Flocks, herds and schools: A distributed behavioral model
SIGGRAPH '87 Proceedings of the 14th annual conference on Computer graphics and interactive techniques
An algorithmic approach to some problems in terrain navigation
Artificial Intelligence - Special issue on geometric reasoning
Situationally driven local navigation for mobile robots
Situationally driven local navigation for mobile robots
The weighted region problem: finding shortest paths through a weighted planar subdivision
Journal of the ACM (JACM)
Gross motion planning—a survey
ACM Computing Surveys (CSUR)
Cooperative Mobile Robotics: Antecedents and Directions
Autonomous Robots
Multiagent Systems: A Survey from a Machine Learning Perspective
Autonomous Robots
What Are Plans For?
Movement simulation and management of cooperating objects in CGF systems: a case study
KES-AMSTA'10 Proceedings of the 4th KES international conference on Agent and multi-agent systems: technologies and applications, Part I
Limited-Damage A*: A path search algorithm that considers damage as a feasibility criterion
Knowledge-Based Systems
Formation preserving path finding in 3-D terrains
Applied Intelligence
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We have developed a movement behavior model for soldier agents who populate a virtual battlefield environment. Whereas many simulations have addressed human movement behavior before, none of them has comprehensively addressed realistic military movement at individual and unit levels. To design an appropriate movement behavior model, we found it necessary to • elaborate all of the requirements on movement from the military tasks of interest, • define a behavior architecture that encompasses all required movement tasks, • select appropriate movement planning and control approaches in light of the requirements, and • implement the planning and control algorithms with novel enhancements to achieve satisfactory results.The breadth of requirements in this problem domain makes simple behavior architectures inadequate and prevents any single planning approach from easily accomplishing all tasks. In our behavior architecture, a hierarchy of tasks is distributed over unit leaders and unit members. For movement planning, we use an A* search algorithm on a hybrid search space comprising a two-dimensional regular grid and a topological map; the plan produced is a series of waypoints annotated with posture and speed changes. Individuals control movement with reactive steering behaviors. The result is a system that can realistically plan and execute a variety of unit and individual agent movement tasks on a virtual battlefield.