50 research outputs found
From Demonstrations to Task-Space Specifications:Using Causal Analysis to Extract Rule Parameterization from Demonstrations
Learning models of user behaviour is an important problem that is broadly
applicable across many application domains requiring human-robot interaction.
In this work, we show that it is possible to learn generative models for
distinct user behavioural types, extracted from human demonstrations, by
enforcing clustering of preferred task solutions within the latent space. We
use these models to differentiate between user types and to find cases with
overlapping solutions. Moreover, we can alter an initially guessed solution to
satisfy the preferences that constitute a particular user type by
backpropagating through the learned differentiable models. An advantage of
structuring generative models in this way is that we can extract causal
relationships between symbols that might form part of the user's specification
of the task, as manifested in the demonstrations. We further parameterize these
specifications through constraint optimization in order to find a safety
envelope under which motion planning can be performed. We show that the
proposed method is capable of correctly distinguishing between three user
types, who differ in degrees of cautiousness in their motion, while performing
the task of moving objects with a kinesthetically driven robot in a tabletop
environment. Our method successfully identifies the correct type, within the
specified time, in 99% [97.8 - 99.8] of the cases, which outperforms an IRL
baseline. We also show that our proposed method correctly changes a default
trajectory to one satisfying a particular user specification even with unseen
objects. The resulting trajectory is shown to be directly implementable on a
PR2 humanoid robot completing the same task.Comment: arXiv admin note: substantial text overlap with arXiv:1903.0126
CAD modeling, multibody system formalisms and visualization : an integrated approach
In this paper an integrated approach of CAD (Computer Aided Design) modeling, generation of equations of motion, simulation and visualization of multibody systems is described. An object-oriented data model for different multibody formalisms is integrated in a commercially available CAD-3D-system. With respect to existing CAD-interfaces, different solid model design methods and various visualization demands the datamodel allow, multi body modeling with a direct interface to a data base. Different software tools like an integrated Newton-Euler formalism are able to use immediately the parametrized multi body system data base. For multibody systems with closed kinematic loops a set of ordinary differential equations and decoupled algebraic equations is formulated automatically which can be solved with explicit multistep integration algorithms. This is achieved by a minimal set of generalized coordinates being specified during the numerical integration. A additional interface provides data for visualization from the simulation tool
The genomic landscape of balanced cytogenetic abnormalities associated with human congenital anomalies
Despite the clinical significance of balanced chromosomal abnormalities (BCAs), their characterization has largely been restricted to cytogenetic resolution. We explored the landscape of BCAs at nucleotide resolution in 273 subjects with a spectrum of congenital anomalies. Whole-genome sequencing revised 93% of karyotypes and demonstrated complexity that was cryptic to karyotyping in 21% of BCAs, highlighting the limitations of conventional cytogenetic approaches. At least 33.9% of BCAs resulted in gene disruption that likely contributed to the developmental phenotype, 5.2% were associated with pathogenic genomic imbalances, and 7.3% disrupted topologically associated domains (TADs) encompassing known syndromic loci. Remarkably, BCA breakpoints in eight subjects altered a single TAD encompassing MEF2C, a known driver of 5q14.3 microdeletion syndrome, resulting in decreased MEF2C expression. We propose that sequence-level resolution dramatically improves prediction of clinical outcomes for balanced rearrangements and provides insight into new pathogenic mechanisms, such as altered regulation due to changes in chromosome topology
Leaping forward, getting rich gloriously, and letting a hundred cities bloom
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