I recently published a new paper
Trajectory Optimization for Legged Robots with Slipping Motions.
Jan Carius, René Ranftl, Vladlen Koltun, and Marco Hutter
IEEE Robotics and Automation Letters (RA-L), vol. 4, no. 3, pp. 3013 - 3020, 2019
This work was supported by Intel Labs, the Swiss National Science Foundation (SNF) through project 166232 and the National Centre of Competence in Research Robotics(NCCR Robotics), and the European Union’s Horizon 2020 research and innovation programme under grant agreement No 780883. This work has been conducted as part of ANYmal Research, a community to advance legged robotics.
Here is the abstract of the publication.
The dynamics of legged systems are characterized by under-actuation, instability, and contact state switching. We present a trajectory optimization method for generating physically consistent motions under these conditions. By integrating a custom solver for hard contact forces in the system dynamics model, the optimal control algorithm has the authority to freely transition between open, closed, and sliding contact states along the trajectory. Our method can discover stepping motions without a predefined contact schedule. Moreover, the optimizer makes use of slipping contacts if a no-slip condition is too restrictive for the task at hand. Additionally, we show that new behaviors like skating over slippery surfaces emerge automatically, which would not be possible with classical methods that assume stationary contact points. Experiments in simulation and on hardware confirm the physical consistency of the generated trajectories. Our solver achieves iteration rates of 40 Hz for a 1 s horizon and is therefore fast enough to run in a receding horizon setting.
A preprint of the full paper PDF is available below, and the published version can be found under https://doi.org/10.1109/LRA.2019.2923967.