Robust self-propulsion in sand using simply controlled vibrating cubes
Much of the Earth and many surfaces of extraterrestrial bodies are composed of non-cohesive particulate matter. Locomoting on such granular terrain is challenging for common robotic devices, either wheeled or legged. In this work, we discover a robust alternative locomotion mechanism on granular media-generating movement via self-vibration. To demonstrate the effectiveness of this locomotion mechanism, we develop a cube-shaped robot with an embedded vibratory motor and conduct systematic experiments on granular terrains of various particle properties and slopes. We investigate how locomotion changes as a function of vibration frequency/intensity on such granular terrains. Compared to hard surfaces, we find such a vibratory locomotion mechanism enables the robot to move faster, and more stably on granular surfaces, facilitated by the interaction between the body and surrounding grains. We develop a numerical simulation of a vibrating single cube on granular media, enabling us to justify our hypothesis that the cube achieves locomotion through the oscillations excited at a distance from the cube's center of mass. The simplicity in structural design and controls of this robotic system indicates that vibratory locomotion can be a valuable alternative way to produce robust locomotion on granular terrains. We further demonstrate that such cube-shaped robots can be used as modular units for vibratory robots with capabilities of maneuverable forward and turning motions, showing potential practical scenarios for robotic systems.
Authors
- Deniz Kerimoğlu (ORCID: https://orcid.org/0000-0002-1193-4680)
- Bangyuan Liu
- Frank L. Hammond (ORCID: https://orcid.org/0000-0002-1634-7573)
- Tianyu Wang (ORCID: https://orcid.org/0000-0001-9012-838X)
- Velin Kojouharov
- Daniel I. Goldman (ORCID: https://orcid.org/0000-0002-6954-9857)
Institutions
- Georgia Institute of Technology (US)
- The Wallace H. Coulter Department of Biomedical Engineering (US)
Publication Details
- Journal
- Frontiers in Robotics and AI
- Published
- 2024-08-30
- DOI
- https://doi.org/10.3389/frobt.2024.1298676
- Citations
- 5
- Primary Topic
- Modular Robots and Swarm Intelligence
- Type
- article
- Field-Weighted Citation Impact
- 1.06
Funders
- National Science Foundation
- Army Research Office