The Visual Computer

, Volume 28, Issue 12, pp 1209–1227 | Cite as

Parallelized egocentric fields for autonomous navigation

  • Mubbasir KapadiaEmail author
  • Shawn Singh
  • William Hewlett
  • Glenn Reinman
  • Petros Faloutsos
Original Article


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 and has better parallel scalability than a global fields approach. We then use these perception fields to compute a fitness measure for every possible action, defined as an affordance field. The action that has the optimal value in the affordance field is the agent’s steering decision. We propose an extension to a linear space-time prediction model for dynamic collision avoidance and present our parallelization results on multicore systems. We analyze and evaluate our framework using a comprehensive suite of test cases provided in SteerBench and 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.


Affordance Egocentric Steering Space-time planning 



The work in this paper was partially supported by Intel through a Visual Computing grant, and the donation of a 32-core Emerald Ridge system with Xeon processors X7560. In particular, we would like to thank Randi Rost, Scott Buck, and Mitchell Lum from Intel for their support.

Supplementary material

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Copyright information

© Springer-Verlag 2012

Authors and Affiliations

  • Mubbasir Kapadia
    • 1
    • 2
    Email author
  • Shawn Singh
    • 1
    • 4
  • William Hewlett
    • 1
  • Glenn Reinman
    • 1
  • Petros Faloutsos
    • 1
    • 3
  1. 1.University of CaliforniaLos AngelesUSA
  2. 2.University of PennsylvaniaPhiladelphiaUSA
  3. 3.York UniversityTorontoCanada
  4. 4.Google Inc.Mountain ViewUSA

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