315 resultados para Autonomous Underwater Vehicles


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100 year old gasoline engine technology vehicles have now become one of the major contributors of greenhouse gases. Plug-in Electric Vehicles (PEVs) have been proposed to achieve environmental friendly transportation. Even though the PEV usage is currently increasing, a technology breakthrough would be required to overcome battery related drawbacks. Although battery technology is evolving, drawbacks inherited with batteries such as; cost, size, weight, slower charging characteristic and low energy density would still be dominating constrains for development of EVs. Furthermore, PEVs have not been accepted as preferred choice by many consumers due to charging related issues. To address battery related limitations, the concept of dynamic Wireless Power Transfer (WPT) enabled EVs have been proposed in which EV is being charged while it is in motion. WPT enabled infrastructure has to be employed to achieve dynamic EV charging concept. The weight of the battery pack can be reduced as the required energy storage is lower if the vehicle can be powered wirelessly while driving. Stationary WPT charging where EV is charged wirelessly when it is stopped, is simpler than dynamic WPT in terms of design complexity. However, stationary WPT does not increase vehicle range compared to wired-PEVs. State-of-art WPT technology for future transportation is discussed in this chapter. Analysis of the WPT system and its performance indices are introduced. Modelling the WPT system using different methods such as equivalent circuit theory, two port network theory and coupled mode theory is described illustrating their own merits in Sect. 2.3. Both stationary and dynamic WPT for EV applications are illustrated in Sect. 2.4. Design challenges and optimization directions are analysed in Sect. 2.5. Adaptive tuning techniques such as adaptive impedance matching and frequency tuning are also discussed. A case study for optimizing resonator design is presented in Sect. 2.6. Achievements by the research community is introduced highlighting directions for future research.

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This thesis explored the utility of long-range stereo visual odometry for application on Unmanned Aerial Vehicles. Novel parameterisations and initialisation routines were developed for the long-range case of stereo visual odometry and new optimisation techniques were implemented to improve the robustness of visual odometry in this difficult scenario. In doing so, the applications of stereo visual odometry were expanded and shown to perform adequately in situations that were previously unworkable.

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There is a need for systems which can autonomously perform coverage tasks on large outdoor areas. Unfortunately, the state-of-the-art is to use GPS based localization, which is not suitable for precise operations near trees and other obstructions. In this paper we present a robotic platform for autonomous coverage tasks. The system architecture integrates laser based localization and mapping using the Atlas Framework with Rapidly-Exploring Random Trees path planning and Virtual Force Field obstacle avoidance. We demonstrate the performance of the system in simulation as well as with real world experiments.

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A system for monitoring conditions in a remote environment. The system comprising a data transmission network including a plurality of data sensing nodes. Each data sensing node includes an environment sensing means for periodically sensing the environment around node, a transmission means for periodic wireless transmission of sensed data to adjacent data sensing nodes. These adjacent data sensing nodes combining their sensed data with the received data from other data sensing nodes and on transmit the combined data.

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Underwater wireless sensor networks (UWSNs) have become the seat of researchers' attention recently due to their proficiency to explore underwater areas and design different applications for marine discovery and oceanic surveillance. One of the main objectives of each deployed underwater network is discovering the optimized path over sensor nodes to transmit the monitored data to onshore station. The process of transmitting data consumes energy of each node, while energy is limited in UWSNs. So energy efficiency is a challenge in underwater wireless sensor network. Dual sinks vector based forwarding (DS-VBF) takes both residual energy and location information into consideration as priority factors to discover an optimized routing path to save energy in underwater networks. The modified routing protocol employs dual sinks on the water surface which improves network lifetime. According to deployment of dual sinks, packet delivery ratio and the average end to end delay are enhanced. Based on our simulation results in comparison with VBF, average end to end delay reduced more than 80%, remaining energy increased 10%, and the increment of packet reception ratio was about 70%.

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We present a method for calculating odome- try in three-dimensions for car-like ground ve- hicles with an Ackerman-like steering model. In our approach we use the information from a single camera to derive the odometry in the plane and fuse it with roll and pitch informa- tion derived from an on-board IMU to extend to three-dimensions, thus providing odometric altitude as well as traditional x and y transla- tion. We have mounted the odometry module on a standard Toyota Prado SUV and present results from a car-park environment as well as from an off-road track.

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We describe our experiences with automating a large fork-lift type vehicle that operates outdoors and in all weather. In particular, we focus on the use of independent and robust localisation systems for reliable navigation around the worksite. Two localisation systems are briefly described. The first is based on laser range finders and retro-reflective beacons, and the second uses a two camera vision system to estimate the vehicle’s pose relative to a known model of the surrounding buildings. We show the results from an experiment where the 20 tonne experimental vehicle, an autonomous Hot Metal Carrier, was conducting autonomous operations and one of the localisation systems was deliberately made to fail.

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One of the main challenges facing online and offline path planners is the uncertainty in the magnitude and direction of the environmental energy because it is dynamic, changeable with time, and hard to forecast. This thesis develops an artificial intelligence for a mobile robot to learn from historical or forecasted data of environmental energy available in the area of interest which will help for a persistence monitoring under uncertainty using the developed algorithm.

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A modularized battery system with Double Star Chopper Cell (DSCC) based modular multilevel converter is proposed for a battery operated electric vehicle (EV). A design concept for the modularized battery micro-packs for DSCC is described. Multidimensional pulse width modulation (MD-PWM) with integrated inter-module SoC balancing and fault tolerant control is proposed and explained. The DSCC can be operated either as an inverter to drive the EV motor or as a synchronous rectifier connected to external three phase power supply equipment for charging the battery micro-packs. The methods of operation as inverter and synchronous rectifier with integrated inter-module SoC balancing and fault tolerant control are discussed. The proposed system operation as inverter and synchronous rectifier are verified through simulations and the results are presented.