Characterization and Correlation of Robotic Snake Scale Friction and Locomotion Speed

Umit Sen; Andri Mahegan; Gina Olson

cs.ROMar 4, 2026

Characterization and Correlation of Robotic Snake Scale Friction and Locomotion Speed

Authors: Umit Sen, Andri Mahegan, Gina Olson

Organizations: Department of Mechanical and Industrial Engineering, University of Massachusetts, Amherst, MA, USA.

Abstract

Snake robots are inspired by the ability of biological snakes to move over rock, grass, leaves, soil, up trees, along pavement and more. Their ability to move in multiple distinct environments is due to their legless locomotion strategy, which combines distinct gaits with a skin that exhibits frictional anisotropy. Designing soft robotic snakes with similar capabilities requires an understanding of how this underlying frictional anisotropy should be created in engineered systems, and how variances in the frictional anisotropy ratio affect locomotion speed and direction on different surfaces. While forward and backward frictional ratios have been characterized for previous scale designs, lateral friction and the associated ratios are often overlooked. In this paper, our contributions include: (i) the development of a novel articulated pseudo-skin design that is modular, easy to construct and has removable or replaceable scales; (ii) experimental measurement of the frictional characteristics of otherwise-identical scales at varying angles of attack (15°, 25°, 35°, 45°) on different surfaces of interest (grass, bark, smooth surface, carpet);(iii) separate measurements of locomotion speed for each angle and surface. Consequently, while we observed some consistent trends between frictional coefficients and scale angle, aligning with literature and intuition, we were not able to consistently identify expected correlations between frictional ratios and locomotion speed. We conclude that either frictional ratios alone are not sufficient to predict the observed speed of a snake robot, or that specific measurement approaches are required to accurately capture these ratios.

Figures & tables

Fig. 1 : The snake robot ((a) top view; (b) side view; (c) scales) used herein has an articulated backbone and is actuated by air-driven McKibbens. The modular scale system is attached to the ribs extending from each vertebra.

Fig. 2 : Vertebra, ribs, and scale structure forms one segment of the robot (a). Primary, secondary, and tertiary units assembled as one scale structure, and multiple scale structures connected through interlocking mechanism (b). Right-side actuation, neutral (no-actuation), left-side actuation scenarios and air circulation scheme inside actuators (c). Assembly details (d).

Fig. 3 : Capping procedure for McKibben actuators: the cap is bonded to the sheath using a 2-part resin, requiring a mold to both contain the resin and protect the sheath. The sheath is inserted through the mold, and then the cap is inserted, before pulling the assembly down into the occlusion mold. Resin is then added and left to cure prior to demolding.

Fig. 4 : Experimental test setups for measuring (a) forward and backward, and (b) lateral friction. The displacement was transmitted to the robot via a pulley mechanism, with reaction forces recorded using a 100 N load cell.

Fig. 5 : Boxplots illustrate $\mu_{f}$ (red), $\mu_{b}$ (orange), and $\mu_{l}$ (blue) distributions for each scale angle (15 ∘ , 25 ∘ , 35 ∘ , 45 ∘ ) - surface (carpet, bark, smooth surface, grass) pair.

Fig. 6 : Velocity, speed, and friction ratio (top to bottom) values displayed for each scale angle-surface pair. Scale angles of 15°, 25°, 35°, and 45° are depicted in red, green, blue, and black, respectively. The metrics $\mathbf{v}_{x}$ , $\mathbf{v}_{y}$ , and $v$ are denoted by circles, triangles, and diamonds, while friction ratios $\mu_{b/f}$ and $\mu_{l/f}$ are shown as squares and left-pointing triangles.

Fig. 7 : Snapshots of locomotion test on bark surface when $\theta=25$ ° at t = 0, t = 60, t = 90, and t = 150 seconds.

Robot Locomotion

Robot locomotion studies how robots move efficiently and reliably across varied terrains, environments, and movement modes.

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Sep 18, 2026J/K move · Enter open · S save

When to Waddle: A Comparative Study of Bipedal Torso-Stabilization on Low-Friction Surfaces

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Humanoid Robot Locomotion Energy-Efficient Robot Locomotion Robot Locomotion

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Low-friction surfaces challenge bipedal locomotion by limiting the contact forces available during stepping. Inspired by penguin waddling, we investigate how lateral torso motion and center of mass (COM) placement affect locomotion as surface friction changes. Using a five-actuator biped, we compare an upright-gait strategy with a penguin-inspired torso-over-stance-leg strategy across multiple COM placements in simulation and hardware. In the 3-D simulator MuJoCo, we sweep through sinusoidal leg and hip actuation parameters across four friction coefficients mu = 0.1, 0.3, 0.5, 0.7. In simulation, torso-over-stance-leg motion produces more successful controllers and higher forward speeds at low friction, with the highest speed occurring for the high-COM configuration. Hardware experiments show the same low-friction speed trend: at mu=0.12, torso-over-stance-leg motion increases forward speed and reduces cost of transport at both tested COM ratios, and the higher COM also improves both measures. The high-COM penguin configuration is the fastest and most energy efficient while maintaining low sideways foot motion. At mu=0.45, the COM trend reverses: the lower-COM configurations are faster and more energy efficient, while gait strategy has little effect on forward speed but still changes sideways foot motion. These results show that the effects of lateral torso motion and COM placement depend on the available friction, and that forward speed, energy use, and slip-related foot motion can be modulated with a penguin-inspired torso motion on hardware.

Abstract

Robot Locomotion

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