Rearranging the Environment to Maximize Energy with a Robotic Circuit Drawing
This addresses the challenge of long-term autonomy for robots in uncertain environments, such as homes or other planets, by allowing them to create their own power sources, though it is incremental as it builds on existing manipulation methods.
The paper tackles the problem of enabling robots to autonomously acquire power by drawing circuits with conductive ink and rearranging their environment to maximize energy from a power source, achieving results where the robot learns to connect a power source with minimal ink and rearrange objects to avoid obstacles in both simulation and real-world settings.
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.