is only possible when robots are designed using only a small repertoire of simple modules. This allows machines to mechanically adapt by consuming parts from other machines or their surroundings and shedding broken components. We demonstrate this principle using a truss modular robot platform composed of one-dimensional actuated bars. We show how robots in this space can grow bigger, faster, and more capable by consuming materials from their environment and from other robots. We suggest that machine metabolic processes akin to the one demonstrated here will be an essential part of any sustained future robot ecology.

Submitted: Nov 17, 2024