
doi: 10.1002/cav.1511
ABSTRACTModern virtual environments can contain a variety of characters and traversable regions. Each character may have different preferences for the traversable region types. Pedestrians may prefer to walk on sidewalks, but they may occasionally need to traverse roads and dirt paths. By contrast, wild animals might try to stay in forest areas, but they are able to leave their protective environment when necessary. This paper presents a novel path planning method named Modified Indicative Routes and Navigation (MIRAN) that takes a character's region preferences into account. Given an indicative route as a rough estimation of a character's preferred route, MIRAN efficiently computes a visually convincing path that is smooth, keeps clearance from obstacles, avoids unnecessary detours, and allows local changes to avoid other characters. To the best of our knowledge, MIRAN is the first path planning method that supports the aforementioned features while using an exact representation of the navigable space. Experiments show that with our approach, a wide range of different character behaviors can be simulated. It also overcomes problems that occur in previous path planning methods such as the Indicative Route Method. The resulting paths are well suited for real‐time simulations and gaming applications. Copyright © 2013 John Wiley & Sons, Ltd.
heterogeneous virtual environments, Scientific, autonomous agents, path planning
heterogeneous virtual environments, Scientific, autonomous agents, path planning
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 19 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
