100 citations · 186 across the 13 of their papers we have counts for
4 papers · 1 filter
Deep Visual Reasoning: Learning to Predict Action Sequences for Task and Motion Planning from an Initial Scene Image
Danny Driess, Jung-Su Ha, Marc Toussaint
In this paper, we propose a deep convolutional recurrent neural network that predicts action sequences for task and motion planning (TAMP) from an initial scene image. Typical TAMP…
Robust Task and Motion Planning for Long-Horizon Architectural Construction Planning
Valentin N. Hartmann, Ozgur S. Oguz, Danny Driess +2
Integrating robotic systems in architectural and construction processes is of core interest to increase the efficiency of the building industry. Automated planning for such systems…
Probabilistic Framework for Constrained Manipulations and Task and Motion Planning under Uncertainty
Jung-Su Ha, Danny Driess, Marc Toussaint
Logic-Geometric Programming (LGP) is a powerful motion and manipulation planning framework, which represents hierarchical structure using logic rules that describe discrete aspects…
Describing Physics For Physical Reasoning: Force-based Sequential Manipulation Planning
Marc Toussaint, Jung-Su Ha, Danny Driess
Physical reasoning is a core aspect of intelligence in animals and humans. A central question is what model should be used as a basis for reasoning. Existing work considered models…