Jean-Yves Fourniols

Stereo Vision Algorithm Implementation in FPGA Using Census Transform for Effective Resource Optimization

In this work, we present the implementation in a reconfigurable architecture of a dense stereo vision algo- rithm based on census transform. Analyzing census transform algorithm we found that size and access memory could be reduced, which consequently also reduced the latency time. Furthermore, architecture resources are optimized and efficient thanks to binary operations and integer arithmetic used by census transform directly compatible with the FPGA. Final architecture is able to construct 130 dense disparity maps per second for each corresponding pair of stereo images. A performance analysis, among other three disparity map implementations and our architecture, shows that at the end, we propose a better trade off among performance, latency, logic elements and memory size. The optimization and the resource saving rend our architecture an interesting option to solve the problem of stereo vision in real time, quite used in autonomous navigation.

An efficient reconfigurable architecture to implement dense stereo vision algorithm using high-level synthesis

This article presents a reconfigurable architecture to calculate a dense disparity map of two stereo images based on census transform. This architecture is simplified and efficient as a result of binary operations and integer arithmetic used by census transform. Our architecture was prototyped using GAUT which is a practical tool to develop high-level synthesis. We take advantage of GAUT rapid prototyping to implement different architectures and to make a general comparison among them, that lets us to optimize the architecture, and at the same time, to improve the systems performance. The optimization and the resource saving rend our architecture an interesting option to solve the problem of stereo vision in real time, quite used in autonomous navigation.

Stereovision Algorithm to be Executed at 100Hz on a FPGA-Based Architecture

Michel Devy1 * , Jean-Louis Boizard2, Diego Botero Galeano3, Henry Carrillo Lindado4, Mario Ibarra Manzano5, Zohir Irki6, Abdelelah Naoulou7, Pierre Lacroix8, Philippe Fillatreau9, Jean-Yves Fourniols10, Carlos Parra11 1,2,3,5,6,7,8,10CNRS; LAAS; 7 avenue du Colonel Roche, F-31077 Toulouse Universite de Toulouse; UPS, INSA, INP, ISAE; LAAS-CNRS : F-31077 Toulouse 3,4,11Pontificia Universidad Javeriana; Carrera 7 No. 40-62; Bogota 9Delta Technologies Sud Ouest; 2 Impasse Michel Labrousse, 31036 Toulouse 1,2,3,5,6,7,8,9,10France 3,4,11Columbia

Reliability of microsystems based on a failure mechanism approach

Compactness, complexity of the interconnections and specific packaging, which are characteristics of Microsystems (MEMS), rule out the use of statistical procedure to assess reliability in space applications. Predictable reliability is the method recommended in this paper that uses a similar approach as CALCE already did for hybrid and microelectronic circuits. This method based on a failure mechanism approach is recalled at first and an example to illustrate this procedure based on the evolution of material crystal properties under radiation is presented.

New real-time structural health monitoring microsystem for aircraft propeller blades

This presents work done on the project “Blade Parameters Recording Microsystem” funded by the French research program FUI. It resulted in a fully operational recorder that can be embedded on a plane. This system allows blade monitoring to be conducted using computing algorithms. Using a top-down modelling method, this recorder can be adapted to any kind of blade. Herein, recorder was devised for a Transall plane blade. This device was used to record data in order to subsequently compute a real-time blade monitoring algorithm. The algorithm takes several blade parameters into account. The top-down modelling easily allows the algorithm parameters to be adapted to various blades.

A Study about Kalman Filters Applied to Embedded Sensors

Over the last decade, smart sensors have grown in complexity and can now handle multiple measurement sources. This work establishes a methodology to achieve better estimates of physical values by processing raw measurements within a sensor using multi-physical models and Kalman filters for data fusion. A driving constraint being production cost and power consumption, this methodology focuses on algorithmic complexity while meeting real-time constraints and improving both precision and reliability despite low power processors limitations. Consequently, processing time available for other tasks is maximized. The known problem of estimating a 2D orientation using an inertial measurement unit with automatic gyroscope bias compensation will be used to illustrate the proposed methodology applied to a low power STM32L053 microcontroller. This application shows promising results with a processing time of 1.18 ms at 32 MHz with a 3.8% CPU usage due to the computation at a 26 Hz measurement and estimation rate.

Space microsystems and reliability: The contribution of behavioral modeling

In order to reduce the weight and enhance the performances of space systems, it would be very interesting to use microsystems/MEMS (Micro-Electro-Mechanical Systems). Before using them, it is necessary to assure their reliability under the particular harsh environmental conditions (radiation, temperature, …) present in a space environment. The development of new reliability approaches is necessary to do this reliability assessment. We are working on a reliability approach that aims to assess the reliability of MEMS components by means of simulation. In order to apply the methodology we have developed a virtual prototype, i. e. a system model, of a part of a launch vehicle’s measurement system as well as a model of a commercial MEMS accelerometer, the ADXL150. The accelerometer model takes into consideration the influence of environmental constraints such as humidity.

Preliminary study: IMU system validation for real-time feedback on swimming technique

The use of Inertial Measurement Units (IMU) for sport performance monitoring has grown in the previous decade due to its ease of use and the growth of private market applications. In swimming monitoring, it has been highlighted (Dadashi et al. 2012; Callaway et al. 2015) that measuring performance with traditional 2D and 3D video-based systems have many downsides (light refraction, bubbles, time-consuming). Other alternative methods are also mentioned such as speed measurement using a tighten cord, but they disturb the swimmer’s technique and only provides feedback on the forward speed. The main problem of those solutions is that the data must be post processed and they do not provide an instant feedback to the swimmer. In this context, IMUs appear to be a low-cost solution, easy to use and not interfering with the swimmer’s technique, even if its data analysis requires a complex data mining process. Such real-time feedback for gesture and sport training is a solution that has been used many times: for instance karate training (Takahata et al. 2004), and various other sports (Spelmezan et al. 2008; Drobny et al. 2009). It has been shown (Zatoń et al. 2014) that an immediate feedback can improve swimming technique. Measuring the performance is something much in demand for sportsmen to be able to keep track of their progress. For swimming, the most common performance criterion tends to be stroke length, stroke count and lap count (Dadashi et al. 2012), which are often summarized by coaches as the ‘Swim Golf ’ (SWOLF) criteria (Perego et al. 2015). Those have been used in several scientific publications as references of the swimmer’s level (Peregoet al. 2015; Lemkaddem et al. 2016), but it also has been shown (Cardelli et al. 2000) that there is a significant correlation between the breathing characteristics and the swimmer’s skills plus the stroke characteristics. From this statement we wanted to validate an IMU devices mounted on the head of a swimmer to measure its breathing characteristics, and experiment on an instant feedback to correct those movements. The tested device is a Swimbot (Meudon, France), based on Newton 2 smart watch core (Ingenic, Beijing) including a 1.2 GhZ M200 CPU running a custom Android 5.1 with a 16 bits 9 axis IMU (MPU-9250 (InvenSense, San Jose, California) embedded, using the Android sensors fusion algorithm to provide a rotation quaternion at a sampling rate of 50 Hz. The other data provided are: accelerometer, magnetometer and gyroscope and two software sensors provided by Android: linear acceleration (without the gravity) and quaternion orientation. The device is placed under the swimming cap at the back of the head and also includes two bone conduction headphones placed just behind the ears for instant feedback under water, with an on-board memory of 2 Gb of data to store logs and data.

Embedded Sensors System Applied to Wearable Motion Analysis in Sports

This paper presents two different wearable motion capture systems for motion analysis in sports, based on inertial measurement units (IMU). One system, called centralized processing, is based on FPGA + microcontroller architecture while the other, called distributed processing, is based on multiple microcontrollers + wireless communication architecture. These architectures are designed to target multisports capabilities, beginning with tri-athlete equipment and thus have to be non-invasive and integrated in sportswear, be waterproofed and autonomous in energy. To characterize them, the systems are compared to lab quality references.

System Engineering Method for System Design

The purpose of this chapter is to present some educational materials, the process and the outcomes to teach an engineering approach applied to a practical development case. The starting point is the requirements of an application of remote supervision of a room with several parameters: light, temperature and movement (intrusion into the room or movement of an object within the room). This application is based on wireless terminal nodes composed of a sensor, a microcontroller and a telecommunication module. Several rooms can be interconnected, so it must be possible to use the sensors of each room of a given site simultaneously. Various issues can be raised during teaching on wireless sensor networks (Kotzl & Essien, 2005): electronic design, risks to humans (Brownsell et al., 1999), energy management, telecommunication technologies, etc.