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.

Manoeuvrability, the ability to make rapid changes in direction, is central to animal locomotion. Turning performance may depend on the ability to successfully complete key challenges including; Withstanding additional lateral forces, Maintaining sufficient friction, Lateral leaning during a turn, and Rotating the body to align with the new heading. We filmed high-speed turning in domestic dogs (Canis lupus familiaris) to quantify turning performance and explore how performance varies with body size and shape. Maximal speed decreased with higher angular velocity, greater centripetal acceleration, and smaller turning radii supporting a force limit for wider turns and a friction limit for sharp turns. Variation in turning ability with size was complex, medium sized dogs produced greater centripetal forces, had relatively higher friction coefficients, and generally aligned the body better with the heading compared to smaller and larger bodied dogs. Body shape further had complex pattern, with longer forelimbs but shorter hindlimbs being associated with better turning ability. Further, while more crouched forelimbs were associated with an increased ability to realign the body in the direction of movement, more upright hindlimbs were related to greater centripetal and tangential accelerations. Thus, we demonstrate that these biomechanical challenges to turning can vary not only with changes in speed or turning radius, but also changes in morphology. These results will have significant implications for understanding the link between form and function in locomotory studies, but also in predicting the outcome of predator prey encounters.

The life and death of an organism often depends on its ability to perform well at some ecologically relevant task. Yet despite this significance we have little idea how well species are optimised for competing locomotor tasks. Most scientists generally accept that the ability for natural systems to become optimised for a specific task is limited by structural, historic or functional constraints. Climbing lizards provide a good example of constraint where climbing ability requires the optimization of conflicting tasks such as speed, stability, or efficiency. Here we reconstruct multiple performance landscapes of climbing locomotion using a 10-DOF 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, 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 cost of transport. By varying foot orientation of fore and hindfeet independently, we found geckos converge on a narrow optimum for both speed and stability, but avoid a secondary wider optimum highlighting a possible constraint. Modifying the spine and limb range of movement revealed a gradient in performance. Evolutionary modifications in movement among extant species appear to follow this gradient towards areas which promote speed and efficiency. This approach can give us a better understanding about locomotor optimization, and provide inspiration for industrial and search-and-rescue robots.Significance StatementClimbing requires the optimization of conflicting tasks such as speed, stability, or efficiency, but understanding the relative importance of these competing performance traits is difficult.We used a highly modular bio-inspired climbing robot to reconstruct performance landscapes for climbing lizards. We then compared the performance of extant species onto these and show strong congruence with lizard phenotypes and robotic optima.Using this method we can show why certain phenotypes are not present among extant species, illustrating why these would be potentially mal-adaptive.These principles may be useful to compare with relative rates of evolution along differing evolutionary histories. It also highlights the importance of biological inspiration towards the optimization of industrial climbing robots, which like lizards, must negotiate complex environments.