The synchronized holonomic model: A framework for efficient generation of motion
We present a simple and efficient mathematical framework suitable for generating motion in the context of a variety of robotic motion tasks ranging from low-level motor control up to high-level locomotion planning. Our concept is based on a one-dimensional second-order model that allows analytic computation of its inverse dynamics while respecting physical constraints. This makes it a particularly useful tool for tasks that are expressed only as a start and goal state, such as animation key frames or way points in path planning. By means of time synchronization, the model extends easily to an arbitrary number of dimensions in a way that the target is reached in all dimensions at the same time. The framework excels in terms of execution time, which lies in the microsecond range even for high-dimensional trajectory generation tasks. We demonstrate our method in two different settings — full-body trajectory generation and path planning — and show its benefits in comparison with current state-of-the-art algorithms.