Real-time multi-agent path planning on arbitrary surfaces

Abstract

Figure 1: Four different views of a scene where agents navigate on the surface of a complex triangular mesh. Agents are color-coded by their different objectives. The system supports path planning of multiple agents on non-planar surfaces, and imposes no limitation on the domain mesh, such as this mesh with more than one genus. AbstractPath planning is an active topic in the literature, and efficient navigation over non-planar surfaces is an open research question. In this work we present a novel technique for navigation of multiple agents over arbitrary triangular domains. The proposed solution uses a fast hierarchical computation of geodesic distances over triangular meshes to allow interactive frame rates, and a GPU-based collision avoidance technique to guide individual agents. Unlike most previous work, the method imposes no limitations on the surface over which the agents are moving, and can naturally deal with non-planar meshes of arbitrary genus and curvature. Moreover, the implementation is a hybrid CPU/GPU algorithm that explores the current trend of increasing the number of CPU cores and GPU programmability. This approach exploits the best qualities in each processor, thus achieving very high performance.

ACCLMesh: curvature‐based navigation mesh generation

“…The work in used discrete geodesics to simulate crowds on continuous 3D surfaces but was limited to meshes without edges or sharp curves. Ricks and Egbert present a whole surface approach for navigation and collision avoidance for crowds on 3D surfaces, while accepting the input mesh as fully traversable.…”

Coordinated Crowd Simulation With Topological Scene Analysis

“…Field‐based methods control the movement of characters using a scalar field over the space of a scene. Geometric distance fields are used to provide plans for crowds on arbitrary surfaces [TSO*10]. Although these plans are globally constructed, they do not take into account the positions and plans of other characters, and hence are still prone to congestion.…”

Dynamic search on the GPU

“…Distance fields can be used to solve 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) November 3-7, 2013. Tokyo, Japan 978-1-4673-6358-7/13/$31.00 ©2013 IEEE multi-agent planning on the GPU [13]. Crowd simulation techniques [14], [15] exploit GPU hardware to accelerate local collision avoidance for crowds but do not handle global planning.…”