Least action principles and their application to constrained and task-level problems in robotics and biomechanics

International audienceLeast action principles provide an insightful starting point from which problems involving constraints and task-level objectives can be addressed. In this paper, the principle of least action is first treated with regard to holonomic constraints in multibody systems. A variant of this, the principle of least curvature or straightest path, is then investigated in the context of geodesic paths on constrained motion manifolds. Subsequently, task space descriptions are addressed and the operational space approach is interpreted in terms of least action. Task-level control is then applied to the problem of cost minimization. Finally, task-level optimization is formulated with respect to extremizing an objective criterion, where the criterion is interpreted as the action of the system. Examples are presented which illustrate these approaches

Common and rare variant association analyses in amyotrophic lateral sclerosis identify 15 risk loci with distinct genetic architectures and neuron-specific biology

A cross-ancestry genome-wide association meta-analysis of amyotrophic lateral sclerosis (ALS) including 29,612 patients with ALS and 122,656 controls identifies 15 risk loci with distinct genetic architectures and neuron-specific biology. Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease with a lifetime risk of one in 350 people and an unmet need for disease-modifying therapies. We conducted a cross-ancestry genome-wide association study (GWAS) including 29,612 patients with ALS and 122,656 controls, which identified 15 risk loci. When combined with 8,953 individuals with whole-genome sequencing (6,538 patients, 2,415 controls) and a large cortex-derived expression quantitative trait locus (eQTL) dataset (MetaBrain), analyses revealed locus-specific genetic architectures in which we prioritized genes either through rare variants, short tandem repeats or regulatory effects. ALS-associated risk loci were shared with multiple traits within the neurodegenerative spectrum but with distinct enrichment patterns across brain regions and cell types. Of the environmental and lifestyle risk factors obtained from the literature, Mendelian randomization analyses indicated a causal role for high cholesterol levels. The combination of all ALS-associated signals reveals a role for perturbations in vesicle-mediated transport and autophagy and provides evidence for cell-autonomous disease initiation in glutamatergic neurons

The application of quaternions and other spatial representations to the reconstruction of re-entry vehicle motion.

The analysis of spacecraft kinematics and dynamics requires an efficient scheme for spatial representation. While the representation of displacement in three dimensional Euclidean space is straightforward, orientation in three dimensions poses particular challenges. The unit quaternion provides an approach that mitigates many of the problems intrinsic in other representation approaches, including the ill-conditioning that arises from computing many successive rotations. This report focuses on the computational utility of unit quaternions and their application to the reconstruction of re-entry vehicle (RV) motion history from sensor data. To this end they will be used in conjunction with other kinematic and data processing techniques. We will present a numerical implementation for the reconstruction of RV motion solely from gyroscope and accelerometer data. This will make use of unit quaternions due to their numerical efficacy in dealing with the composition of many incremental rotations over a time series. In addition to signal processing and data conditioning procedures, algorithms for numerical quaternion-based integration of gyroscope data will be addressed, as well as accelerometer triangulation and integration to yield RV trajectory. Actual processed flight data will be presented to demonstrate the implementation of these methods

Fusion of product and process data: Batch-mode and real-time streaming

In today's DP product realization enterprise it is imperative to reduce the design-to-fabrication cycle time and cost while improving the quality of DP parts (reducing defects). Much of this challenge resides in the inherent gap between the product and process worlds. The lack of seamless, bi-directional flow of information prevents true concurrency in the product realization world. This report addresses a framework for product-process data fusion to help achieve next generation product realization. A fundamental objective is to create an open environment for multichannel observation of process date, and subsequent mapping of that data onto product geometry. In addition to the sensor-based observation of manufacturing processes, model-based process data provides an important complement to empirically acquired data. Two basic groups of manufacturing models are process physics, and machine kinematics and dynamics. Process physics addresses analytical models that describe the physical phenomena of the process itself. Machine kinematic and dynamic models address the mechanical behavior of the processing equipment. As a secondary objective, an attempt has been made in this report to address part of the model-based realm through the development of an open object-oriented library and toolkit for machine kinematics and dynamics. Ultimately, it is desirable to integrate design definition, with all types of process data; both sensor-based and model-based. Collectively, the goal is to allow all disciplines within the product realization enterprise to have a centralized medium for the fusion of product and process data

Task-level approaches for the control of constrained multibody

system

Keywords Least action · Constraints · Task-level control · Musculoskeletal system ·

Least action principles and their application to constrained and task-level problems in robotics and biomechanic