21 research outputs found

    Distributed Communication in Swarms of Autonomous Underwater Vehicles

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    Effective communication mechanisms are a key requirement for schools of submersible robots and their meaningful deployment. Large schools of identical submersibles require a fully distributed communication system which scales well and optimises for ”many-to-many” communication (omnicast, also known as gossiping). As an additional constraint, communication channels under water are typically very low bandwidth and short range. This thesis discusses possible electric and electro-magnetic wireless communication channels suitable for underwater environments. Theoretical findings on the omnicast communication problem are presented, as well as the implementation of a distributed time division multiple access (TDMA) scheduling algorithm in simulation and in hardware. It is shown theoretically and in simulation that short range links in a robotic swarm are actually an advantage, compared to links that cover large parts of the network. Experiments were carried out on custom-developed digital long-wave radio and optical link modules. The results of the experiments are used to revisit the initial assumptions on communication in multi-hop wireless networks

    Vertex: A New Distributed Underwater Robotic Platform for Environmental Monitoring

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    We present a new Autonomous Underwater Vehicle (AUV) system for cooperative environmental sensing. The AUV was specifically developed as a platform for distributed, cooperative sensing in lakes and coastal areas. In this paper we describe the prerequisite subsystems for a submersible multi-robot system and their interactions. In particular, we incorporate a distributed acoustic localisation system and distributed time-sliced communication systems into an agile, 5-DOF submersible robot that is small, easy to deploy and retrieve, with a modular environmental sensor payload for relevant scientific measurements. We also developed a distributed Hardware-In-the-Loop (HIL) simulation framework to facilitate early testing of algorithms in simulation while running final binary code on the actual robot hardware. To avoid communication overhead and real-time issues, the simulation of the vehicle dynamics and all proprioceptive sensors is performed on-board. Exteroceptive sensors are simulated by vehicle-to-vehicle communication where possible, supported by a central simulation supervisor where required. Finally, we present some preliminary experimental results of the system

    On-Board Relative Bearing Estimation for Teams of Drones Using Sound

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    In a team of autonomous drones, individual knowledge about the relative location of teammates is essential. Existing relative positioning solutions for teams of small drones mostly rely on external systems such as motion tracking cameras or GPS satellites that might not always be accessible. In this letter, we describe an onboard solution to measure the 3-D relative direction between drones using sound as the main source of information. First, we describe a method to measure the directions of other robots from perceiving their engine sounds in the absence of self-engine noise. We then extend the method to use active acoustic signaling to obtain the relative directions in the presence of self-engine noise, to increase the detection range, and to discriminate the identity of robots. Methods are evaluated in real world experiments and a fully autonomous leader-following behavior is illustrated with two drones using the proposed system

    Audio-based Localization for Swarms of Micro Air Vehicles

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    Localization is one of the key challenges that needs to be considered beforehand to design truly autonomous MAV teams. In this paper, we present a cooperative method to address the localization problem for a team of MAVs, where individuals obtain their position through perceiving a sound-emitting beacon MAV that is flying relative to a reference point in the environment. For this purpose, an on-board audio-based localization system is proposed that allows individuals to measure the relative bearing to the beacon robot and furthermore to localize themselves and the beacon robot simultaneously, without the need for a communication network. Our method is based on coherence testing among signals of a small on-board microphone array, to obtain the relative bearing measurements, and an estimator, to fuse these measurements with sensory information about the motion of the robot throughout time, to estimate robustly the MAV positions. The proposed method is evaluated both in simulation and in real world experiments

    Autonomous Feature Tracing and Adaptive Sampling in Real-World Underwater Environments

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    Applications of robots for gathering data in underwater environments has been limited due to the challenges posed by the medium. We have developed a miniature, agile, easy to carry and deploy Autonomous Underwater Vehicle (AUV) equipped with a suite of sensors for underwater environmental sensing. We have also developed a compact high resolution fast temperature sensing module for the AUV for microstructure and turbulence measurements in water bodies. In this paper, we describe a number of algorithms and subsystems of the AUV that enable autonomous real-world operation, and present the data gathered in an experimental campaign in collaboration with limnologists. We demonstrate adaptive sampling missions where the AUV could autonomously locate a zone of interest and adapt its trajectory to stay in it. Further, it could execute specific behaviors to accommodate special sensing requirements necessary to enhance the quality of the data collected. In these missions, the AUV could autonomously trace a feature and capture horizontal variation in various quantities, including turbidity and temperature fluctuations, allowing limnologists to study lake phenomena in an additional dimension

    Human-Comfortable Collision Free Navigation for Personal Aerial Vehicles

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    Semi- or fully-autonomous Personal Aerial Vehicles (PAVs) are currently studied and developed by public and private organizations as a solution for traffic congestion. While optimal collision-free navigation algorithms have been proposed for autonomous robots, trajectories and accelerations for PAVs should also take into account human comfort. In this work, we propose a reactive decentralized collision avoidance strategy that incorporates passenger physiological comfort based on the Optimal Reciprocal Collision Avoidance strategy [1]. We study in simulation the effects of increasing PAV densities on the level of comfort, on the relative flight time and on the number of collisions per flight hour and demonstrate that our strategy reduces collision risk for platforms with limited dynamic range. Finally, we validate our strategy with a swarm of 10 quadcopters flying outdoors

    Automated Real-Time Control of Fluidic Self-Assembly of Microparticles

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    Self-assembly is a key coordination mechanism for large multi-unit systems and a powerful bottom-up technology for micro/nanofabrication. Controlled self-assembly and dynamic reconfiguration of large ensembles of microscopic particles can effectively bridge these domains to build innovative systems. In this perspective, we present SelfSys, a novel platform for the automated control of the fluidic self-assembly of microparticles. SelfSys centers around a water-filled microfluidic chamber whose agitation modes, induced by a coupled ultrasonic actuator, drive the assembly. Microparticle dynamics is imaged, tracked and analyzed in real-time by an integrated software framework, which in turn algorithmically controls the agitation modes of the microchamber. The closed control loop is fully automated and can direct the stochastic assembly of microparticle clusters of preset dimension. Control issues specific to SelfSys implementation are discussed, and its potential applications presented. The SelfSys platform embodies at microscale the automated self-assembly control paradigm we first demonstrated in an earlier platform

    myCopter – Enabling Technologies for Personal Aerial Transportation Systems

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    This paper describes the European Commission Framework 7 funded project myCopter (2011-2014). The project is still at an early stage so the paper starts with the current transportation issues faced by developed countries and describes a means to solve them through the use of personal aerial transportation. The concept of personal air vehicles (PAV) is briefly reviewed and how this project intends to tackle the problem from a different perspective described. It is argued that the key reason that many PAV concepts have failed is because the operational infrastructure and socio- economic issues have not been properly addressed; rather, the start point has been the design of the vehicle itself. Some of the key aspects that would make a personal aerial transport system (PATS) viable include the required infrastructure and associated technologies, the skill levels and machine interfaces needed by the occupant or pilot and the views of society as a whole on the acceptability of such a proposition. The myCopter project will use these areas to explore the viability of PAVs within a PATS. The paper provides an overview of the project structure, the roles of the partners, and hence the available research resources, and some of the early thinking on each of the key project topic areas

    Collins and Sivers asymmetries in muonproduction of pions and kaons off transversely polarised protons

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    Measurements of the Collins and Sivers asymmetries for charged pions and charged and neutral kaons produced in semi-inclusive deep-inelastic scattering of high energy muons off transversely polarised protons are presented. The results were obtained using all the available COMPASS proton data, which were taken in the years 2007 and 2010. The Collins asymmetries exhibit in the valence region a non-zero signal for pions and there are hints of non-zero signal also for kaons. The Sivers asymmetries are found to be positive for positive pions and kaons and compatible with zero otherwise. © 2015
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