101,602 research outputs found

    FlightGoggles: A Modular Framework for Photorealistic Camera, Exteroceptive Sensor, and Dynamics Simulation

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    FlightGoggles is a photorealistic sensor simulator for perception-driven robotic vehicles. The key contributions of FlightGoggles are twofold. First, FlightGoggles provides photorealistic exteroceptive sensor simulation using graphics assets generated with photogrammetry. Second, it provides the ability to combine (i) synthetic exteroceptive measurements generated in silico in real time and (ii) vehicle dynamics and proprioceptive measurements generated in motio by vehicle(s) in a motion-capture facility. FlightGoggles is capable of simulating a virtual-reality environment around autonomous vehicle(s). While a vehicle is in flight in the FlightGoggles virtual reality environment, exteroceptive sensors are rendered synthetically in real time while all complex extrinsic dynamics are generated organically through the natural interactions of the vehicle. The FlightGoggles framework allows for researchers to accelerate development by circumventing the need to estimate complex and hard-to-model interactions such as aerodynamics, motor mechanics, battery electrochemistry, and behavior of other agents. The ability to perform vehicle-in-the-loop experiments with photorealistic exteroceptive sensor simulation facilitates novel research directions involving, e.g., fast and agile autonomous flight in obstacle-rich environments, safe human interaction, and flexible sensor selection. FlightGoggles has been utilized as the main test for selecting nine teams that will advance in the AlphaPilot autonomous drone racing challenge. We survey approaches and results from the top AlphaPilot teams, which may be of independent interest.Comment: Initial version appeared at IROS 2019. Supplementary material can be found at https://flightgoggles.mit.edu. Revision includes description of new FlightGoggles features, such as a photogrammetric model of the MIT Stata Center, new rendering settings, and a Python AP

    AltURI: a thin middleware for simulated robot vision applications

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    Fast software performance is often the focus when developing real-time vision-based control applications for robot simulators. In this paper we have developed a thin, high performance middleware for USARSim and other simulators designed for real-time vision-based control applications. It includes a fast image server providing images in OpenCV, Matlab or web formats and a simple command/sensor processor. The interface has been tested in USARSim with an Unmanned Aerial Vehicle using two control applications; landing using a reinforcement learning algorithm and altitude control using elementary motion detection. The middleware has been found to be fast enough to control the flying robot as well as very easy to set up and use

    Agents for educational games and simulations

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    This book consists mainly of revised papers that were presented at the Agents for Educational Games and Simulation (AEGS) workshop held on May 2, 2011, as part of the Autonomous Agents and MultiAgent Systems (AAMAS) conference in Taipei, Taiwan. The 12 full papers presented were carefully reviewed and selected from various submissions. The papers are organized topical sections on middleware applications, dialogues and learning, adaption and convergence, and agent applications

    A Real-Time Communication Framework for Wireless Sensor Networks

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    Recent advances in miniaturization and low power design have led to a flurry of activity in wireless sensor networks. Sensor networks have different constraints than traditional wired networks. A wireless sensor network is a special network with large numbers of nodes equipped with embedded processors, sensors, and radios. These nodes collaborate to accomplish a common task such as environment monitoring or asset tracking. In many applications, sensor nodes will be deployed in an ad-hoc fashion without careful planning. They must organize themselves to form a multihop, wireless communication network. In sensor network environments, much research has been conducted in areas such as power consumption, self-organisation techniques, routing between the sensors, and the communication between the sensor and the sink. On the other hand, real-time communication with the Quality of Service (QoS) concept in wireless sensor networks is still an open research field. Most protocols either ignore real time or simply attempt to process as fast as possible and hope that this speed is sufficient to meet the deadline. However, the introduction of real-time communication has created additional challenges in this area. The sensor node spends most of its life routing packets from one node to another until the packet reaches the sink; therefore, the node functions as a small router most of the time. Since sensor networks deal with time-critical applications, it is often necessary for communication to meet real time constraints. However, research that deals with providing QoS guarantees for real-time traffic in sensor networks is still in its infancy.This thesis presents a real-time communication framework to provide quality of service in sensor networks environments. The proposed framework consists of four components: First, present an analytical model for implementing Priority Queuing (PQ) in a sensor node to calculate the queuing delay. The exact packet delay for corresponding classes is calculated. Further, the analytical results are validated through an extensive simulation study. Second, report on a novel analytical model based on a limited service polling discipline. The model is based on an M/D/1 queuing system (a special class of M/G/1 queuing systems), which takes into account two different classes of traffic in a sensor node. The proposed model implements two queues in a sensor node that are served in a round robin fashion. The exact queuing delay in a sensor node for corresponding classes is calculated. Then, the analytical results are validated through an extensive simulation study. Third, exhibit a novel packet delivery mechanism, namely the Multiple Level Stateless Protocol (MLSP), as a real-time protocol for sensor networks to guarantee the traffic in wireless sensor networks. MLSP improves the packet loss rate and the handling of holes in sensor network much better than its counterpart, MMSPEED. It also introduces the k-limited polling model for the first time. In addition, the whole sending packets dropped significantly compared to MMSPEED, which it leads to decrease the consumption power. Fourth, explain a new framework for moving data from the sink to the user, at a low cost and low power, using the Universal Mobile Telecommunication System (UMTS), which is standard for the Third Generation Mobile System (3G). The integration of sensor networks with the 3G mobile network infrastructure will reduce the cost of building new infrastructures and enable the large-scale deployment of sensor network

    An Energy Aware and Secure MAC Protocol for Tackling Denial of Sleep Attacks in Wireless Sensor Networks

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    Wireless sensor networks which form part of the core for the Internet of Things consist of resource constrained sensors that are usually powered by batteries. Therefore, careful energy awareness is essential when working with these devices. Indeed,the introduction of security techniques such as authentication and encryption, to ensure confidentiality and integrity of data, can place higher energy load on the sensors. However, the absence of security protection c ould give room for energy drain attacks such as denial of sleep attacks which have a higher negative impact on the life span ( of the sensors than the presence of security features. This thesis, therefore, focuses on tackling denial of sleep attacks from two perspectives A security perspective and an energy efficiency perspective. The security perspective involves evaluating and ranking a number of security based techniques to curbing denial of sleep attacks. The energy efficiency perspective, on the other hand, involves exploring duty cycling and simulating three Media Access Control ( protocols Sensor MAC, Timeout MAC andTunableMAC under different network sizes and measuring different parameters such as the Received Signal Strength RSSI) and Link Quality Indicator ( Transmit power, throughput and energy efficiency Duty cycling happens to be one of the major techniques for conserving energy in wireless sensor networks and this research aims to answer questions with regards to the effect of duty cycles on the energy efficiency as well as the throughput of three duty cycle protocols Sensor MAC ( Timeout MAC ( and TunableMAC in addition to creating a novel MAC protocol that is also more resilient to denial of sleep a ttacks than existing protocols. The main contributions to knowledge from this thesis are the developed framework used for evaluation of existing denial of sleep attack solutions and the algorithms which fuel the other contribution to knowledge a newly developed protocol tested on the Castalia Simulator on the OMNET++ platform. The new protocol has been compared with existing protocols and has been found to have significant improvement in energy efficiency and also better resilience to denial of sleep at tacks Part of this research has been published Two conference publications in IEEE Explore and one workshop paper

    Unified clustering and communication protocol for wireless sensor networks

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    In this paper we present an energy-efficient cross layer protocol for providing application specific reservations in wireless senor networks called the “Unified Clustering and Communication Protocol ” (UCCP). Our modular cross layered framework satisfies three wireless sensor network requirements, namely, the QoS requirement of heterogeneous applications, energy aware clustering and data forwarding by relay sensor nodes. Our unified design approach is motivated by providing an integrated and viable solution for self organization and end-to-end communication is wireless sensor networks. Dynamic QoS based reservation guarantees are provided using a reservation-based TDMA approach. Our novel energy-efficient clustering approach employs a multi-objective optimization technique based on OR (operations research) practices. We adopt a simple hierarchy in which relay nodes forward data messages from cluster head to the sink, thus eliminating the overheads needed to maintain a routing protocol. Simulation results demonstrate that UCCP provides an energy-efficient and scalable solution to meet the application specific QoS demands in resource constrained sensor nodes. Index Terms — wireless sensor networks, unified communication, optimization, clustering and quality of service

    Big Data Model Simulation on a Graph Database for Surveillance in Wireless Multimedia Sensor Networks

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    Sensors are present in various forms all around the world such as mobile phones, surveillance cameras, smart televisions, intelligent refrigerators and blood pressure monitors. Usually, most of the sensors are a part of some other system with similar sensors that compose a network. One of such networks is composed of millions of sensors connect to the Internet which is called Internet of things (IoT). With the advances in wireless communication technologies, multimedia sensors and their networks are expected to be major components in IoT. Many studies have already been done on wireless multimedia sensor networks in diverse domains like fire detection, city surveillance, early warning systems, etc. All those applications position sensor nodes and collect their data for a long time period with real-time data flow, which is considered as big data. Big data may be structured or unstructured and needs to be stored for further processing and analyzing. Analyzing multimedia big data is a challenging task requiring a high-level modeling to efficiently extract valuable information/knowledge from data. In this study, we propose a big database model based on graph database model for handling data generated by wireless multimedia sensor networks. We introduce a simulator to generate synthetic data and store and query big data using graph model as a big database. For this purpose, we evaluate the well-known graph-based NoSQL databases, Neo4j and OrientDB, and a relational database, MySQL.We have run a number of query experiments on our implemented simulator to show that which database system(s) for surveillance in wireless multimedia sensor networks is efficient and scalable
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