Procedural animation systems are capable of synthesising life-like organic motion automatically. However, due to extensive parameterisation, tuning these systems can be very difficult. Not only are there potentially hundreds of interlinked parameters, the resultant animation can be very subjective and the process is difficult to automate effectively. In this paper, we describe a crowd-sourced approach to procedural animation parameter optimisation using genetic algorithms. We test our approach by asking users to interactively rate a population of virtual dolphins to a prescribed behavioural criterion. Our results show that within a few generations a group of users can successfully tune the system towards a desired behaviour. Our secondary motivation is to investigate whether there are differences in animation and behavioural preference between observations made using a standard desktop monitor and those made in virtual reality (VR). We describe a study where users tuned two sets of dolphin animation systems in parallel, one using a normal monitor and another using an Oculus Rift. Our results indicate that being immersed in VR leads to some key differences in preferred behaviour.

Procedural animation systems are capable of synthesising life-like organic motion automatically. However due to extensive parameterisation, tuning these systems can be very difficult. Not only are there potentially hundreds of interlinked parameters, the resultant animation can be very subjective and the process is difficult to automate effectively.In this paper we describe a crowd-sourced approach to procedural animation parameter optimisation using genetic algorithms. We test our approach by asking users to interactively rate a population of virtual dolphins to a prescribed behavioural criteria. Our results show that within a few generations a group of users can successfully tune the system toward a desired behaviour.Our secondary motivation is to investigate if there are differences in animation and behavioural preference between observations made using a standard desktop monitor and those made using Virtual Reality (VR). We describe a study where users tuned two sets of dolphin animation systems in parallel, one using a normal monitor and another using an Oculus Rift. Our results indicate that being immersed in VR leads to some key differences in preferred behaviour.

Procedural animation systems are capable of synthesizing vivid organic character motion automatically. However, these systems can consist of hundreds of interlinked parameters, yielding a very large search space of potential animations and emergent behaviours. Parametrised Animation is also notoriously difficult to automatically optimise, as the resultant motion or behaviour can be subtle, complex and subjective. We describe a web-based simulation that enables multiple users to interactively rate the animation of a randomly generated population of virtual creatures based on a prescribed criteria. A record of each individual rating is stored and used to seed subsequent generations, thereby guiding the system towards exhibiting a desired type of motion or behaviour. We start by introducing issues inherent to procedural animation techniques and survey related work. We then describe our prototype implementation that allows multiple users to interactively shape the parameters of a snake-like animation system in real-time. We conclude by discussing the next steps of our research, including the optimisation of procedurally animated dolphins.

Work in progress for the development of a novel virtual training environment for training a kidney biopsy procedure is presented. Our goal is to provide an affordable high fidelity simulation through the integration of some of the latest off-the-shelf technology components. The range of forces that are encountered during this procedure have been recorded using a custom designed force sensitive glove and then applied within the simulation.