
-
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...
read it
-
Learning Efficient Constraint Graph Sampling for Robotic Sequential Manipulation
Efficient sampling from constraint manifolds, and thereby generating a d...
read it
-
Efficient Sampling of Transition Constraints for Motion Planning under Sliding Contacts
Contact-based motion planning for manipulation, object exploration or ba...
read it
-
Sparse Multilevel Roadmaps on Fiber Bundles for High-Dimensional Motion Planning
Sparse roadmaps are important to compactly represent state spaces, to de...
read it
-
Section Patterns: Efficiently Solving Narrow Passage Problems using Multilevel Motion Planning
Sampling-based planning methods often become inefficient due to narrow p...
read it
-
Natural Gradient Shared Control
We propose a formalism for shared control, which is the problem of defin...
read it
-
Anticipating Human Intention for Full-Body Motion Prediction in Object Grasping and Placing Tasks
Motion prediction in unstructured environments is a difficult problem an...
read it
-
Multilevel Motion Planning: A Fiber Bundle Formulation
Motion planning problems involving high-dimensional state spaces can oft...
read it
-
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...
read it
-
An Interior Point Method Solving Motion Planning Problems with Narrow Passages
Algorithmic solutions for the motion planning problem have been investig...
read it
-
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 ...
read it
-
Optimized Directed Roadmap Graph for Multi-Agent Path Finding Using Stochastic Gradient Descent
We present a novel approach called Optimized Directed Roadmap Graph (ODR...
read it
-
Robust Task and Motion Planning for Long-Horizon Architectural Construction Planning
Integrating robotic systems in architectural and construction processes ...
read it
-
Probabilistic Framework for Constrained Manipulations and Task and Motion Planning under Uncertainty
Logic-Geometric Programming (LGP) is a powerful motion and manipulation ...
read it
-
Describing Physics For Physical Reasoning: Force-based Sequential Manipulation Planning
Physical reasoning is a core aspect of intelligence in animals and human...
read it
-
Visualizing Local Minima in Multi-Robot Motion Planning using Morse Theory
Multi-robot motion planning problems often have many local minima. It is...
read it
-
Prediction of Human Full-Body Movements with Motion Optimization and Recurrent Neural Networks
Human movement prediction is difficult as humans naturally exhibit compl...
read it
-
Motion Planning Explorer: Visualizing Local Minima using a Local-Minima Tree
We present an algorithm to visualize local minima in a motion planning p...
read it
-
Deep Workpiece Region Segmentation for Bin Picking
For most industrial bin picking solutions, the pose of a workpiece is lo...
read it
-
An Optimal Algorithm to Solve the Combined Task Allocation and Path Finding Problem
We consider multi-agent transport task problems where, e.g. in a factory...
read it
-
Learning Arbitration for Shared Autonomy by Hindsight Data Aggregation
In this paper we present a framework for the teleoperation of pick-and-p...
read it
-
Motion Prediction with Recurrent Neural Network Dynamical Models and Trajectory Optimization
Predicting human motion in unstructured and dynamic environments is diff...
read it
-
Rapidly-Exploring Quotient-Space Trees: Motion Planning using Sequential Simplifications
Motion planning problems can be simplified by admissible projections of ...
read it
-
Trajectory-Based Off-Policy Deep Reinforcement Learning
Policy gradient methods are powerful reinforcement learning algorithms a...
read it
-
Kinematic Morphing Networks for Manipulation Skill Transfer
The transfer of a robot skill between different geometric environments i...
read it
-
Probabilistic Recurrent State-Space Models
State-space models (SSMs) are a highly expressive model class for learni...
read it
-
Physical problem solving: Joint planning with symbolic, geometric, and dynamic constraints
In this paper, we present a new task that investigates how people intera...
read it
-
Identification of Unmodeled Objects from Symbolic Descriptions
Successful human-robot cooperation hinges on each agent's ability to pro...
read it
-
Advancing Bayesian Optimization: The Mixed-Global-Local (MGL) Kernel and Length-Scale Cool Down
Bayesian Optimization (BO) has become a core method for solving expensiv...
read it
-
The Advantage of Cross Entropy over Entropy in Iterative Information Gathering
Gathering the most information by picking the least amount of data is a ...
read it
-
Planning with Noisy Probabilistic Relational Rules
Noisy probabilistic relational rules are a promising world model represe...
read it
-
Path Integral Control by Reproducing Kernel Hilbert Space Embedding
We present an embedding of stochastic optimal control problems, of the s...
read it
-
Hierarchical POMDP Controller Optimization by Likelihood Maximization
Planning can often be simpli ed by decomposing the task into smaller tas...
read it
-
Approximate Inference and Stochastic Optimal Control
We propose a novel reformulation of the stochastic optimal control probl...
read it
-
Notes on information geometry and evolutionary processes
In order to analyze and extract different structural properties of distr...
read it
-
Recent Results on No-Free-Lunch Theorems for Optimization
The sharpened No-Free-Lunch-theorem (NFL-theorem) states that the perfor...
read it
-
The structure of evolutionary exploration: On crossover, buildings blocks and Estimation-Of-Distribution Algorithms
The notion of building blocks can be related to the structure of the off...
read it
-
Neutrality: A Necessity for Self-Adaptation
Self-adaptation is used in all main paradigms of evolutionary computatio...
read it
-
A neural model for multi-expert architectures
We present a generalization of conventional artificial neural networks t...
read it
-
On model selection and the disability of neural networks to decompose tasks
A neural network with fixed topology can be regarded as a parametrizatio...
read it
-
On Classes of Functions for which No Free Lunch Results Hold
In a recent paper it was shown that No Free Lunch results hold for any s...
read it
-
Self-adaptive exploration in evolutionary search
We address a primary question of computational as well as biological res...
read it