Vojtech Salanský

Pose Consistency KKT-Loss for Weakly Supervised Learning of Robot-Terrain Interaction Model

We address the problem of self-supervised learning for predicting the shape of supporting terrain (i.e. the terrain which will provide rigid support for the robot during its traversal) from sparse input measurements. The learning method exploits two types of ground-truth labels: dense 2.5D maps and