A human body model for dynamic response analysis of an integrated human-seat-controller-high speed marine craft interaction system

Small boats are increasingly being operated at high speed in rough weather by organisations carrying out essential missions such as the military and rescue services. Crew and passengers on these boats are exposed to continuous vibration and impacts leading to reduced crew effectiveness, fatigue and the possibility of injury. In addition to this marine craft will soon fall under the jurisdiction of the European Union Directive 2002/44/EC on the protection of workers from vibration.To assess the possibility of injury and mitigate it at the design stage of a vessel a design tool is needed to assess the vibration levels on/in the human body while the boat operates in dynamic environments. A review of current human body models is presented and a new human body model, which allows for estimates of muscle activity, is proposed. This model is supplemented by a numerical approach using finite element methods to assess the dynamic response of the integrated human-seat-controller-boat interaction system excited by wave loads or boat motions measured in full scale boat operation tests. The vibration control actuators are arranged between the seat and boat to reduce vibrations transmitted to the human body from the boat to obtain a comfortable ride condition

A human body model for dynamic response analysis of an integrated human-seat-controller-high speed marine craft interaction system

Small boats are increasingly being operated at high speed in rough weather by organisations carrying out essential missions such as the military and rescue services. Crew and passengers on these boats are exposed to continuous vibration and impacts leading to reduced crew effectiveness, fatigue and the possibility of injury. In addition to this marine craft will soon fall under the jurisdiction of the European Union Directive 2002/44/EC on the protection of workers from vibration.To assess the possibility of injury and mitigate it at the design stage of a vessel a design tool is needed to assess the vibration levels on/in the human body while the boat operates in dynamic environments. A review of current human body models is presented and a new human body model, which allows for estimates of muscle activity, is proposed. This model is supplemented by a numerical approach using finite element methods to assess the dynamic response of the integrated human-seat-controller-boat interaction system excited by wave loads or boat motions measured in full scale boat operation tests. The vibration control actuators are arranged between the seat and boat to reduce vibrations transmitted to the human body from the boat to obtain a comfortable ride condition

Neural 3D Morphable Models: Spiral Convolutional Networks for 3D Shape Representation Learning and Generation

Generative models for 3D geometric data arise in many important applications in 3D computer vision and graphics. In this paper, we focus on 3D deformable shapes that share a common topological structure, such as human faces and bodies. Morphable Models and their variants, despite their linear formulation, have been widely used for shape representation, while most of the recently proposed nonlinear approaches resort to intermediate representations, such as 3D voxel grids or 2D views. In this work, we introduce a novel graph convolutional operator, acting directly on the 3D mesh, that explicitly models the inductive bias of the fixed underlying graph. This is achieved by enforcing consistent local orderings of the vertices of the graph, through the spiral operator, thus breaking the permutation invariance property that is adopted by all the prior work on Graph Neural Networks. Our operator comes by construction with desirable properties (anisotropic, topology-aware, lightweight, easy-to-optimise), and by using it as a building block for traditional deep generative architectures, we demonstrate state-of-the-art results on a variety of 3D shape datasets compared to the linear Morphable Model and other graph convolutional operators.Comment: to appear at ICCV 201

Applications and benefits of digital human models to improve the design of workcells in car’s manufacturing plants according to international standards

During last years, the car’s manufacturing process has deeply changed because of several factors affected the automotive global scenario. As a consequence, design methodologies of the plant’s workcells have changed. In particular, ergonomics for manufacturing system has become a key factor to improve product’s quality, safety and work organization. In this paper, the authors show the approach used in Fiat Group Automobiles (FGA) based on simulation tools to analyse ergonomic aspects of work-cells already in design phase. Simulation tools allow a deep postural analysis that is one of the main criticism in the design phase. The principles of Digital Human Modeling have been used to develop an easy internal virtual manikin, the Human Model. The tool, based on ISO standards and on a worldwide anthropometric database, allows designers to simulate the most probable postures engaged by operator during work tasks as well as to validate improvements and corrective actions

Supervised Autonomous Locomotion and Manipulation for Disaster Response with a Centaur-like Robot

Mobile manipulation tasks are one of the key challenges in the field of search and rescue (SAR) robotics requiring robots with flexible locomotion and manipulation abilities. Since the tasks are mostly unknown in advance, the robot has to adapt to a wide variety of terrains and workspaces during a mission. The centaur-like robot Centauro has a hybrid legged-wheeled base and an anthropomorphic upper body to carry out complex tasks in environments too dangerous for humans. Due to its high number of degrees of freedom, controlling the robot with direct teleoperation approaches is challenging and exhausting. Supervised autonomy approaches are promising to increase quality and speed of control while keeping the flexibility to solve unknown tasks. We developed a set of operator assistance functionalities with different levels of autonomy to control the robot for challenging locomotion and manipulation tasks. The integrated system was evaluated in disaster response scenarios and showed promising performance.Comment: In Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Madrid, Spain, October 201

OperatorNet: Recovering 3D Shapes From Difference Operators

This paper proposes a learning-based framework for reconstructing 3D shapes from functional operators, compactly encoded as small-sized matrices. To this end we introduce a novel neural architecture, called OperatorNet, which takes as input a set of linear operators representing a shape and produces its 3D embedding. We demonstrate that this approach significantly outperforms previous purely geometric methods for the same problem. Furthermore, we introduce a novel functional operator, which encodes the extrinsic or pose-dependent shape information, and thus complements purely intrinsic pose-oblivious operators, such as the classical Laplacian. Coupled with this novel operator, our reconstruction network achieves very high reconstruction accuracy, even in the presence of incomplete information about a shape, given a soft or functional map expressed in a reduced basis. Finally, we demonstrate that the multiplicative functional algebra enjoyed by these operators can be used to synthesize entirely new unseen shapes, in the context of shape interpolation and shape analogy applications.Comment: Accepted to ICCV 201