Egocentric affordance fields in pedestrian steering

Mubbasir Kapadia, Shawn Singh, William Hewlett, Petros Faloutsos

Research output: Chapter in Book/Report/Conference proceedingConference contribution

88 Scopus citations

Abstract

In this paper we propose a general framework for local path-planning and steering that can be easily extended to perform high-level behaviors. Our framework is based on the concept of affordances - the possible ways an agent can interact with its environment. Each agent perceives the environment through a set of vector and scalar fields that are represented in the agent's local space. This egocentric property allows us to efficiently compute a local space-time plan. We then use these perception fields to compute a fitness measure for every possible action, known as an affordance field. The action that has the optimal value in the affordance field is the agent's steering decision. Using our framework, we demonstrate autonomous virtual pedestrians that perform steering and path planning in unknown environments along with the emergence of high-level responses to never seen before situations.

Original languageEnglish (US)
Title of host publicationProceedings of I3D 2009
Subtitle of host publicationThe 2009 ACM SIGGRAPH Symposium on Interactive 3D Graphics and Games
Pages215-223
Number of pages9
DOIs
StatePublished - 2009
Externally publishedYes
Event2009 ACM SIGGRAPH Symposium on Interactive 3D Graphics and Games, I3D 2009 - Boston, MA, United States
Duration: Feb 27 2009Mar 1 2009

Publication series

NameProceedings of I3D 2009: The 2009 ACM SIGGRAPH Symposium on Interactive 3D Graphics and Games

Other

Other2009 ACM SIGGRAPH Symposium on Interactive 3D Graphics and Games, I3D 2009
Country/TerritoryUnited States
CityBoston, MA
Period2/27/093/1/09

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Computational Theory and Mathematics
  • Computer Graphics and Computer-Aided Design
  • Human-Computer Interaction

Keywords

  • Affordance
  • Egocentric
  • Space-time planning
  • Steering

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