activity
20202022
most citedLearning Models as Functionals of Signed-Distance Fields for Manipulation Planning

12 citations · 13 across the 3 of their papers we have counts for

collaborators
Showing cs.ROShow all

5 papers · 1 filter

cs.RO2022

FC: Feasibility-Based Control Chain Coordination

Jason Harris, Danny Driess, Marc Toussaint

Hierarchical coordination of controllers often uses symbolic state representations that fully abstract their underlying low-level controllers, treating them as "black boxes" to the…

cs.RO202112 cited

Learning Models as Functionals of Signed-Distance Fields for Manipulation Planning

Danny Driess, Jung-Su Ha, Marc Toussaint +1

This work proposes an optimization-based manipulation planning framework where the objectives are learned functionals of signed-distance fields that represent objects in the scene.…

cs.RO2021

Deep 6-DoF Tracking of Unknown Objects for Reactive Grasping

Marc Tuscher, Julian Hörz, Danny Driess +1

Robotic manipulation of unknown objects is an important field of research. Practical applications occur in many real-world settings where robots need to interact with an unknown en…

cs.RO2020

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…

cs.RO2020

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…