A System for Real-Time Deformable Terrain

Terrain constitutes an important part of many virtual environments. In computer games or simulations it is often useful to allow the user to modify the terrain since this can help to foster immersion. Unfortunately, real-time deformation schemes can be expensive and most game engines simply substitute proxy geometry or use texturing to create the illusion of deformation. We present a new terrain deformation framework which is able to produce persistent, real-time deformation by utilising the capabilities of current generation GPUs. Our method utilises texture storage, a terrain level-of-detail scheme and a tile-based terrain representation to achieve high frame rates. To accommodate a range of hardware, we provide deformation schemes for hardware with and without geometry tessellation units. Deformation using the fragment shader (no tessellation) is significantly faster than the geometry shader (tessellation) approach, although this does come at the cost of some high resolution detail. Our tests show that both deformation schemes consume a comparatively small proportion of the GPU per frame budget and can thus be integrated into more complex virtual environments

Fast Simulation of Vehicles with Non-deformable Tracks

This paper presents a novel technique that allows for both computationally fast and sufficiently plausible simulation of vehicles with non-deformable tracks. The method is based on an effect we have called Contact Surface Motion. A comparison with several other methods for simulation of tracked vehicle dynamics is presented with the aim to evaluate methods that are available off-the-shelf or with minimum effort in general-purpose robotics simulators. The proposed method is implemented as a plugin for the open-source physics-based simulator Gazebo using the Open Dynamics Engine.Comment: Submitted to IROS 201

A perception and manipulation system for collecting rock samples

An important part of a planetary exploration mission is to collect and analyze surface samples. As part of the Carnegie Mellon University Ambler Project, researchers are investigating techniques for collecting samples using a robot arm and a range sensor. The aim of this work is to make the sample collection operation fully autonomous. Described here are the components of the experimental system, including a perception module that extracts objects of interest from range images and produces models of their shapes, and a manipulation module that enables the system to pick up the objects identified by the perception module. The system was tested on a small testbed using natural terrain

Tractable robot simulation for terrain leveling

This thesis describes the problem of terrain leveling, in which one or more robots or vehicles are used to atten a terrain. The leveling operation is carried out either in preparation for construction, or for terrain reparation. In order to develop and prototype such a system, the use of simulation is advantageous. Such a simulation requires high fidelity to accurately model earth moving robots, which navigate uneven terrain and potentially manipulate the terrain itself. It has been found that existing tools for robot simulation typically do not adequately model deformable and/or uneven terrain. Software which does exist for this purpose, based on a traditional physics engine, is difficult if not impossible to run in real-time while achieving the desired accuracy. A number of possible approaches are proposed for a terrain leveling system using autonomous mobile robots. In order to test these approaches in simulation, a 2D simulator called Alexi has been developed, which uses the predictions of a neural network rather than physics simulation, to predict the motion of a vehicle and changes to a terrain. The neural network is trained using data captured from a high-fidelity non-real-time 3D simulator called Sandbox. Using a trained neural network to drive the 2D simulation provides considerable speed-up over the high-fidelity 3D simulation, allowing behaviour to be simulated in real-time while still capturing the physics of the agents and the environment. Two methods of simulating terrain in Sandbox are explored with results related to performance given for each. Two variants of Alexi are also explored, with results related to neural network training and generalization provided

Modelling and validation of off-road vehicle ride dynamics

Increasing concerns on human driver comfort/health and emerging demands on suspension systems for off-road vehicles call for an effective and efficient off-road vehicle ride dynamics model. This study devotes both analytical and experimental efforts in developing a comprehensive off-road vehicle ride dynamics model. A three-dimensional tire model is formulated to characterize tire–terrain interactions along all the three translational axes. The random roughness properties of the two parallel tracks of terrain profiles are further synthesized considering equivalent undeformable terrain and a coherence function between the two tracks. The terrain roughness model, derived from the field-measured responses of a conventional forestry skidder, was considered for the synthesis. The simulation results of the suspended and unsuspended vehicle models are derived in terms of acceleration PSD, and weighted and unweighted rms acceleration along the different axes at the driver seat location. Comparisons of the model responses with the measured data revealed that the proposed model can yield reasonably good predictions of the ride responses along the translational as well as rotational axes for both the conventional and suspended vehicles. The developed off-road vehicle ride dynamics model could serve as an effective and efficient tool for predicting vehicle ride vibrations, to seek designs of primary and secondary suspensions, and to evaluate the roles of various operating conditions

Creating gameplay mechanics with deformable characters

This paper presents how soft body simulation can create deformable characters and physics-based game mechanics that result in a more varied gameplay experience. A framework was implemented that allows the creation of a fully deformable soft body character within a games application where the simulation model properties could be altered at runtime to create gameplay mechanics based on varying the deformation of the character. The simulation model was augmented to allow appropriate methods of player control that complemented the character design and its ability to deform. It was found that while the implementation of deformation-based mechanics created a more varied gameplay experience, the underlying simulation model allowed for a limited amount of deformation before becoming unstable. The ffectiveness of the framework is demonstrated by the resulting mechanics that are not possible through the use of previous methods

Quantifying the Evolutionary Self Structuring of Embodied Cognitive Networks

We outline a possible theoretical framework for the quantitative modeling of networked embodied cognitive systems. We notice that: 1) information self structuring through sensory-motor coordination does not deterministically occur in Rn vector space, a generic multivariable space, but in SE(3), the group structure of the possible motions of a body in space; 2) it happens in a stochastic open ended environment. These observations may simplify, at the price of a certain abstraction, the modeling and the design of self organization processes based on the maximization of some informational measures, such as mutual information. Furthermore, by providing closed form or computationally lighter algorithms, it may significantly reduce the computational burden of their implementation. We propose a modeling framework which aims to give new tools for the design of networks of new artificial self organizing, embodied and intelligent agents and the reverse engineering of natural ones. At this point, it represents much a theoretical conjecture and it has still to be experimentally verified whether this model will be useful in practice.

Real-time Physics Based Simulation for 3D Computer Graphics

Restoration of realistic animation is a critical part in the area of computer graphics. The goal of this sort of simulation is to imitate the behavior of the transformation in real life to the greatest extent. Physics-based simulation provides a solid background and proficient theories that can be applied in the simulation. In this dissertation, I will present real-time simulations which are physics-based in the area of terrain deformation and ship oscillations. When ground vehicles navigate on soft terrains such as sand, snow and mud, they often leave distinctive tracks. The realistic simulation of such vehicle-terrain interaction is important for ground based visual simulations and many video games. However, the existing research in terrain deformation has not addressed this issue effectively. In this dissertation, I present a new terrain deformation algorithm for simulating vehicle-terrain interaction in real time. The algorithm is based on the classic terramechanics theories, and calculates terrain deformation according to the vehicle load, velocity, tire size, and soil concentration. As a result, this algorithm can simulate different vehicle tracks on different types of terrains with different vehicle properties. I demonstrate my algorithm by vehicle tracks on soft terrain. In the field of ship oscillation simulation, I propose a new method for simulating ship motions in waves. Although there have been plenty of previous work on physics based fluid-solid simulation, most of these methods are not suitable for real-time applications. In particular, few methods are designed specifically for simulating ship motion in waves. My method is based on physics theories of ship motion, but with necessary simplifications to ensure real-time performance. My results show that this method is well suited to simulate sophisticated ship motions in real time applications