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Challenges in exploiting prioritized inverse kinematics for motion capture and postural control

Related publications (38)

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Expressing Motivations By Facilitating Other’s Inverse Reinforcement Learning

Pierre Dillenbourg, Wafa Monia Benkaouar Johal, Alexis David Jacq, Ana Paiva

It is often necessary to understand each other’s motivations in order to cooperate. Reaching such a mutual understanding requires two abilities: to build models of other’s motivations in order to understand them, and to build a model of “my” motivations pe ...

Instituto Superiro Technico2017

Modelling Resource Dependencies

Simon Bliudze, Alena Simalatsar, Alina Zolotukhina

The major research in the resource management literature focuses primarily on two directions: 1) specification languages for formulating resource requests and 2) constraint problems modelling allocation and scheduling. Both directions assume the knowledge ...

2016

A Dichotomy for Real Weighted Holant Problems

Sangxia Huang

Holant is a framework of counting characterized by local constraints. It is closely related to other well-studied frameworks such as the counting constraint satisfaction problem (#CSP) and graph homomorphism. An effective dichotomy for such frameworks can ...

Springer Basel Ag2016

Programming complex shapes in thin nematic elastomer and glass sheets

Marius Christopher Lemm

Nematic elastomers and glasses are solids that display spontaneous distortion under external stimuli. Recent advances in the synthesis of sheets with controlled heterogeneities have enabled their actuation into nontrivial shapes with unprecedented energy d ...

2016

Protecting Privacy through Distributed Computation in Multi-agent Decision Making

Boi Faltings, Thomas Léauté

As large-scale theft of data from corporate servers is becoming increasingly common, it becomes interesting to examine alternatives to the paradigm of centralizing sensitive data into large databases. Instead, one could use cryptography and distributed com ...

AI Access Foundation2013

A Multipath Sparse Beamfroming Method

Hervé Bourlard, Volkan Cevher, Afsaneh Asaei

A novel formulation of beamforming is proposed for acquisition of the signals in reverberant acoustic clutter of interferences and noise. We derive the beamforming methods which incorporate the sparsity structure pertained to the acoustic source distributi ...

2013

Stochastic Model Predictive Control: Controlling the Average Number of Constraint Violations

Colin Neil Jones, Milan Korda

This paper considers linear discrete-time systems with additive bounded disturbances subject to hard control input bounds and constraints on the expected number of state-constraint violations averaged over time, or, equivalently, constraints on the probabi ...

2012

Constraints as Control

Viktor Kuncak, Philippe Paul Henri Suter

We present an extension of Scala that supports constraint programming over bounded and unbounded domains. The resulting language, Kaplan, provides the benefits of constraint programming while preserving the existing features of Scala. Kaplan integrates con ...

2012

Constraints as Control

Viktor Kuncak, Philippe Paul Henri Suter

ACM Order Department, P O Box 64145, Baltimore, MD 21264 Usa2012

Input Filter Design for Feasibility in Constraint-Adaptation Schemes

Dominique Bonvin, Grégory François, Gene Bunin

The subject of real-time, steady-state optimization under significant uncertainty is addressed in this paper. Specifically, the use of constraint-adaptation schemes is reviewed, and it is shown that, in general, such schemes cannot guarantee process feasib ...

2011