Rafael Vidal Aroca

Towards green data centers: A comparison of x86 and ARM architectures power efficiency

Servers and clusters are fundamental building blocks of high performance computing systems and the IT infrastructure of many companies and institutions. This paper analyzes the feasibility of building servers based on low power computers through an experimental comparison of server applications running on x86 and ARM computer architectures. The comparison executed on web and database servers includes power usage, CPU load, temperature, request latencies and the number of requests handled by each tested system. Floating point performance and power usage are also evaluated. The use of ARM based systems has shown to be a good choice when power efficiency is needed without losing performance.

Efficient 3D object recognition using foveated point clouds

Recent hardware technologies have enabled acquisition of 3D point clouds from real world scenes in real time. A variety of interactive applications with the 3D world can be developed on top of this new technological scenario. However, a main problem that still remains is that most processing techniques for such 3D point clouds are computationally intensive, requiring optimized approaches to handle such images, especially when real time performance is required. As a possible solution, we propose the use of a 3D moving fovea based on a multiresolution technique that processes parts of the acquired scene using multiple levels of resolution. Such approach can be used to identify objects in point clouds with efficient timing. Experiments show that the use of the moving fovea shows a seven fold performance gain in processing time while keeping 91.6% of true recognition rate in comparison with state-of-the-art 3D object recognition methods. Graphical abstractDisplay Omitted HighlightsObject recognition: foveation speedup 7x compared to the non-foveated approach.True recognitions rates are kept high with false recognitions at 8.3%.Faster setups with 91.6% recognition rate and 14x improvement were also achieved.The slowest configuration still shows almost 3x faster computing times

A Wearable Mobile Sensor Platform to Assist Fruit Grading

Wearable computing is a form of ubiquitous computing that offers flexible and useful tools for users. Specifically, glove-based systems have been used in the last 30 years in a variety of applications, but mostly focusing on sensing peoples attributes, such as finger bending and heart rate. In contrast, we propose in this work a novel flexible and reconfigurable instrumentation platform in the form of a glove, which can be used to analyze and measure attributes of fruits by just pointing or touching them with the proposed glove. An architecture for such a platform is designed and its application for intuitive fruit grading is also presented, including experimental results for several fruits.

Method for Reading Sensors and Controlling Actuators Using Audio Interfaces of Mobile Devices

This article presents a novel closed loop control architecture based on audio channels of several types of computing devices, such as mobile phones and tablet computers, but not restricted to them. The communication is based on an audio interface that relies on the exchange of audio tones, allowing sensors to be read and actuators to be controlled. As an application example, the presented technique is used to build a low cost mobile robot, but the system can also be used in a variety of mechatronics applications and sensor networks, where smartphones are the basic building blocks.

Design and Implementation of a Control System for a Sailboat Robot

This article discusses a control architecture for autonomous sailboat navigation and also presents a sailboat prototype built for experimental validation of the proposed architecture. The main goal is to allow long endurance autonomous missions, such as ocean monitoring. As the system propulsion relies on wind forces instead of motors, sailboat techniques are introduced and discussed, including the needed sensors, actuators and control laws. Mathematical modeling of the sailboat, as well as control strategies developed using PID and fuzzy controllers to control the sail and the rudder are also presented. Furthermore, we also present a study of the hardware architecture that enables the system overall performance to be increased. The sailboat movement can be planned through predetermined geographical way-points provided by a base station. Simulated and experimental results are presented to validate the control architecture, including tests performed on a lake. Underwater robotics can rely on such a platform by using it as a basis vessel, where autonomous charging of unmanned vehicles could be done or else as a relay surface base station for transmitting data.

Probabilistic robotic grid mapping based on occupancy and elevation information

This paper proposes an alternative environment mapping method for accurate robotic navigation based on 3D information. Typical techniques for 3D mapping using occupancy grid require intensive computational workloads to both build and store the map. We introduce an occupancy-elevation grid (OEG) mapping technique, which is a discrete mapping approach where each cell represents the occupancy probability, the height of the terrain and its variance. This representation allows a mobile robot to know if a spot in the environment is occupied by an obstacle and the height of such obstacle, thus, it can decide if it is possible to traverse the obstacle. In general, the map representation introduced can be used in conjunction with any kind of distance sensor. In this work, we have used laser range data with a probabilistic treatment. The resulting maps allow the execution of tasks like decision making for autonomous navigation, exploration, localization and path planning, considering the existence and the height of the obstacles. Experiments carried out with real data demonstrate that the proposed approach yields useful maps for autonomous navigation.

Real Time Interactive Image Segmentation Using User Indicated Real-World Seeds

We propose a novel and fast interactive segmentation methodology for computer vision applications. Basically, the proposed system performs the tracking of seeds so that multiple seeds can be acquired over time, substantially improving the segmentation results. Moreover, instead of image coordinates, the user indicates points in the real-world that become seeds in the image. These seeds can be indicated, for example using a laser pointer or a smart-phone. The seeds can then be tracked and used by a segmentation algorithm. Experiments using the Lucas-Kanade Optical Flow and the Fast Multi-Object Fuzzy Segmentation (Fast-MOFS) algorithm demonstrate that the proposed technique successfully segments images in real-time and improves the user ability to directly segment an object in the real world. The proposed system has a high performance, allowing it to be used with high frame rates in devices with low processing capability and/or with restricted power requirements.

Brazilian robotics olympiad: a successful paradigm for science and technology dissemination

This article introduces the successful methodology adopted for the realization of the Brazilian Robotics Olympiad. Organizational and scientific issues are presented and discussed as well as results of statistical surveys performed with participants that verify the benefits brought by this robotics Olympiad. The Brazilian Robotics Olympiad is a nine-year-old nation-wide initiative created with the mission of promoting robotics among Brazilian students with or without previous knowledge of robotics, fostering their interest to engage in science, technology and engineering studies and careers. The Olympiad is fully free for participants, being annually organized by hundreds of volunteers from several Brazilian universities. It is divided into practical and theoretical components with several levels, each one designed for a certain student age. More than 300,000 students have already participated in the Brazilian Robotics Olympiad and, according to 58% of these students, the Brazilian Robotics Olympiad helped them to decide which university course to pursue.

Cloud based low cost educational robot

This paper presents a novel Internet and Telephony cloud based system for low cost educational robotics. A webserver provides a web based on-line application that allows students to write block based or textual programs for a robot. When the program is executed, this server calls a standard mobile phone using the public switched telephony network and uses the telephony audio channel to send actuator commands and read sensors through audio tones. The proposed architecture allows the construction of low cost educational robots that can be programmed and controlled from the web via any mobile phone that can receive calls and has standard earphone connectors.