Low cost underwater robot sensor suite

One of the most expensive parts of underwater robotics is the sensors. This paper looks at modifying off the shelf components to create a sensor suite on a small budget. A big saving is made with sonar using a cheap commercial product to create a four sonar array. A depth sensor and acceleration navigation system are also developed.<br /

Modeling the Bat Spatial Navigation System: A Neuromorphic VLSI Approach

Autonomously navigating robots have long been a tough challenge facing engineers. The recent push to develop micro-aerial vehicles for practical military, civilian, and industrial use has added a significant power and time constraint to the challenge. In contrast, animals, from insects to humans, have been navigating successfully for millennia using a wide range of variants of the ultra-low-power computational system known as the brain. For this reason, we look to biological systems to inspire a solution suitable for autonomously navigating micro-aerial vehicles. In this dissertation, the focus is on studying the neurobiological structures involved in mammalian spatial navigation. The mammalian brain areas widely believed to contribute directly to navigation tasks are the Head Direction Cells, Grid Cells and Place Cells found in the post-subiculum, the medial entorhinal cortex, and the hippocampus, respectively. In addition to studying the neurobiological structures involved in navigation, we investigate various neural models that seek to explain the operation of these structures and adapt them to neuromorphic VLSI circuits and systems. We choose the neuromorphic approach for our systems because we are interested in understanding the interaction between the real-time, physical implementation of the algorithms and the real-world problem (robot and environment). By utilizing both analog and asynchronous digital circuits to mimic similar computations in neural systems, we envision very low power VLSI implementations suitable for providing practical solutions for spatial navigation in micro-aerial vehicles

Design of a prototype underwater research platform for swarm robotics

To perform under water robotic research requires specialized equipment. A few pieces of electronics atop a set of wheels are not going to cut it. An underwater research platform must be waterproof, reliable, robust, recoverable and easy to maintain. It must also be able to move in 3 dimensions. Also it must be able to navigate and avoid obstacles. Further if this platform is to be part of a swarm of like platforms then it must be cost effective and relatively small. To purchase such a platform can be very expensive. However, for shallow water, a suitable platform can be built from mostly off the shelf items at little cost. This article describes the design of one such underwater robot including various sensors and communications systems that allow for swarm robotics. Whilst the robotic platform performs well, to explore what many of them would do, that is more than are available, simulation is required. This article continues to study how best to simulate these robots for a swarm, or system of systems, approach

Convoy screening against a mixed submarine threat (U)

(U) The problem of convoy defense against a mixed threat of conventional and nuclear submarines is posed. A general, conceptual method of solution is offered from which a simple analytical model is constructed. Use of the model for obtaining optimal policies of screening force disposition is demonstrated. Underlying assumptions of the model and related tactical problem areas are discussed and analyzed.http://archive.org/details/convoyscreeningg109453040

Algorithm and Hardware Design for High Volume Rate 3-D Medical Ultrasound Imaging

abstract: Ultrasound B-mode imaging is an increasingly significant medical imaging modality for clinical applications. Compared to other imaging modalities like computed tomography (CT) or magnetic resonance imaging (MRI), ultrasound imaging has the advantage of being safe, inexpensive, and portable. While two dimensional (2-D) ultrasound imaging is very popular, three dimensional (3-D) ultrasound imaging provides distinct advantages over its 2-D counterpart by providing volumetric imaging, which leads to more accurate analysis of tumor and cysts. However, the amount of received data at the front-end of 3-D system is extremely large, making it impractical for power-constrained portable systems. In this thesis, algorithm and hardware design techniques to support a hand-held 3-D ultrasound imaging system are proposed. Synthetic aperture sequential beamforming (SASB) is chosen since its computations can be split into two stages, where the output generated of Stage 1 is significantly smaller in size compared to the input. This characteristic enables Stage 1 to be done in the front end while Stage 2 can be sent out to be processed elsewhere. The contributions of this thesis are as follows. First, 2-D SASB is extended to 3-D. Techniques to increase the volume rate of 3-D SASB through a new multi-line firing scheme and use of linear chirp as the excitation waveform, are presented. A new sparse array design that not only reduces the number of active transducers but also avoids the imaging degradation caused by grating lobes, is proposed. A combination of these techniques increases the volume rate of 3-D SASB by 4\texttimes{} without introducing extra computations at the front end. Next, algorithmic techniques to further reduce the Stage 1 computations in the front end are presented. These include reducing the number of distinct apodization coefficients and operating with narrow-bit-width fixed-point data. A 3-D die stacked architecture is designed for the front end. This highly parallel architecture enables the signals received by 961 active transducers to be digitalized, routed by a network-on-chip, and processed in parallel. The processed data are accumulated through a bus-based structure. This architecture is synthesized using TSMC 28 nm technology node and the estimated power consumption of the front end is less than 2 W. Finally, the Stage 2 computations are mapped onto a reconfigurable multi-core architecture, TRANSFORMER, which supports different types of on-chip memory banks and run-time reconfigurable connections between general processing elements and memory banks. The matched filtering step and the beamforming step in Stage 2 are mapped onto TRANSFORMER with different memory configurations. Gem5 simulations show that the private cache mode generates shorter execution time and higher computation efficiency compared to other cache modes. The overall execution time for Stage 2 is 14.73 ms. The average power consumption and the average Giga-operations-per-second/Watt in 14 nm technology node are 0.14 W and 103.84, respectively.Dissertation/ThesisDoctoral Dissertation Engineering 201

Real-time Map-building for Fast Mobile Robot Obstacle Avoidance

ABSTRACT This paper introduces HIMM (histogramic in-motion mapping), a new method for real-time map building with a mobile robot in motion. HIMM represents data in a two-dimensional array (called a histogram gjid) that is updated through rapid continuous sampling of the onboard range sensors during motion. Rapid in-motion sampling results in a statistical map representation that is well-suited to modeling inaccurate and noisy range-sensor data. HIMM is integral part of an obstacle avoidance algorithm and allows the robot to immediately use the mapped information in real-time obstacleavoidance. The benefits of this integrated approach are twofold: (1) quick, accurate mapping; and (2) safe navigation of the robot toward a given target. HIMM has been implemented and tested on a mobile robot. Its dual functionality was demonstrated through numerous tests in which maps of unknown obstacle courses were created, while the robot simultaneously performed real-time obstacle avoidance maneuvers at speeds of up to 0.78m/sec