  To traverse complex three-dimensional terrainwith large obstacles, animals
and robots must transition across different modes. However, the most
mechanistic understanding of terrestrial locomotion concerns how to generate
and stabilize near-steady-state, single-mode locomotion (e.g. walk, run). We
know little about how to use physical interaction to make robust locomotor
transitions. Here, we review our progress towards filling this gap by
discovering terradynamic principles of multi-legged locomotor transitions,
using simplified model systems representing distinct challenges in complex
three-dimensional terrain. Remarkably, general physical principles emerge
across diverse model systems, by modelling locomotor-terrain interaction using
a potential energy landscape approach. The animal and robots' stereotyped
locomotor modes are constrained by physical interaction. Locomotor transitions
are stochastic, destabilizing, barrier-crossing transitions on the landscape.
They can be induced by feed-forward self-propulsion and are facilitated by
feedbackcontrolled active adjustment. General physical principles and
strategies from our systematic studies already advanced robot performance in
simple model systems. Efforts remain to better understand the intelligence
aspect of locomotor transitions and how to compose larger-scale potential
energy landscapes of complex three-dimensional terrains from simple landscapes
of abstracted challenges. This will elucidate how the neuromechanical control
system mediates physical interaction to generate multi-pathway locomotor
transitions and lead to advancements in biology, physics, robotics and
dynamical systems theory.
