Johanna T Schultz

Locomotion is a key aspect associated with ecologically relevant tasks for many organisms, therefore, survival often depends on their ability to perform well at these tasks. Despite this significance, we have little idea how different performance tasks are weighted when increased performance in one task comes at the cost of decreased performance in another. Additionally, the ability for natural systems to become optimized to perform a specific task can be limited by structural, historic or functional constraints. Climbing lizards provide a good example of these constraints as climbing ability likely requires the optimization of tasks which may conflict with one another such as increasing speed, avoiding falls and reducing the cost of transport (COT). Understanding how modifications to the lizard bauplan can influence these tasks may allow us to understand the relative weighting of different performance objectives among species. Here, we reconstruct multiple performance landscapes of climbing locomotion using a 10 d.f. robot based upon the lizard bauplan, including an actuated spine, shoulders and feet, the latter which interlock with the surface via claws. This design allows us to independently vary speed, foot angles and range of motion (ROM), while simultaneously collecting data on climbed distance, stability and efficiency. We first demonstrate a trade-off between speed and stability, with high speeds resulting in decreased stability and low speeds an increased COT. By varying foot orientation of fore- and hindfeet independently, we found geckos converge on a narrow optimum of foot angles (fore 20°, hind 100°) for both speed and stability, but avoid a secondary wider optimum (fore -20°, hind -50°) highlighting a possible constraint. Modifying the spine and limb ROM revealed a gradient in performance. Evolutionary modifications in movement among extant species over time appear to follow this gradient towards areas which promote speed and efficiency.