Motion simulators

Motion simulation research can lead to all manner of projects – from live performance to measuring brain activity.

At IISRI, we apply our research to a range of industry needs. We can create programs that assess ergonomics on assembly lines and design programs that identify people by their heartbeat. Motion simulation is a vast arena of innovation that can be adopted to make life-altering changes across the world.

The motion notion

Our Motion Simulation Lab is home to a range of mobile and industrial robots. We also developed the haptically enabled Universal Motion Simulator (UMS) – a flexible, high-fidelity motion system for dynamic, immersive training.

The UMS represents the next generation in vehicle simulation, featuring a far greater range of motion, greater flexibility and more realism.

Dr Kyle Nelson – virtual motion master

IISRI's world-leading Universal Motion Simulator (UMS) is next-generation technology and Dr Kyle Nelson is Deakin's lead UMS engineer.

The gigantic robotic arm of the UMS delivers realistic accelerations and manoeuvres at high speeds in any direction, taking users on the ultimate, self-directed simulated journey.

This high-tech simulation is saving the aircraft, defence and automotive industries serious capital. The UMS is being increasingly used by designers and engineers to test new vehicle designs long before the innovations ever hit the production line.

'Once we load in the specifications of a particular vehicle type, the UMS can create the sensation and types of motion that drivers would experience if they were in the actual vehicle,' Dr Nelson explained.

Read more about the UMS

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Research topics

World-Class Universal Motion Simulator (UMS)

The UMS is the first haptically-enabled robot-based motion simulator in the world. It is a motion simulator that gives a realistic sense of motion without causing simulator sickness. The UMS allows the subject to experience situations in their entirety including a full range of motion that can be adjusted to suit many forms of training which are not capable in reality.

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Human performance measures in interactive virtual training systems

World-leading operations are increasingly relying on modelling and simulation to develop more efficient systems to produce higher quality products and services. Modelling and simulation allows scientists and engineers to better understand 3D and time-dependent phenomena, as well as providing a platform for predicting future behaviour. Virtual training  systems using advanced virtual reality technology are important in areas such as aerospace, engineering, medicine and education. This research examines ways to evaluate the efficiency of such technology, while altering technology design to achieve more effective learning outcomes.

Image fusion algorithm and metric duality index

Current image fusion metrics fail to suit all fusion algorithms as some need to be evaluated with specially designed metrics. Using counter examples, this research identifies the compatibility challenges facing image fusion metrics with respect to a certain fusion algorithm.

Colour map and histogram fusion

The main objective of multi-domain image fusion is to incorporate captured information from sensors observing certain phenomena from different viewpoints. This allows the observer to understand the whole situation.

Optimal multi-sensor data fusion

Multi-sensor data fusion refers to the process of combining data from different resources to improve the quality of information and accuracy of measurements. It is used in a range of applications, including smart buildings, bridges and satellites. The main challenge with multi-sensor data fusion is that it is highly dependent on the quality of measurements obtained from each sensor. Since these sensors operate in real environments, there is no guarantee the outputs of the sensors are accurate. This research aims to incorporate the possibility of missing measurements in the data fusion process and obtain the optimal data fusion for systems which have this problem.

Robust filtering for uncertain systems

This research addresses the problem of system modelling when the system under consideration suffers from uncertainties. It also provides the design of a new filter that allows for the optimal filtering of systems under uncertainties without prior knowledge about the uncertainty values.

Robust rapid MRI

Despite the advantages of MRI (Magnetic Resonance Imaging) machines, they come along with problems. The MRI scanning process is time-consuming and sensitive to movements, which may cause the patient having to repeat the scan. This research investigates how to increase the speed of the MRI scanning process using a novel measurement sampling technique. This technique guarantees the minimum number of acquired measurements without compromising the scan quality.

3D sparse-feature model using short-baseline stereo and multiple view registration

This research investigates a method for generating a distinctive object representation offline. IISRI are using short-baseline stereo fundamentals to triangulate highly descriptive object features in multiple pairs of stereo images.

Intelligent 3D programmable surface

Creating a highly programmable surface operating in real-time at a relatively high speed presents many challenges. This research investigates various system designs, modularity, programmability and system control intelligence. Such a system has applications in the field of optical telescopes, product manufacturing, and 3D-screens and billboards for advertising and artwork.

Vox Lumen – motion simulation in dance

As part of Melbourne’s White Night 2015, Vox Lumen: People into Light transformed Federation Square into an interactive world. It involved stunning abstract digital projections, dancer-driven live motion capture, and interactive content that tracked the movement of crowds across Melbourne's biggest night of arts and culture. The event was a combination of live performance and audience interactivity.

The fusion of live performance and technology featured dancer/choreographer Steph Hutchison, who wore IISRI's high-tech Xsens motion capture suit. 

This marker-less, full-body suit allows researchers to go mobile, taking a technology that is usually limited to a commercial lab setting into the heart of the city. The inertial-based suit measures the movement of the dancer using an internal gyroscope, so that every movement directly affects the content on the screen.

Read more about Vox Lumen