Three papers to appear at ICRA 2020 – Check em’ out!

We’re excited to have three lab papers that will be presented at this year’s (virtual) ICRA 2020 conference! Highlights and video links are below.

Check out our new extension to DPC-Net (from ICRA 2018): we show that DPC networks can be trained in a fully self-supervised manner, which improves accuracy and allows for retraining online in new environments!

Got features? Our recent RA-L and ICRA 2020 work demonstrates how to learn maximally-matchable image mappings to dramatically reduce the data needed for experience-based navigation.

Check out our work on a QCQP approach to inverse kinematics for redundant manipulators. We show that this difficult, nonconvex problem often admits a provably tight convex relaxation that can be efficiently solved! Coming soon to MoveIt!