# The biohybrid autonomous robots (BAR): a feasibility of implementation

## TL;DR

This paper explores the feasibility of using biohybrid systems in autonomous robots to improve energy efficiency compared to traditional battery-powered robots.

## Contribution

The study introduces a novel approach using biohybrid systems and demonstrates their potential energy efficiency advantage over conventional robots.

## Key findings

- Biohybrid Autonomous Robots (BAR) could be up to 5.1 times more efficient in energy transport compared to conventional robots.
- A model is proposed to determine when BAR would be rationally applicable based on basal metabolism.
- BAR is positioned as a promising solution among other energy autonomy approaches like GPAR and FCAR.

## Abstract

Limited battery capacity poses a challenge for autonomous robots. We believe that instead of relying solely on electric motors and batteries, basically Conventional Autonomous Robots (CAR), one way to address this challenge may be to develop Biohybrid Autonomous Robots (BAR), based on current achievements of the field of biohybrid robotics. The BAR approach is based on the facts that fat store high amount of energy, that biological muscles generate decent force per unit of cross-sectional area and that biological muscles have capability for regeneration and adaptation compared to electric motors. To reach conclusions about the feasibility of BAR, this study uses data from the fields of muscle energetics, robotics, engineering, physiology, biomechanics and others to perform analysis and interdisciplinary calculations. Our calculations show that the BAR approach is up to 5.1 times more efficient in terms of the mass of energy substrate to useful energy transported than the Conventional Autonomous Robots (CAR) with mass-produced batteries in an ideal scenario. The study also presents the model for determining the point of the rational use of the BAR, taking into the account basal metabolism of living systems. The results of this study provide a preliminary basis for further research of the BAR, putting it into the context of the other possible solutions for energy autonomy problem: Generator-Powered Autonomous Robots (GPAR) and Fuell-Cell Autonomous Robots (FCAR).