Publication Articles



Towards Computer Assisted Crowd Aware Architectural Design

With this work we build upon prevous work in crowd optimization. Leveraging optimization methods previously used to assist users in architectural design tasks. Abstract We present a preliminary exploration of an architectural optimization process towards a computational tool for designing environments (e.g., building floor plans). Using dynamic crowd simulators …

Using synthetic crowds to inform building pillar placements

Abstract We present a preliminary exploration of synthetic crowds towards computational tools for informing the design of environments (e.g., building floor plans). Feedback and automatic design processes are developed from exploring crowd behaviours and metrics derived from simulations of environments in density stressed scenarios, such as evacuations. Computational approaches …

Terrain Adaptive Locomotion Skills using Deep Reinforcement Learning

Abstract Reinforcement learning offers a promising methodology for developing skills for simulated characters, but typically requires working with sparse hand-crafted features. Building on recent progress in deep reinforcement learning (DeepRL), we introduce a mixture of actor-critic experts (MACE) approach that learns terrain-adaptive dynamic locomotion skills using high-dimensional state and terrain …

ACCLMesh: Curvature-Based Navigation Mesh Generation

Evaluating height clearance with the navigation mesh allows agents to walk under a slanted overpass safely. The approach can be integrated into standard navigation and animation systems to simulate thousands of agents on 3D surfaces in real-time. With this work we build upon prevous work to construct navigation meshes. These …