Structuring a virtual environment for sport training: A case study on rowing technique

The advancements in technology and the possibility of their integration in the domain of virtual environments allow access to new application domains previously limited to highly expensive setups. This is specifically the case of sport training that can take advantage of the improved quality of measurement systems and computing techniques. Given this the challenge that emerges is related to the way training is performed and how it is possible to evaluate the transfer from the virtual setup to the real case. In this work we discuss the aspect of system architecture for a VE in sport training, taking as a case study a rowing training system. The paper will address in particular the challenges of training technique in rowing

Exploiting Posit Arithmetic for Deep Neural Networks in Autonomous Driving Applications

This paper discusses the introduction of an integrated Posit Processing Unit (PPU) as an alternative to Floating-point Processing Unit (FPU) for Deep Neural Networks (DNNs) in automotive applications. Autonomous Driving tasks are increasingly depending on DNNs. For example, the detection of obstacles by means of object classification needs to be performed in real-time without involving remote computing. To speed up the inference phase of DNNs the CPUs on-board the vehicle should be equipped with co-processors, such as GPUs, which embed specific optimization for DNN tasks. In this work, we review an alternative arithmetic that could be used within the co-processor. We argue that a new representation for floating point numbers called Posit is particularly advantageous, allowing for a better trade-off between computation accuracy and implementation complexity. We conclude that implementing a PPU within the co-processor is a promising way to speed up the DNN inference phase

A Method for Digital Representation of Human Movements

In this work we present a method to produce a model of human motion based on an expansion in functions series. The model is thought to reproduce the learned movements generalizing them to different conditions. We will show, with an example, how the proposed method is capable to produce the model from a reduced set of examples preserving the relevant features of the demonstrations while guaranteeing constraints at boundaries

ArchGenTool: a System-Independent Collaborative Tool for Robotic Architecture Design

Complex robotic architectures require a collaborative effort in design and adherence to the design in the implementation phse. ArchGentTool is a collaborative architecture generation tool which supports the design of the robotic architecture in a multi-level fashion. It comprises high-level conceptual analysis of the system to be designed, as well as low-level implementation breakdown of its functional components, acting complementary to the ROS framework. The tool facilitates reusability and expandability of the architecture to any robotic system, as it can be adapted to different specifications. A case study with the RAMCIP service robot is presente

Standardized evaluation of haptic rendering systems

The development and evaluation of haptic rendering algorithms presents two unique challenges. Firstly, the haptic information channel is fundamentally bidirectional, so the output of a haptic environment is fundamentally dependent on user input, which is difficult to reliably reproduce. Additionally, it is difficult to compare haptic results to real-world, "gold standard" results, since such a comparison requires applying identical inputs to real and virtual objects and measuring the resulting forces, which requires hardware that is not widely available. We have addressed these challenges by building and releasing several sets of position and force information, collected by physically scanning a set of real-world objects, along with virtual models of those objects. We demonstrate novel applications of this data set for the development, debugging, optimization, evaluation, and comparison of haptic rendering algorithms

Survey of Motion Tracking Methods Based on Inertial Sensors: A Focus on Upper Limb Human Motion

Motion tracking based on commercial inertial measurements units (IMUs) has been widely studied in the latter years as it is a cost-effective enabling technology for those applications in which motion tracking based on optical technologies is unsuitable. This measurement method has a high impact in human performance assessment and human-robot interaction. IMU motion tracking systems are indeed self-contained and wearable, allowing for long-lasting tracking of the user motion in situated environments. After a survey on IMU-based human tracking, five techniques for motion reconstruction were selected and compared to reconstruct a human arm motion. IMU based estimation was matched against motion tracking based on the Vicon marker-based motion tracking system considered as ground truth. Results show that all but one of the selected models perform similarly (about 35 mm average position estimation error)

Dynamic Power Consumption of the Full Posit Processing Unit: Analysis and Experiments

Since its introduction in 2017, the Posit™ format for representing real numbers has attracted a lot of interest, as an alternative to IEEE 754 floating point representation. Several hardware implementations of arithmetic operations between posit numbers have also been proposed in recent years. In this work, we analyze the dynamic power consumption of the Full Posit Processing Unit (FPPU) recently developed at the University of Pisa. Experimental results show that we can model the dynamic power consumption of the FPPU with an acceptable approximation error from 2.84% (32-bit FPPU) to 7.32% (8-bit FPPU). Furthermore, from the synthesis of the power monitoring unit alongside the FPPU we demonstrate that the additional power module has an area cost that goes from ∼ 5% (32-bit FPPU) to ∼ 30% (8-bit FPPU) of the total unit area occupatio