35 resultados para 290301 Robotics and Mechatronics

em Deakin Research Online - Australia


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Underwater swarm robotics today faces a series of challenges unique to its aquatic environment. This chapter explores some possible applications of underwater swarm robotics and its challenges. Those challenges include the environment itself, sensor types required, problems with communication and the difficulty in localisation. it notes the serious challenges in underwater communication is that radio communications is practically non-existent in the underwater realm. Localisation also becomes problematic due to the lack of radio waves as GPS cannot be used. it also looks at the platforms required by underwater robots and includes a possible low-cost platform. Also explored is a method of swarm robotics control known as consensus control. It shows possible solutions to the challenges and where swarm robotics may head.

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In 2005 the Sloan Consortium called for engineering education to be available "anywhere, anytime."* Increasing numbers of engineering departments are interesting in offering their programs by means of online learning. These schools grapple with several difficulties and issues associated with wholly online learning: course structure, communication with students, delivery of course material, delivery of exams, accreditation, equity between on-campus and off-campusstudents, and especially the delivery of practical training. Deakin University faced these same challenges when it commenced teaching undergraduate engineering via distance education in the early 1990's. It now offers a fully accredited Bachelor of Engineering degree in both on-campus and off-campus modes, with majors that include civil,mechanical, electrical/electronics, and mechatronics/robotics.This presentation describes Deakin's unique off-campus delivery, students, curricula, approaches to practical work, and solutions to the problems mentioned above. Attendees will experience how Deakin Engineering delivers course materials, communicates with off-campus students, runs off-campus classes, and even delivers lab experience to students living thousands of miles away from the home campus. On display will be experimental lab kits, video presentations, student projects, and online broadcasts of freshman lab experiments. Participants will have the opportunity to see some of these resources hands-on. I will also discuss recent innovations in off-campus delivery ofcourses, including how flipping the classroom has led to blended learning with the on-campus students.Many universities have placed engineering distance education into the too-hard basket. Deakin Engineering demonstrates that it is possible to deliver a full undergraduate degree by means of distance education and online learning, and modern technology makes the job easier than everbefore. The benefits to the professor are many, not the least of which is helping a student living in a remote area or with a full-time job become fully trained and qualified in engineering.

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Control of tele-operated remote robot’s is nothing new; the public was introduced to this 'new' field in 1986 when the Chernobyl cleanup began. Pictures of weird and wonderful robotic workers pouring concrete or moving rubble flooded the world. Integration of force feedback or 'haptics' to remote robot's is a new development and one that is likely to make a big difference in man-machine interaction. Development of haptic capable tele-operation schema is a challenge. Often platform specific software is developed for one off tasks. This research focussed on the development of an open software platform for haptic control of multiple remote robotic platforms. The software utilises efficient server/client architecture for low data latency, while efficiently performing required kinematic transforms and data manipulation in real time. A description of the algorithm, software interface and hardware is presented in this paper. Preliminary results are encouraging as haptic control has been shown to greatly enhances remote positioning tasks.

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This paper presents an efficient technique to design dynamic feedback control scheme for single-link flexible manipulators.  A linear model can be derived for the robotic system using the assumed-mode method.  Conventional techniques such as pole-placement or LQR require physical measurements of all systme states,  posing a stringent requirement for its implementation.  To overcome this problem, a low-order state functional observer is proposed here for reconstruction of the state feedback control action.  The observer design involves solving an optimisation problem with the objective to generate a feedback gain that is as close as possible to that of the required feedback controller.  A condition for robust stability of the closed-loop system under the observer-based control scheme is given.  The attractive features of the propsed technique are the resulted functional state observer is of a very low order and it requires only sensor measurements of only the output- the tip position of the arm.

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The design of locally optimal fault-tolerant manipulators has been previously addressed via adding constraints on the bases of a desired null space to the design constraints of the manipulators. Then by algebraic or numeric solution of the design equations, the optimal Jacobian matrix is obtained. In this study, an optimal fault-tolerant Jacobian matrix generator is introduced from geometric properties instead of the null space properties. The proposed generator provides equally fault-tolerant Jacobian matrices in R3 that are optimally fault tolerant for one or two locked joint failures. It is shown that the proposed optimal Jacobian matrices are directly obtained via regular pyramids. The geometric approach and zonotopes are used as a novel tool for determining relative manipulability in the context of fault-tolerant robotics and for bringing geometric insight into the design of optimal fault-tolerant manipulators.

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Laboratory practicals form an essential component in any electronics or electrical engineering course. Many students choose to study engineering by means of distance education. Providing such students with effective and manageable practical experience has always been a significant challenge for those involved in providing distance education. Our university has employed an experimental electronics kit for teaching laboratory skills to distance-education students over the past several years. The chief limitation of the early kit was the inability to use it for performing AC experiments without an additional AC signal generator and an oscilloscope. We now supply distance-education students with the original components pack, and an additional “HELP” kit which contains the signal generator, PC-oscilloscope, a basic multimeter, logic probe, software and documentation. The combined kits allow these students to perform basic DC and AC electronics experiments at home in both freshman and sophomore electronics courses. A more recent development is introducing a small robot platform intended to enhance the student experience and interest in electronics and mechatronics, while still covering the basic skills necessary for the engineer-in-training. Distance-education students receive an updated experimental kit containing the robot, other equipment and components to allow them to complete a fuller suite of practical exercises in electronics in their first two years of study. Within this paper, we present these developments in our HELP kit and also make comparisons between on-campus and off-campus performance.

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The problem of 3D object recognition is of immense practical importance, with the last decade witnessing a number of breakthroughs in the state of the art. Most of the previous work has focused on the matching of textured objects using local appearance descriptors extracted around salient image points. The recently proposed bag of boundaries method was the first to address directly the problem of matching smooth objects using boundary features. However, no previous work has attempted to achieve a holistic treatment of the problem by jointly using textural and shape features which is what we describe herein. Due to the complementarity of the two modalities, we fuse the corresponding matching scores and learn their relative weighting in a data specific manner by optimizing discriminative performance on synthetically distorted data. For the textural description of an object we adopt a representation in the form of a histogram of SIFT based visual words. Similarly the apparent shape of an object is represented by a histogram of discretized features capturing local shape. On a large public database of a diverse set of objects, the proposed method is shown to outperform significantly both purely textural and purely shape based approaches for matching across viewpoint variation.

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Increasing numbers of engineering departments are interested in offering their programs by distanceeducation. These schools grabble with several difficulties and issues associated with distance education:course structure, communication with students, delivery of course material, delivery of exams,accreditation, equity between on-campus and off-campus students, and especially the delivery ofpractical training.In the early 1990’s, Deakin University faced these same problems when it commenced teachingundergraduate engineering by distance education. It now offers a full Bachelor of Engineering degreein both on-campus and off-campus mode, with majors that include civil, mechanical,electrical/electronics, and mechatronics. Student cohorts are approximately 72% on-campus, 28% offcampus.Accredited by Engineers Australia and part of the Washington Accord, Deakin has adapted toadvances in communications technology and changes in education design. The future direction of theSchool includes an emphasis on design-oriented, project-based learning and “flipping the classroom”.As a result, differences between the more traditional off-campus and on-campus cohorts are becomingincreasingly blurred.

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In order to develop a robotic system of systems the robotic platforms must be designed and built. For this to happen, the type of application involved should be clear. Swarm robots need to be self contained and powered. They must also be self governing. Here the authors examine various applications and a prototype robot that may be useful in these scenarios.

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Flowcharting is a common method of setting out the requirements for a piece of code. It is simple with few rules to follow. Rarely however, s it used as the code itself. This paper describes the outline of a software package that uses the flowchart as the code for a small, autonomous, modular robot, designed for use in High Schools. It also describe the code used by the robot to complement the flowchart software creating a system that can be used by students and their teachers to design, build and program a robot without previous programming experience.

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A continued increase in computing power, sensor capability, software functionality, immersive interfaces and hardware modularity has given robot designers seemingly endless potential in the area of mobile robotics.  While some mobile robotic system designers are focusing on expensive, full-featured platforms, developers are realising the advantages of emerging technology in providing small, low-cost mobile reconnaissance vehicles as expendable teleoperated robotic systems.  The OzBotTM mobile reconnaissance platform presents one such system.  The design objectives of the OzBotTM platform focus on the development of inexpensive, lightweight carry-case sized robots for search and rescue operations, law enforcement scenarios and hazardous environment inspection.  The incorporation of Haptic augmentation provides the teleoperator with improved task immersion for an outdoor search and rescue scenario.  Achieved in cooperation with law enforcement agencies within Australia, this paper discusses the performance of the first four revisions of the OzBotTM platform.

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This paper presents an application of Microsoft Robotics Studio (MSRS) in which a team of six four wheel drive, ground based robots explore and map simulated terrain. The user has the ability to modify the terrain and assign destination objectives to the team while the simulation is running. The terrain is initially generated using a gray scale image, in which the intensity of each pixel in the image gives an altitude datum. The robots start with no knowledge of their surroundings, and map the terrain as they attempt to reach user-defined target objectives. The mapping process simulates the use of common sensory hardware to determine datum points, including provision for field of view, detection range, and measurement accuracy. If traversal of a mapped area is indicated by the users’ targeting commands, path planning heuristics developed for MSRS by the author in earlier work are used to determine an efficient series of waypoints to reach the objective. Mutability of terrain is also explored- the user is able to modify the terrain without stopping the simulation. This forces the robots to adapt to changing environmental conditions, and permits analysis of the robustness of mapping algorithms used when faced with a changing world.