Rearranging the Environment to Maximize Energy with a Robotic Circuit Drawing

TL;DR

This paper introduces a robot that actively rearranges its environment to optimize energy harvesting by drawing conductive circuits, demonstrating effective manipulation and circuit creation in both simulation and real-world scenarios.

Contribution

The work presents a novel robotic system capable of environmental rearrangement and circuit drawing to maximize energy intake, integrating visual manipulation with circuit design.

Findings

Robot learns to rearrange objects to optimize circuit paths

Effective in both simulation and real-world environments

Achieves minimal conductive ink usage for circuit completion

Abstract

Robots with the ability to actively acquire power from surroundings will be greatly beneficial for long-term autonomy and to survive in uncertain environments. In this work, we present a robot capable of drawing circuits with conductive ink while also rearranging the visual world to receive maximum energy from a power source. A range of circuit drawing tasks is designed to simulate real-world scenarios, including avoiding physical obstacles and regions that would discontinue drawn circuits. We adopt the state-of-the-art Transporter networks for pick-and-place manipulation from visual observation. We conduct experiments in both simulation and real-world settings, and our results show that, with a small number of demonstrations, the robot learns to rearrange the placement of objects (removing obstacles and bridging areas unsuitable for drawing) and to connect a power source with a minimum amount of conductive ink. As autonomous robots become more present, in our houses and other planets, our proposed method brings a novel way for machines to keep themselves functional by rearranging their surroundings to create their own electric circuits.