Trajectory Optimization with Implicit Hard Contacts
I’m happy to announce a new paper
Trajectory Optimization with Implicit Hard Contacts.
Jan Carius, René Ranftl, Vladlen Koltun, and Marco Hutter
IEEE Robotics and Automation Letters (RA-L), vol. 3, no. 4, pp. 3316-3323, 2018
This work was supported by Intel Labs, the Swiss National Science Foundation (SNF) through project 166232 and NCCR Robotics.
Here is the abstract of the publication.
We present a contact invariant trajectory optimization formulation to synthesize motions for legged robotic systems. The method is capable of finding optimal trajectories subject to whole-body dynamics with hard contacts. Contact switches are determined automatically. We make use of concepts from bilevel optimization to find gradients of the system dynamics including the constraint forces and subsequently solve the optimal control problem with the unconstrained iLQR algorithm. Our formulation achieves fast computation times and scales well with the number of contact points. The physical correctness of the produced trajectories is verified through experiments in simulation and on real hardware. We showcase our method on a single-legged hopper for which jumping and forward hopping motions are synthesized with an arbitrary number of contact switches. The jumping trajectories can be tracked on the robot and allow it to safely liftoff and land.
Together with my colleague Vassilios Tsounis, we presented a brief overview on our method at the Dynamic Walking Conference 2018.
A preprint of the full paper PDF is available below, and the published version can be found under http://doi.org/10.1109/LRA.2018.2852785.