Navigation and steering for autonomous virtual humans

Kapadia, Mubbasir; Badler, Norman I.

doi:10.1002/wcs.1223

Cited by 25 publications

(10 citation statements)

References 70 publications

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“…The second layer (navigation) implements the way-finding behavior of the agents. On this layer, Kapadia [38] differentiates between navigation and steering. While navigation addresses the aspect of finding a collision-free global path, steering ensures that the agents are able to move along the global path by avoiding static and dynamic obstacles.…”

Section: Operational Level Motor Layer Locomotion Layermentioning

confidence: 99%

Modeling Dynamic Decision-Making of Virtual Humans

Handel

2016

Systems

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Imagine a person visiting an urban event. At each moment in time, the person has to weigh up different possible actions and make consecutive decisions. For instance, a person might be hungry or thirsty and would therefore like to go somewhere to eat or to drink, or a person might need to go to the toilet and thus go searching for the restrooms. Other possible desires might be to go dancing or to have a rest due to exhaustion. All these examples can be seen in the context of dynamic decision-making. To be able to implement the dynamic decision-making of virtual humans living their lives in a persistent microworld, an advanced concept to solve this-in artificial intelligence research commonly called action selection problem-is required. This article focuses on an novel approach to model the activation of motivations-as an attempt to answer the recurring question of the virtual humans "What to do next?". The novelty is to use System Dynamics, in general defined as a top-down simulation approach, from the bottom-up inside each instance of the agent population and to implement an action selection mechanism on the basis of this methodology. This approach enables us to model the dynamic decision-making of the virtual humans with stocks and flows resulting in nonlinear motivation evolution. A case study in the context of an urban event documents the application of this innovative method.

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Section: Operational Level Motor Layer Locomotion Layermentioning

confidence: 99%

Modeling Dynamic Decision-Making of Virtual Humans

Handel

2016

Systems

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“…There exists a wealth of research [1], [2], [3] that separately addresses the problems of character animation, steering and path-finding, and behavior authoring, with many open challenges [4] that need to be addressed in an effort to arrive at a common standard for simulating autonomous virtual humans for the next generation of interactive virtual world applications.…”

Section: Related Workmentioning

confidence: 99%

ADAPT: The Agent Developmentand Prototyping Testbed

Shoulson

Marshak

Kapadia

et al. 2014

IEEE Trans. Visual. Comput. Graphics

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We present ADAPT, a flexible platform for designing and authoring functional, purposeful human characters in a rich virtual environment. Our framework incorporates character animation, navigation, and behavior with modular interchangeable components to produce narrative scenes. The animation system provides locomotion, reaching, gaze tracking, gesturing, sitting, and reactions to external physical forces, and can easily be extended with more functionality due to a decoupled, modular structure. The navigation component allows characters to maneuver through a complex environment with predictive steering for dynamic obstacle avoidance. Finally, our behavior framework allows a user to fully leverage a character's animation and navigation capabilities when authoring both individual decision-making and complex interactions between actors using a centralized, event-driven model.

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“…Depending upon application requirements, a variety of navigation approaches have been proposed for autonomous agents, some of which are described in the succeeding text.…”

Section: Related Workmentioning

confidence: 99%

“…There exists a large body of work in path planning research , with many proposed solutions that balance path optimality and computational efficiency. These approaches produce trajectories that minimize total distance traveled and use reactive policies to account for constraints (e.g., collision avoidance and inter‐agent relationships).…”

Section: Introductionmentioning

confidence: 99%

Planning approaches to constraint‐aware navigation in dynamic environments

Ninomiya

Kapadia

Shoulson

et al. 2014

Computer Animation & Virtual

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Path planning is a fundamental problem in many areas, ranging from robotics and artificial intelligence to computer graphics and animation. Although there is extensive literature for computing optimal, collision-free paths, there is relatively little work that explores the satisfaction of spatial constraints between objects and agents at the global navigation layer. This paper presents a planning framework that satisfies multiple spatial constraints imposed on the path. The type of constraints specified can include staying behind a building, walking along walls, or avoiding the line of sight of patrolling agents. We introduce two hybrid environment representations that balance computational efficiency and search space density to provide a minimal, yet sufficient, discretization of the search graph for constraint-aware navigation. An extended anytime dynamic planner is used to compute constraint-aware paths, while efficiently repairing solutions to account for varying dynamic constraints or an updating world model. We demonstrate the benefits of our method on challenging navigation problems in complex environments for dynamic agents using combinations of hard and soft, attracting and repelling constraints, defined by both static obstacles and moving obstacles.Keywords path planning, spatial constraints, navigation, anytime dynamic planning, potential fields Disciplines Computer Sciences | Engineering | Graphics and Human Computer Interfaces CommentsThe preprint version title is Constraint-Aware Navigation in Dynamic Environments; it was published in its final form as Planning Approaches to Constraint-Aware Navigation in Dynamic Environments.This journal article is available at ScholarlyCommons: http://repository.upenn.edu/hms/139 Constraint-Aware Navigation in Dynamic Environments AbstractPath planning is a fundamental problem in many areas ranging from robotics and artificial intelligence to computer graphics and animation. While there is extensive literature for computing optimal, collision-free paths, there is little work that explores the satisfaction of spatial constraints between objects and agents at the global navigation layer. This paper presents a planning framework that satisfies multiple spatial constraints imposed on the path. The type of constraints specified could include staying behind a building, walking along walls, or avoiding the line of sight of patrolling agents. We introduce a hybrid environment representation that balances computational efficiency and discretization resolution, to provide a minimal, yet sufficient discretization of the search graph for constraintaware navigation. An extended anytime-dynamic planner is used to compute constraint-aware paths, while efficiently repairing solutions to account for dynamic constraints. We demonstrate the benefits of our method on challenging navigation problems in complex environments for dynamic agents using combinations of hard and soft constraints, attracting and repelling constraints, on static obstacles and moving obstacles.

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Navigation and steering for autonomous virtual humans

Cited by 25 publications

References 70 publications

Modeling Dynamic Decision-Making of Virtual Humans

Modeling Dynamic Decision-Making of Virtual Humans

ADAPT: The Agent Developmentand Prototyping Testbed

Planning approaches to constraint‐aware navigation in dynamic environments

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