Moving Path Planning Forward

Sturtevant, Nathan R.

doi:10.1007/978-3-642-34710-8_1

Cited by 5 publications

(2 citation statements)

References 11 publications

(8 reference statements)

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“…Path planning is the process of computing an overall path for a character to reach their goal in a manner which accounts for the known static obstacles in the environment. While many aspects of path planning are well understood, the recent work of [Sturtevant 2012] discusses some of the important challenges remaining in the field.…”

Section: Previous Workmentioning

confidence: 99%

Psycho-physical Crowds

Guy

2013

Proceedings of Motion on Games

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Human crowds are becoming an increasingly important component of video games and virtual environments. However, as these virtual worlds become more realistic, the simulation of human crowds must become more sophisticated to keep pace. Much recent work in the field of crowd simulation has focused on improving aspects relating to navigation and collision avoidance in order to create complex, collision free trajectories. However, this paper argues that an equally important aspect of creating believable crowds is simulating aspects beyond navigation such as the internal psychological state of a simulated agent and external physical forces. We also discuss how recently proposed methods can be used to simulate these physical and psychological aspects of crowd simulations while maintaining high-quality, collision free motion.

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Section: Previous Workmentioning

confidence: 99%

Psycho-physical Crowds

Guy

2013

Proceedings of Motion on Games

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“…Given a source s and a target t in a Euclidean plane containing polygonal obstacles, we study Euclidean Shortest Path Problem (ESPP) which is to compute the shortest obstacle avoiding path between s and t. Due to its applications in robotics (Mac et al 2016), indoor location-based services (Cheema 2018) and computer games (Sturtevant 2012b), efficiently computing ESPP has been extensively studied. Some of the most notable works include any-angle pathfinding approaches such as Anya (Harabor et al 2016), navigation-mesh-based techniques such as Polyanya (Cui, Harabor, and Grastien 2017), advanced visibility graph techniques such as hierarchical sparse visibility graph (Oh and Leong 2017), and the techniques based on distance oracles such as End Point Search (EPS) (Shen et al 2020).…”

Section: Introductionmentioning

confidence: 99%

Ultrafast Euclidean Shortest Path Computation Using Hub Labeling

Shen

Cheema

2023

AAAI

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Finding shortest paths in a Euclidean plane containing polygonal obstacles is a well-studied problem motivated by a variety of real-world applications. The state-of-the-art algorithms require finding obstacle corners visible to the source and target, and need to consider potentially a large number of candidate paths. This adversely affects their query processing cost. We address these limitations by proposing a novel adaptation of hub labeling which is the state-of-the-art approach for shortest distance computation in road networks. Our experimental study conducted on the widely used benchmark maps shows that our approach is typically 1-2 orders of magnitude faster than two state-of-the-art algorithms.

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