In this work we present a trajectory Optimization framework for whole-body
motion planning through contacts. We demonstrate how the proposed approach can
be applied to automatically discover different gaits and dynamic motions on a
quadruped robot. In contrast to most previous methods, we do not pre-specify
contact switches, timings, points or gait patterns, but they are a direct
outcome of the optimization. Furthermore, we optimize over the entire dynamics
of the robot, which enables the optimizer to fully leverage the capabilities of
the robot. To illustrate the spectrum of achievable motions, here we show eight
different tasks, which would require very different control structures when
solved with state-of-the-art methods. Using our trajectory Optimization
approach, we are solving each task with a simple, high level cost function and
without any changes in the control structure. Furthermore, we fully integrated
our approach with the robot's control and estimation framework such that
optimization can be run online. By demonstrating a rough manipulation task with
multiple dynamic contact switches, we exemplarily show how optimized
trajectories and control inputs can be directly applied to hardware.Comment: Video: https://youtu.be/sILuqJBsyK
