Finding Perimeter of Query Regions in Heterogenous Wireless Sensor Networks

Some applications in wireless sensor networks (WSNs) only need to record the information of a target entering or leaving some specific regions of WSNs perimeter. One important issue in this context is to detect the perimeter of the deployed network to ensure that the sensor nodes cover the target area. In this paper we propose two distributed algorithms to elect the perimeter nodes of query regions in a WSN. We consider the most general case, where every sensor has a different sensing radius. We provide performance metrics to analyze the performance of our approach and show by simulation that the proposed algorithms give good performance

Fast Object Learning and Dual-arm Coordination for Cluttered Stowing, Picking, and Packing

Robotic picking from cluttered bins is a demanding task, for which Amazon Robotics holds challenges. The 2017 Amazon Robotics Challenge (ARC) required stowing items into a storage system, picking specific items, and packing them into boxes. In this paper, we describe the entry of team NimbRo Picking. Our deep object perception pipeline can be quickly and efficiently adapted to new items using a custom turntable capture system and transfer learning. It produces high-quality item segments, on which grasp poses are found. A planning component coordinates manipulation actions between two robot arms, minimizing execution time. The system has been demonstrated successfully at ARC, where our team reached second places in both the picking task and the final stow-and-pick task. We also evaluate individual components.Comment: In: Proceedings of the International Conference on Robotics and Automation (ICRA) 201

Viking '75 spacecraft design and test summary. Volume 1: Lander design

The Viking Mars program is summarized. The design of the Viking lander spacecraft is described

Using the Nonlinear Duffing Effect of Piezoelectric Micro-Oscillators for Wide-Range Pressure Sensing

This paper investigates the resonant behaviour of silicon-based micro-oscillators with a length of 3600 µm, a width of 1800 µm and a thickness of 10 µm over a wide range of ambient gas (N2 ) pressures, extending over six orders of magnitude from 10−3 mbar to 900 mbar. The oscillators are actuated piezoelectrically by a thin-film aluminium-nitride (AlN) layer, with the cantilever coverage area being varied from 33% up to 100%. The central focus is on nonlinear Duffing effects, occurring at higher oscillation amplitudes. A theoretical background is provided. All relevant parameters describing a Duffing oscillator, such as stiffness parameters for each coverage size as well as for different bending modes and more complex modes, are extracted from the experimental data. The so-called 2nd roof-tile-shaped mode showed the highest stiffness value of −97.3·107 m−2 s −2 . Thus, it was chosen as being optimal for extended range pressure measurements. Interestingly, both a spring softening effect and a spring hardening effect were observed in this mode, depending on the percentage of the AlN coverage area. The Duffing-effect-induced frequency shift was found to be optimal for obtaining the highest pressure sensitivity, while the size of the hysteresis loop is also a very useful parameter because of the possibility of eliminating the temperature influences and long-term drift effects of the resonance frequency. An reasonable application-specific compromise between the sensitivity and the measurement range can be selected by adjusting the excitation voltage, offering much flexibility. This novel approach turns out to be very promising for compact, cost-effective, wide-range pressure measurements in the vacuum range

AER Neuro-Inspired interface to Anthropomorphic Robotic Hand

Address-Event-Representation (AER) is a communication protocol for transferring asynchronous events between VLSI chips, originally developed for neuro-inspired processing systems (for example, image processing). Such systems may consist of a complicated hierarchical structure with many chips that transmit data among them in real time, while performing some processing (for example, convolutions). The information transmitted is a sequence of spikes coded using high speed digital buses. These multi-layer and multi-chip AER systems perform actually not only image processing, but also audio processing, filtering, learning, locomotion, etc. This paper present an AER interface for controlling an anthropomorphic robotic hand with a neuro-inspired system.Unión Europea IST-2001-34124 (CAVIAR)Ministerio de Ciencia y Tecnología TIC-2003-08164-C03-02Ministerio de Ciencia y Tecnología TIC2000-0406-P4- 0