Using an air-fluidized bed trackway filled with poppy seeds or glass spheres, researchers at the Georgia Institute of Technology systematically varied the stiffness of the ground to mimic a variety of surfaces, from hard-packed sand to powdery snow. By studying how running lizards, geckos, crabs, and a robot moved through the varying conditions, the researchers found ideal parameters for appendage design.
With a bio-inspired hexapedal robot, Sandbot, as a physical model, the researchers studied average forward speed as a factor of ground penetration resistance – the “stiffness” of the sand – and the frequency of leg movement.
The robot was used to study how the stiffness of a loosely packed surface affects the ability to move across it.
The average speed of the robot declined as the increased air flow through the trackway made the surface weaker. Increasing the leg frequency made the speed decrease more rapidly with increasing air flow.
As part of the research, Georgia Tech graduate students Feifei Qian and Tingnan Zhang used a terradynamics approach based on resistive force theory to perform numerical simulations of robots and animals. The engineers found that their model successfully predicted locomotor performance for low resistance granular states.
Findings from the study may keep future robots from getting stuck in loose soil on a distant planet.
Also: Read more Robotics, Automation & Control tech briefs.