Marc Toussaint

research

∙ 03/06/2023

PaLM-E: An Embodied Multimodal Language Model

Large language models excel at a wide range of complex tasks. However, e...

0 Danny Driess, et al. ∙

research

∙ 03/01/2023

Efficient Path Planning In Manipulation Planning Problems by Actively Reusing Validation Effort

The path planning problems arising in manipulation planning and in task ...

0 Valentin N. Hartmann, et al. ∙

research

∙ 01/31/2023

Control-Tree Optimization: an approach to MPC under discrete Partial Observability

This paper presents a new approach to Model Predictive Control for envir...

0 Camille Phiquepal, et al. ∙

research

∙ 12/06/2022

Solving Rearrangement Puzzles using Path Defragmentation in Factored State Spaces

Rearrangement puzzles are variations of rearrangement problems in which ...

0 S. Bora Bayraktar, et al. ∙

research

∙ 11/28/2022

A Conflict-driven Interface between Symbolic Planning and Nonlinear Constraint Solving

Robotic planning in real-world scenarios typically requires joint optimi...

0 Joaquim Ortiz-Haro, et al. ∙

research

∙ 10/24/2022

Planning Coordinated Human-Robot Motions with Neural Network Full-Body Prediction Models

Numerical optimization has become a popular approach to plan smooth moti...

0 Philipp Kratzer, et al. ∙

research

∙ 10/22/2022

Learning Feasibility of Factored Nonlinear Programs in Robotic Manipulation Planning

A factored Nonlinear Program (Factored-NLP) explicitly models the depend...

0 Joaquim Ortiz-Haro, et al. ∙

research

∙ 06/03/2022

Reinforcement Learning with Neural Radiance Fields

It is a long-standing problem to find effective representations for trai...

0 Danny Driess, et al. ∙

research

∙ 05/17/2022

Effort Informed Roadmaps (EIRM*): Efficient Asymptotically Optimal Multiquery Planning by Actively Reusing Validation Effort

Multiquery planning algorithms find paths between various different star...

0 Valentin N. Hartmann, et al. ∙

research

∙ 05/09/2022

FC^3: Feasibility-Based Control Chain Coordination

Hierarchical coordination of controllers often uses symbolic state repre...

0 Jason Harris, et al. ∙

research

∙ 04/09/2022

Path-Tree Optimization in Partially Observable Environments using Rapidly-Exploring Belief-Space Graphs

Robots often need to solve path planning problems where essential and di...

0 Camille Phiquepal, et al. ∙

research

∙ 03/21/2022

db-A*: Discontinuity-bounded Search for Kinodynamic Mobile Robot Motion Planning

We consider time-optimal motion planning for dynamical systems that are ...

0 Wolfgang Hoenig, et al. ∙

research

∙ 03/10/2022

Sequence-of-Constraints MPC: Reactive Timing-Optimal Control of Sequential Manipulation

Task and Motion Planning has made great progress in solving hard sequent...

0 Marc Toussaint, et al. ∙

research

∙ 03/04/2022

ST-RRT*: Asymptotically-Optimal Bidirectional Motion Planning through Space-Time

We present a motion planner for planning through space-time with dynamic...

0 Francesco Grothe, et al. ∙

research

∙ 03/03/2022

BITKOMO: Combining Sampling and Optimization for Fast Convergence in Optimal Motion Planning

Optimal sampling based motion planning and trajectory optimization are t...

0 Jay Kamat, et al. ∙

research

∙ 02/24/2022

Learning Multi-Object Dynamics with Compositional Neural Radiance Fields

We present a method to learn compositional predictive models from image ...

0 Danny Driess, et al. ∙

research

∙ 12/13/2021

MotionBenchMaker: A Tool to Generate and Benchmark Motion Planning Datasets

Recently, there has been a wealth of development in motion planning for ...

0 Constantinos Chamzas, et al. ∙

research

∙ 12/09/2021

Learning Neural Implicit Functions as Object Representations for Robotic Manipulation

Robotic manipulation planning is the problem of finding a sequence of ro...

0 Jung-Su Ha, et al. ∙

research

∙ 11/15/2021

Learning to Execute: Efficient Learning of Universal Plan-Conditioned Policies in Robotics

Applications of Reinforcement Learning (RL) in robotics are often limite...

0 Ingmar Schubert, et al. ∙

research

∙ 10/28/2021

From Machine Learning to Robotics: Challenges and Opportunities for Embodied Intelligence

Machine learning has long since become a keystone technology, accelerati...

46 Nicholas Roy, et al. ∙

research

∙ 10/07/2021

RHH-LGP: Receding Horizon And Heuristics-Based Logic-Geometric Programming For Task And Motion Planning

Sequential decision-making and motion planning for robotic manipulation ...

0 Cornelius V. Braun, et al. ∙

research

∙ 10/02/2021

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

This work proposes an optimization-based manipulation planning framework...

0 Danny Driess, et al. ∙

research

∙ 08/24/2021

Learning to Arbitrate Human and Robot Control using Disagreement between Sub-Policies

In the context of teleoperation, arbitration refers to deciding how to b...

0 Yoojin Oh, et al. ∙

research

∙ 07/30/2021

Active Learning in Gaussian Process State Space Model

We investigate active learning in Gaussian Process state-space models (G...

0 Hon Sum Alec Yu, et al. ∙

research

∙ 07/14/2021

Plan-Based Relaxed Reward Shaping for Goal-Directed Tasks

In high-dimensional state spaces, the usefulness of Reinforcement Learni...

0 Ingmar Schubert, et al. ∙

research

∙ 07/06/2021

Approximate Topological Optimization using Multi-Mode Estimation for Robot Motion Planning

In this extended abstract, we report on ongoing work towards an approxim...

0 Andreas Orthey, et al. ∙

research

∙ 07/05/2021

GraspME – Grasp Manifold Estimator

In this paper, we introduce a Grasp Manifold Estimator (GraspME) to dete...

0 Janik Hager, et al. ∙

research

∙ 07/05/2021

A System for Traded Control Teleoperation of Manipulation Tasks using Intent Prediction from Hand Gestures

This paper presents a teleoperation system that includes robot perceptio...

0 Yoojin Oh, et al. ∙

research

∙ 06/04/2021

Long-Horizon Multi-Robot Rearrangement Planning for Construction Assembly

Robotic assembly planning has the potential to profoundly change how bui...

0 Valentin Noah Hartmann, et al. ∙

research

∙ 04/16/2021

Hierarchical Human-Motion Prediction and Logic-Geometric Programming for Minimal Interference Human-Robot Tasks

In this paper, we tackle the problem of human-robot coordination in sequ...

0 An T. Le, et al. ∙

research

∙ 03/09/2021

Deep 6-DoF Tracking of Unknown Objects for Reactive Grasping

Robotic manipulation of unknown objects is an important field of researc...

0 Marc Tuscher, et al. ∙

research

∙ 01/28/2021

Visualization of Nonlinear Programming for Robot Motion Planning

Nonlinear programming targets nonlinear optimization with constraints, w...

0 David Hägele, et al. ∙

research

∙ 11/23/2020

MoGaze: A Dataset of Full-Body Motions that Includes Workspace Geometry and Eye-Gaze

As robots become more present in open human environments, it will become...

0 Philipp Kratzer, et al. ∙

research

∙ 11/09/2020

Learning Efficient Constraint Graph Sampling for Robotic Sequential Manipulation

Efficient sampling from constraint manifolds, and thereby generating a d...

0 Joaquim Ortiz de Haro, et al. ∙

research

∙ 11/03/2020

Efficient Sampling of Transition Constraints for Motion Planning under Sliding Contacts

Contact-based motion planning for manipulation, object exploration or ba...

0 Marie-Therese Khoury, et al. ∙

research

∙ 11/02/2020

Sparse Multilevel Roadmaps on Fiber Bundles for High-Dimensional Motion Planning

Sparse roadmaps are important to compactly represent state spaces, to de...

0 Andreas Orthey, et al. ∙

research

∙ 10/27/2020

Section Patterns: Efficiently Solving Narrow Passage Problems using Multilevel Motion Planning

Sampling-based planning methods often become inefficient due to narrow p...

0 Andreas Orthey, et al. ∙

research

∙ 07/30/2020

Natural Gradient Shared Control

We propose a formalism for shared control, which is the problem of defin...

0 Yoojin Oh, et al. ∙

research

∙ 07/20/2020

Anticipating Human Intention for Full-Body Motion Prediction in Object Grasping and Placing Tasks

Motion prediction in unstructured environments is a difficult problem an...

0 Philipp Kratzer, et al. ∙

research

∙ 07/18/2020

Multilevel Motion Planning: A Fiber Bundle Formulation

Motion planning problems involving high-dimensional state spaces can oft...

0 Andreas Orthey, et al. ∙

research

∙ 07/15/2020

Qgraph-bounded Q-learning: Stabilizing Model-Free Off-Policy Deep Reinforcement Learning

In state of the art model-free off-policy deep reinforcement learning, a...

13 Sabrina Hoppe, et al. ∙

research

∙ 07/09/2020

An Interior Point Method Solving Motion Planning Problems with Narrow Passages

Algorithmic solutions for the motion planning problem have been investig...

0 Jim Mainprice, et al. ∙

research

∙ 06/09/2020

Deep Visual Reasoning: Learning to Predict Action Sequences for Task and Motion Planning from an Initial Scene Image

In this paper, we propose a deep convolutional recurrent neural network ...

2 Danny Driess, et al. ∙

research

∙ 03/29/2020

Optimized Directed Roadmap Graph for Multi-Agent Path Finding Using Stochastic Gradient Descent

We present a novel approach called Optimized Directed Roadmap Graph (ODR...

2 Christian Henkel, et al. ∙

research

∙ 03/17/2020

Robust Task and Motion Planning for Long-Horizon Architectural Construction Planning

Integrating robotic systems in architectural and construction processes ...

0 Valentin N. Hartmann, et al. ∙

research

∙ 03/09/2020

Probabilistic Framework for Constrained Manipulations and Task and Motion Planning under Uncertainty

Logic-Geometric Programming (LGP) is a powerful motion and manipulation ...

0 Jung-Su Ha, et al. ∙

research

∙ 02/28/2020

Describing Physics For Physical Reasoning: Force-based Sequential Manipulation Planning

Physical reasoning is a core aspect of intelligence in animals and human...

0 Marc Toussaint, et al. ∙

research

∙ 02/11/2020

Visualizing Local Minima in Multi-Robot Motion Planning using Morse Theory

Multi-robot motion planning problems often have many local minima. It is...

0 Andreas Orthey, et al. ∙

research

∙ 10/04/2019

Prediction of Human Full-Body Movements with Motion Optimization and Recurrent Neural Networks

Human movement prediction is difficult as humans naturally exhibit compl...

25 Philipp Kratzer, et al. ∙

research

∙ 09/11/2019

Motion Planning Explorer: Visualizing Local Minima using a Local-Minima Tree

We present an algorithm to visualize local minima in a motion planning p...

4 Andreas Orthey, et al. ∙

Marc Toussaint

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