945 resultados para Vehicles submergibles -- Sistemes de control


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We present a novel, simple and effective approach for tele-operation of aerial robotic vehicles with haptic feedback. Such feedback provides the remote pilot with an intuitive feel of the robot’s state and perceived local environment that will ensure simple and safe operation in cluttered 3D environments common in inspection and surveillance tasks. Our approach is based on energetic considerations and uses the concepts of network theory and port-Hamiltonian systems. We provide a general framework for addressing problems such as mapping the limited stroke of a ‘master’ joystick to the infinite stroke of a ‘slave’ vehicle, while preserving passivity of the closed-loop system in the face of potential time delays in communications links and limited sensor data

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This paper proposes the use of optical flow from a moving robot to provide force feedback to an operator's joystick to facilitate collision free teleoperation. Optic flow is measured by wide angle cameras on board the vehicle and used to generate a virtual environmental force that is reflected to the user through the joystick, as well as feeding back into the control of the vehicle. The coupling between optical flow (velocity) and force is modelled as an impedance - in this case an optical impedance. We show that the proposed control is dissipative and prevents the vehicle colliding with the environment as well as providing the operator with a natural feel for the remote environment. The paper focuses on applications to aerial robotics vehicles, however, the ideas apply directly to other force actuated vehicles such as submersibles or space vehicles, and the authors believe the approach has potential for control of terrestrial vehicles and even teleoperation of manipulators. Experimental results are provided for a simulated aerial robot in a virtual environment controlled by a haptic joystick.

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Fast thrust changes are important for authoritive control of VTOL micro air vehicles. Fixed-pitch rotors that alter thrust by varying rotor speed require high-bandwidth control systems to provide adequate performace. We develop a feedback compensator for a brushless hobby motor driving a custom rotor suitable for UAVs. The system plant is identified using step excitation experiments. The aerodynamic operating conditions of these rotors are unusual and so experiments are performed to characterise expected load disturbances. The plant and load models lead to a proportional controller design capable of significantly decreasing rise-time and propagation of disturbances, subject to bus voltage constraints.

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This paper describes an autonomous navigation system for a large underground mining vehicle. The control architecture is based on a robust reactive wall-following behaviour. To make it purposeful we provide driving hints derived from an approximate nodal-map. For most of the time, the vehicle is driven with weak localization (odometry). This need only be improved at intersections where decisions must be made – a technique we refer to as opportunistic localization. The paper briefly reviews absolute and relative navigation strategies, and describes an implementation of a reactive navigation system on a 30 tonne Load-Haul-Dump truck. This truck has achieved full-speed autonomous operation at an artificial test mine, and subsequently, at a operational underground mine.

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This paper considers the question of designing a fully image-based visual servo control for a class of dynamic systems. The work is motivated by the ongoing development of image-based visual servo control of small aerial robotic vehicles. The kinematics and dynamics of a rigid-body dynamical system (such as a vehicle airframe) maneuvering over a flat target plane with observable features are expressed in terms of an unnormalized spherical centroid and an optic flow measurement. The image-plane dynamics with respect to force input are dependent on the height of the camera above the target plane. This dependence is compensated by introducing virtual height dynamics and adaptive estimation in the proposed control. A fully nonlinear adaptive control design is provided that ensures asymptotic stability of the closed-loop system for all feasible initial conditions. The choice of control gains is based on an analysis of the asymptotic dynamics of the system. Results from a realistic simulation are presented that demonstrate the performance of the closed-loop system. To the author's knowledge, this paper documents the first time that an image-based visual servo control has been proposed for a dynamic system using vision measurement for both position and velocity.

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Maintenance trains travel in convoy. In Australia, only the first train of the convoy pays attention to the track sig- nalization (the other convoy vehicles simply follow the preceding vehicle). Because of human errors, collisions can happen between the maintenance vehicles. Although an anti-collision system based on a laser distance meter is already in operation, the existing system has a limited range due to the curvature of the tracks. In this paper, we introduce an anti-collision system based on vision. The two main ideas are, (1) to warp the camera image into an image where the rails are parallel through a projective transform, and (2) to track the two rail curves simultaneously by evaluating small parallel segments. The performance of the system is demonstrated on an image dataset.

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The following paper proposes a novel application of Skid-to-Turn maneuvers for fixed wing Unmanned Aerial Vehicles (UAVs) inspecting locally linear infrastructure. Fixed wing UAVs, following the design of manned aircraft, commonly employ Bank-to-Turn ma- neuvers to change heading and thus direction of travel. Whilst effective, banking an aircraft during the inspection of ground based features hinders data collection, with body fixed sen- sors angled away from the direction of turn and a panning motion induced through roll rate that can reduce data quality. By adopting Skid-to-Turn maneuvers, the aircraft can change heading whilst maintaining wings level flight, thus allowing body fixed sensors to main- tain a downward facing orientation. An Image-Based Visual Servo controller is developed to directly control the position of features as captured by onboard inspection sensors. This improves on the indirect approach taken by other tracking controllers where a course over ground directly above the feature is assumed to capture it centered in the field of view. Performance of the proposed controller is compared against that of a Bank-to-Turn tracking controller driven by GPS derived cross track error in a simulation environment developed to replicate the field of view of a body fixed camera.

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Traffic control at road junctions is one of the major concerns in most metropolitan cities. Controllers of various approaches are available and the required control action is the effective green-time assigned to each traffic stream within a traffic-light cycle. The application of fuzzy logic provides the controller with the capability to handle uncertain natures of the system, such as drivers’ behaviour and random arrivals of vehicles. When turning traffic is allowed at the junction, the number of phases in the traffic-light cycle increases. The additional input variables inevitably complicate the controller and hence slow down the decision-making process, which is critical in this real-time control problem. In this paper, a hierarchical fuzzy logic controller is proposed to tackle this traffic control problem at a 2-way road junction with turning traffic. The two levels of fuzzy logic controllers devise the minimum effective green-time and fine-tune it respectively at each phase of a traffic-light cycle. The complexity of the controller at each level is reduced with smaller rule-set. The performance of this hierarchical controller is examined by comparison with a fixed-time controller under various traffic conditions. Substantial delay reduction has been achieved as a result and the performance and limitation of the controller will be discussed.

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The Transport Certification Australia on-board mass feasibility project is testing various on-board mass devices in a range of heavy vehicles (HVs). Extensive field tests of on-board mass measurement systems for HVs have been conducted during 2008. These tests were of accuracy, robustness and tamper-evidence of heavy vehicle on-board mass telematics. All the systems tested showed accuracies within approximately +/- 500 kg of gross combination mass or approximately +/- 2% of the attendant weighbridge reading. Analysis of the dynamic data also showed encouraging results and has raised the possibility of use of such dynamic information in tamper evidence in two areas. This analysis was to determine if the use of averaged dynamic data could identify potential tampering or incorrect operating procedures as well as the possibility of dynamic measurements flagging a tamper event by the use of metrics including a tampering index (TIX). Technical and business options to detect tamper events will now be developed during implementation of regulatory OBM system application to Australian heavy vehicles (HVs).

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Designing trajectories for a submerged rigid body motivates this paper. Two approaches are addressed: the time optimal approach and the motion planning ap- proach using concatenation of kinematic motions. We focus on the structure of singular extremals and their relation to the existence of rank-one kinematic reduc- tions; thereby linking the optimization problem to the inherent geometric frame- work. Using these kinematic reductions, we provide a solution to the motion plan- ning problem in the under-actuated scenario, or equivalently, in the case of actuator failures. We finish the paper comparing a time optimal trajectory to one formed by concatenation of pure motions.

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Autonomous underwater vehicles (AUVs) are increasingly used, both in military and civilian applications. These vehicles are limited mainly by the intelligence we give them and the life of their batteries. Research is active to extend vehicle autonomy in both aspects. Our intent is to give the vehicle the ability to adapt its behavior under different mission scenarios (emergency maneuvers versus long duration monitoring). This involves a search for optimal trajectories minimizing time, energy or a combination of both. Despite some success stories in AUV control, optimal control is still a very underdeveloped area. Adaptive control research has contributed to cost minimization problems, but vehicle design has been the driving force for advancement in optimal control research. We look to advance the development of optimal control theory by expanding the motions along which AUVs travel. Traditionally, AUVs have taken the role of performing the long data gathering mission in the open ocean with little to no interaction with their surroundings, MacIver et al. (2004). The AUV is used to find the shipwreck, and the remotely operated vehicle (ROV) handles the exploration up close. AUV mission profiles of this sort are best suited through the use of a torpedo shaped AUV, Bertram and Alvarez (2006), since straight lines and minimal (0 deg - 30 deg) angular displacements are all that are necessary to perform the transects and grid lines for these applications. However, the torpedo shape AUV lacks the ability to perform low-speed maneuvers in cluttered environments, such as autonomous exploration close to the seabed and around obstacles, MacIver et al. (2004). Thus, we consider an agile vehicle capable of movement in six degrees of freedom without any preference of direction.

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From Pontryagin’s Maximum Principle to the Duke Kahanamoku Aquatic Complex; we develop the theory and generate implementable time efficient trajectories for a test-bed autonomous underwater vehicle (AUV). This paper is the beginning of the journey from theory to implementation. We begin by considering pure motion trajectories and move into a rectangular trajectory which is a concatenation of pure surge and pure sway. These trajectories are tested using our numerical model and demonstrated by our AUV in the pool. In this paper we demonstrate that the above motions are realizable through our method, and we gain confidence in our numerical model. We conclude that using our current techniques, implementation of time efficient trajectories is likely to succeed.

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In this paper, we are concerned with the practical implementation of time optimal numerical techniques on underwater vehicles. We briefly introduce the model of underwater vehicle we consider and present the parameters for the test bed ODIN (Omni-Directional Intelligent Navigator). Then we explain the numerical method used to obtain time optimal trajectories with a structure suitable for the implementation. We follow this with a discussion on the modifications to be made considering the characteristics of ODIN. Finally, we illustrate our computations with some experimental results.

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While using unmanned systems in combat is not new, what will be new in the foreseeable future is how such systems are used and integrated in the civilian space. The potential use of Unmanned Aerial Vehicles in civil and commercial applications is becoming a fact, and is receiving considerable attention by industry and the research community. The majority of Unmanned Aerial Vehicles performing civilian tasks are restricted to flying only in segregated space, and not within the National Airspace. The areas that UAVs are restricted to flying in are typically not above populated areas, which in turn are the areas most useful for civilian applications. The reasoning behind the current restrictions is mainly due to the fact that current UAV technologies are not able to demonstrate an Equivalent Level of Safety to manned aircraft, particularly in the case of an engine failure which would require an emergency or forced landing. This chapter will preset and guide the reader through a number of developments that would facilitate the integration of UAVs into the National Airspace. Algorithms for UAV Sense-and-Avoid and Force Landings are recognized as two major enabling technologies that will allow the integration of UAVs in the civilian airspace. The following sections will describe some of the techniques that are currently being tested at the Australian Research Centre for Aerospace Automation (ARCAA), which places emphasis on the detection of candidate landing sites using computer vision, the planning of the descent path trajectory for the UAV, and the decision making process behind the selection of the final landing site.

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A forced landing is an unscheduled event in flight requiring an emergency landing, and is most commonly attributed to engine failure, failure of avionics or adverse weather. Since the ability to conduct a successful forced landing is the primary indicator for safety in the aviation industry, automating this capability for unmanned aerial vehicles (UAVs) will help facilitate their integration into, and subsequent routine operations over civilian airspace. Currently, there is no commercial system available to perform this task; however, a team at the Australian Research Centre for Aerospace Automation (ARCAA) is working towards developing such an automated forced landing system. This system, codenamed Flight Guardian, will operate onboard the aircraft and use machine vision for site identification, artificial intelligence for data assessment and evaluation, and path planning, guidance and control techniques to actualize the landing. This thesis focuses on research specific to the third category, and presents the design, testing and evaluation of a Trajectory Generation and Guidance System (TGGS) that navigates the aircraft to land at a chosen site, following an engine failure. Firstly, two algorithms are developed that adapts manned aircraft forced landing techniques to suit the UAV planning problem. Algorithm 1 allows the UAV to select a route (from a library) based on a fixed glide range and the ambient wind conditions, while Algorithm 2 uses a series of adjustable waypoints to cater for changing winds. A comparison of both algorithms in over 200 simulated forced landings found that using Algorithm 2, twice as many landings were within the designated area, with an average lateral miss distance of 200 m at the aimpoint. These results present a baseline for further refinements to the planning algorithms. A significant contribution is seen in the design of the 3-D Dubins Curves planning algorithm, which extends the elementary concepts underlying 2-D Dubins paths to account for powerless flight in three dimensions. This has also resulted in the development of new methods in testing for path traversability, in losing excess altitude, and in the actual path formation to ensure aircraft stability. Simulations using this algorithm have demonstrated lateral and vertical miss distances of under 20 m at the approach point, in wind speeds of up to 9 m/s. This is greater than a tenfold improvement on Algorithm 2 and emulates the performance of manned, powered aircraft. The lateral guidance algorithm originally developed by Park, Deyst, and How (2007) is enhanced to include wind information in the guidance logic. A simple assumption is also made that reduces the complexity of the algorithm in following a circular path, yet without sacrificing performance. Finally, a specific method of supplying the correct turning direction is also used. Simulations have shown that this new algorithm, named the Enhanced Nonlinear Guidance (ENG) algorithm, performs much better in changing winds, with cross-track errors at the approach point within 2 m, compared to over 10 m using Park's algorithm. A fourth contribution is made in designing the Flight Path Following Guidance (FPFG) algorithm, which uses path angle calculations and the MacCready theory to determine the optimal speed to fly in winds. This algorithm also uses proportional integral- derivative (PID) gain schedules to finely tune the tracking accuracies, and has demonstrated in simulation vertical miss distances of under 2 m in changing winds. A fifth contribution is made in designing the Modified Proportional Navigation (MPN) algorithm, which uses principles from proportional navigation and the ENG algorithm, as well as methods specifically its own, to calculate the required pitch to fly. This algorithm is robust to wind changes, and is easily adaptable to any aircraft type. Tracking accuracies obtained with this algorithm are also comparable to those obtained using the FPFG algorithm. For all three preceding guidance algorithms, a novel method utilising the geometric and time relationship between aircraft and path is also employed to ensure that the aircraft is still able to track the desired path to completion in strong winds, while remaining stabilised. Finally, a derived contribution is made in modifying the 3-D Dubins Curves algorithm to suit helicopter flight dynamics. This modification allows a helicopter to autonomously track both stationary and moving targets in flight, and is highly advantageous for applications such as traffic surveillance, police pursuit, security or payload delivery. Each of these achievements serves to enhance the on-board autonomy and safety of a UAV, which in turn will help facilitate the integration of UAVs into civilian airspace for a wider appreciation of the good that they can provide. The automated UAV forced landing planning and guidance strategies presented in this thesis will allow the progression of this technology from the design and developmental stages, through to a prototype system that can demonstrate its effectiveness to the UAV research and operations community.