Optimization in simulations of human movement planning

Anders Eriksson; Krister Svanberg

doi:10.1002/nme.3143

Optimization in simulations of human movement planning

International Journal for Numerical Methods in Engineering ◽

10.1002/nme.3143 ◽

2011 ◽

Vol 87 (12) ◽

pp. 1127-1147 ◽

Cited By ~ 1

Author(s):

Anders Eriksson ◽

Krister Svanberg

Keyword(s):

Human Movement ◽

Movement Planning

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Limits to human movement planning in tasks with asymmetric gain landscapes

Journal of Vision ◽

10.1167/6.1.5 ◽

2006 ◽

Vol 6 (1) ◽

pp. 5 ◽

Cited By ~ 24

Author(s):

Shih-Wei Wu ◽

Julia Trommershäuser ◽

Laurence T. Maloney ◽

Michael S. Landy

Keyword(s):

Human Movement ◽

Movement Planning

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Movement Behavior for Soldier Agents on a Virtual Battlefield

Presence Teleoperators & Virtual Environments ◽

10.1162/105474603322391622 ◽

2003 ◽

Vol 12 (4) ◽

pp. 387-410 ◽

Cited By ~ 5

Author(s):

Douglas A. Reece

Keyword(s):

Search Algorithm ◽

Human Movement ◽

Movement Planning ◽

Movement Behavior ◽

Behavior Model ◽

Topological Map ◽

Hybrid Search ◽

Individual Agent ◽

Planning And Control ◽

And Control

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.

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