
Prediction of Human FullBody Movements with Motion Optimization and Recurrent Neural Networks
Human movement prediction is difficult as humans naturally exhibit compl...
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RapidlyExploring QuotientSpace Trees: Motion Planning using Sequential Simplifications
Motion planning problems can be simplified by admissible projections of ...
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Deep Workpiece Region Segmentation for Bin Picking
For most industrial bin picking solutions, the pose of a workpiece is lo...
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TrajectoryBased OffPolicy Deep Reinforcement Learning
Policy gradient methods are powerful reinforcement learning algorithms a...
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Motion Planning Explorer: Visualizing Local Minima using a LocalMinima Tree
We present an algorithm to visualize local minima in a motion planning p...
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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 ...
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Optimized Directed Roadmap Graph for MultiAgent Path Finding Using Stochastic Gradient Descent
We present a novel approach called Optimized Directed Roadmap Graph (ODR...
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Physical problem solving: Joint planning with symbolic, geometric, and dynamic constraints
In this paper, we present a new task that investigates how people intera...
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Advancing Bayesian Optimization: The MixedGlobalLocal (MGL) Kernel and LengthScale Cool Down
Bayesian Optimization (BO) has become a core method for solving expensiv...
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Identification of Unmodeled Objects from Symbolic Descriptions
Successful humanrobot cooperation hinges on each agent's ability to pro...
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Notes on information geometry and evolutionary processes
In order to analyze and extract different structural properties of distr...
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Recent Results on NoFreeLunch Theorems for Optimization
The sharpened NoFreeLunchtheorem (NFLtheorem) states that the perfor...
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The structure of evolutionary exploration: On crossover, buildings blocks and EstimationOfDistribution Algorithms
The notion of building blocks can be related to the structure of the off...
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Neutrality: A Necessity for SelfAdaptation
Selfadaptation is used in all main paradigms of evolutionary computatio...
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A neural model for multiexpert architectures
We present a generalization of conventional artificial neural networks t...
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On model selection and the disability of neural networks to decompose tasks
A neural network with fixed topology can be regarded as a parametrizatio...
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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...
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Selfadaptive exploration in evolutionary search
We address a primary question of computational as well as biological res...
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Planning with Noisy Probabilistic Relational Rules
Noisy probabilistic relational rules are a promising world model represe...
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The Advantage of Cross Entropy over Entropy in Iterative Information Gathering
Gathering the most information by picking the least amount of data is a ...
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Hierarchical POMDP Controller Optimization by Likelihood Maximization
Planning can often be simpli ed by decomposing the task into smaller tas...
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Path Integral Control by Reproducing Kernel Hilbert Space Embedding
We present an embedding of stochastic optimal control problems, of the s...
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Approximate Inference and Stochastic Optimal Control
We propose a novel reformulation of the stochastic optimal control probl...
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Probabilistic Recurrent StateSpace Models
Statespace models (SSMs) are a highly expressive model class for learni...
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Kinematic Morphing Networks for Manipulation Skill Transfer
The transfer of a robot skill between different geometric environments i...
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Motion Prediction with Recurrent Neural Network Dynamical Models and Trajectory Optimization
Predicting human motion in unstructured and dynamic environments is diff...
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Learning Arbitration for Shared Autonomy by Hindsight Data Aggregation
In this paper we present a framework for the teleoperation of pickandp...
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An Optimal Algorithm to Solve the Combined Task Allocation and Path Finding Problem
We consider multiagent transport task problems where, e.g. in a factory...
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Visualizing Local Minima in MultiRobot Motion Planning using Morse Theory
Multirobot motion planning problems often have many local minima. It is...
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Describing Physics For Physical Reasoning: Forcebased Sequential Manipulation Planning
Physical reasoning is a core aspect of intelligence in animals and human...
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Probabilistic Framework for Constrained Manipulations and Task and Motion Planning under Uncertainty
LogicGeometric Programming (LGP) is a powerful motion and manipulation ...
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Robust Task and Motion Planning for LongHorizon Architectural Construction Planning
Integrating robotic systems in architectural and construction processes ...
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Marc Toussaint
verfied profile
Professor in Machine Learning and Robotics at University of Stuttgart