On the Practical Limitations for the Generation of Gunn Oscillations in Highly Doped GaN Diodes

Planar Gunn diodes based on doped GaN active layers with different geometries have been fabricated and characterized. Gunn oscillations have not been observed due to the catastrophic breakdown of the diodes for applied voltages around 20-25 V, much below the bias theoretically needed for the onset of Gunn oscillations. The breakdown of the diodes has been analyzed by pulsed I-V measurements at low temperature, and it has been observed to be almost independent of the geometry of the channels, thus allowing to discard self-heating effects as the origin of the device burning. The other possible mechanism for the device failure is impact-ionization avalanche due to the high electric fields present at the anode corner of the isolating trenches. However, Monte Carlo simulations using the typical value of the intervalley energy separation of GaN, ε_(1-2)=2.2 eV, show that impact ionization mechanisms are not significant for the voltages for which the experimental failure is observed. But recent experiments showed that ε_(1-2) is lower, around 0.9 eV. This lower intervalley separation leads to a much lower threshold voltage for the Gunn oscillations, not far from the experimental breakdown. Therefore, we attribute the devices failure to an avalanche process just when Gunn domains start to form, since they increase the population of electrons at the high electric field region, thus strongly enhancing impact ionization mechanisms which lead to the diode failure

Towards a portable smart spatial exploration system for environment perception

International audienc

INSPEX: Make environment perception available as a portable system

International audienceObstacle avoidance systems for autonomous vehicles combine multiple sensing technologies (i.e. LiDAR, Radar, Ultrasound and Visual) to detect different types of obstacles across the full range of lighting and weather conditions. Sensor data are fused with vehicle orientation (obtained for instance from an Inertial Measurement Unit and/or compass) and navigation subsystems. Power hungry, they require powerful computational capability, which limits their use to high-end vehicles and robots. 2 INSPEX ambition The H2020 INSPEX project plans to make obstacle detection capabilities available as a personal portable multi-sensors, miniaturised, low power device. This device will detect, locate and warn of obstacles under different environmental conditions, in indoor/outdoor environments, with static and mobile obstacles. Potential applications range from safer human navigation in reduced visibility conditions (e.g. for first responders and fire brigades), small robot/drone obstacle avoidance systems to navigation for the visually and mobility impaired people. As primary demonstrator (Fig.1), we will plug the INSPEX device on a white cane (see Fig. 1) for Visually Impaired and Blind (VIB) people to detect obstacle over the whole person height, provide audio feedback about harmful obstacles, improve their mobility confidence and reduce injuries, especially at waist and head levels [1]. The device will offer a "safety cocoon" to its user

INSPEX: design and integration of a portable/wearable smart spatial exploration system

The INSPEX H2020 project main objective is to integrate automotive-equivalent spatial exploration and obstacle detection functionalities into a portable/wearable multi-sensor, miniaturised, low power device. The INSPEX system will detect and localise in real-time static and mobile obstacles under various environmental conditions in 3D. Potential applications range from safer human navigation in reduced visibility, small robot/drone obstacle avoidance systems to navigation for the visually/mobility impaired, this latter being the primary use-case considered in the project

INSPEX: Make environment perception available as a portable system

Obstacle avoidance systems for autonomous vehicles combine multiple sensing technologies (i.e. LiDAR, Radar, Ultrasound and Visual) to detect different types of obstacles across the full range of lighting and weather conditions. Sensor data are fused with vehicle orientation (obtained for instance from an Inertial Measurement Unit and/or compass) and navigation subsystems. Power hungry, they require powerful computational capability, which limits their use to high-end vehicles and robots

Adaptive Data Prefetching for High Performance Processors

Projet ANR PersyvalInternational audienceNowadays, one of the main limiting factor in processordevelopment is the increasing speed gap between efficient processingelements and slow main memories. To reduce this limitation, prefetchingmechanisms, implemented in memory hierarchy, attempt to predict thefuture data needed in local memory. However, classical proposedsolutions are designed for specific access sequences but lack ofefficiency considering irregular and heterogeneous access patterns.Adaptive data prefetching aims to tackle the limitation of existingprefetch solution by self-reconfiguring its parameters according to thedynamic variations in the current access sequence. We propose to use amodeling of the main existing access patterns and an on-line monitoringof the access sequence to detect and trigger the data prefetching

Application of distributed model predictive approaches to temperature and CO2 concentration control in buildings

In the context of energy consumption reduction, this paper focuses on the application of Model Predictive Control to occupants’ thermal comfort together with indoor air quality control while improving the whole building energy efficiency First, an open-space office split in three zones, located in Cork Institute of Technology, is modeled. A centralized MPC is designed to control the temperature and CO2 concentration in the three zones. Then, a distributed version of the MPC, with three separate local controllers, is considered. Finally, simulation results show that the distributed MPC solution achieves control performance quite close to the centralized version with less computing effort

A Low-Cost Air Data Attitude Heading Reference System for the Tourism Airplane Applications

Abstract-A cheap tourism airplane ADAHRS unit is developed by fusing magnetometers, rate gyros and accelerometers (MEMS technology). The rigid body orientation is modeled with quaternion, which eliminates attitude estimation singularities. The real-time implementation is done unifying a quaternion formulation of Wahba's problem with a Multiplicative Extended Kalman Filter. It includes the gyro bias model. A quaternion measurement model is introduced. It avoids the linearization step that induces undesirable effects. Accelerometers detect gravitational acceleration and centrifugal forces, resulting in incorrect attitude estimation (e.g. false horizon and subjective vertical). Therefore, some pressure sensors are added, resulting in a robust solution. The real-time implementation uses a PCMCIA data acquisition card and a TabletPC. Simulated and real data validate the ADAHRS