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Teleoperation systems are an important tool for performing tasks which require the sensori-motor coordination of an operator but where it is physically impossible for an operator to undertake such tasks in situ. The vast majority of these devices supply the operator with both visual and haptic sensory feedback in order that the operator can perform the task at hand as naturally and fluently as possible and as though physically present at the remote site. This thesis is concerned with overcoming the sensory limitations imposed by a fixed camera teleoperation system. The principal aim of this work is the extraction and redisplay of visual information to facilitate such a system. The thesis augments the Oxford teleoperation system with a virtual viewing module, where the operator is able to select his or her viewpoint and viewing direction onto the workcell by first tracking the locations of known objects in the workcell using a computer vision system, and then rendering them graphically on a display in front of the operator. This system, because the model-based object tracker is based around a Kalman filter, motivates the design of experiments to examine whether the operator's visuo-motor control loop maintains a state model of the manipulation process as in a Kalman filter. Experimental evidence is presented showing the latter to be false. A new operator model is then postulated using an adaptive gain controller, with the gain chosen to minimise the variance between desired and actual output. The experimental evidence supports this model. These findings support the hypothesis that the required bandwidth of the tracking filter is both i) sufficient that the tracker can robustly track hand manipulated objects and ii) matched to the visual needs of the operator.

Local active noise control systems aim to create zones of quiet at specific locations within a sound field. The created zones of quiet generally tend to be small, especially for higher frequencies, and are usually centred at the error sensors. For an observer to experience significant reductions in the noise, the error sensors therefore have to be placed relatively close to an observer’s ears, which is not always feasible or convenient. Virtual sensing methods have been proposed to overcome these problems that have limited the scope of successful local active noise control applications. These methods require non-intrusive sensors that are placed remotely from the desired locations of maximum attenuation. These non-intrusive sensors are used to provide an estimate of the sound pressures at these locations, which can then be minimised by a local active noise control system. This effectively moves the zones of quiet away from the physical locations of the transducers to the desired locations of maximum attenuation, such as a person’s ears. A number of virtual sensing algorithms have been proposed previously. The difference between these algorithms is the structure that is assumed to compute an estimate of the virtual error signals. The question now arises as to whether there is an optimal structure that can be used to solve the virtual sensing problem, which amounts to a linear estimation problem. It is well-known that the Kalman filter provides an optimal structure for solving such problems. An optimal solution to the virtual sensing problem is therefore derived in this thesis using Kalman filtering theory. The proposed algorithm is implemented on an acoustic duct arrangement to demonstrate its effectiveness. The presented experimental results indicate that the zone of quiet was effectively moved away from the physical sensor towards the desired location of maximum attenuation. The previously proposed virtual sensing algorithms have been developed with the aim to create zones of quiet at virtual locations that are assumed spatially fixed within the sound field. Because an observer is very likely to move their head, the desiredlocations of the zones of quiet are generally moving through the sound field rather than being spatially fixed. For effective control, a local active noise control system incorporating a virtual sensing method thus has to be able to create moving zones of quiet that track the observer’s ears. A moving virtual sensing method is therefore developed in this thesis that can be used to estimate the error signals at virtual locations that are moving through the sound field. It is shown that an optimal solution to the moving virtual sensing problem can be derived using Kalman filtering theory. A practical implementation of the developed algorithm is combined with an adaptive feedforward control algorithm and implemented on an acoustic duct arrangement. The presented experimental results illustrate that a narrowband moving zone of quiet that tracks the desired location of maximum attenuation has successfully been created. / http://proxy.library.adelaide.edu.au/login?url= http://library.adelaide.edu.au/cgi-bin/Pwebrecon.cgi?BBID=1291123 / Thesis (Ph.D.) -- University of Adelaide, School of Mechanical Engineering, 2007.

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Local active noise control systems aim to create zones of quiet at specific locations within a sound field. The created zones of quiet generally tend to be small, especially for higher frequencies, and are usually centred at the error sensors. For an observer to experience significant reductions in the noise, the error sensors therefore have to be placed relatively close to an observer’s ears, which is not always feasible or convenient. Virtual sensing methods have been proposed to overcome these problems that have limited the scope of successful local active noise control applications. These methods require non-intrusive sensors that are placed remotely from the desired locations of maximum attenuation. These non-intrusive sensors are used to provide an estimate of the sound pressures at these locations, which can then be minimised by a local active noise control system. This effectively moves the zones of quiet away from the physical locations of the transducers to the desired locations of maximum attenuation, such as a person’s ears. A number of virtual sensing algorithms have been proposed previously. The difference between these algorithms is the structure that is assumed to compute an estimate of the virtual error signals. The question now arises as to whether there is an optimal structure that can be used to solve the virtual sensing problem, which amounts to a linear estimation problem. It is well-known that the Kalman filter provides an optimal structure for solving such problems. An optimal solution to the virtual sensing problem is therefore derived in this thesis using Kalman filtering theory. The proposed algorithm is implemented on an acoustic duct arrangement to demonstrate its effectiveness. The presented experimental results indicate that the zone of quiet was effectively moved away from the physical sensor towards the desired location of maximum attenuation. The previously proposed virtual sensing algorithms have been developed with the aim to create zones of quiet at virtual locations that are assumed spatially fixed within the sound field. Because an observer is very likely to move their head, the desiredlocations of the zones of quiet are generally moving through the sound field rather than being spatially fixed. For effective control, a local active noise control system incorporating a virtual sensing method thus has to be able to create moving zones of quiet that track the observer’s ears. A moving virtual sensing method is therefore developed in this thesis that can be used to estimate the error signals at virtual locations that are moving through the sound field. It is shown that an optimal solution to the moving virtual sensing problem can be derived using Kalman filtering theory. A practical implementation of the developed algorithm is combined with an adaptive feedforward control algorithm and implemented on an acoustic duct arrangement. The presented experimental results illustrate that a narrowband moving zone of quiet that tracks the desired location of maximum attenuation has successfully been created. / http://proxy.library.adelaide.edu.au/login?url= http://library.adelaide.edu.au/cgi-bin/Pwebrecon.cgi?BBID=1291123 / Thesis (Ph.D.) -- University of Adelaide, School of Mechanical Engineering, 2007.

Thesis (M.A. Sc.)--University of Toronto, 2004. / Adviser: C.J. Damaren.

Thesis (Ocean E.)--Massachusetts Institute of Technology and Woods Hole Oceanographic Institution, 1994. / Includes bibliographical references (p. 90-91).

Thesis (Ph. D.)--Virginia Polytechnic Institute and State University, 1991. / Vita. Abstract. Includes bibliographical references (leaves 132-137). Also available via the Internet.

Thesis (Ph. D.)--West Virginia University, 2000. / Title from document title page. Document formatted into pages; contains ix, 151 p. : ill. (some col.). Includes abstract. Includes bibliographical references (p. 141-151).