Stam: a framework for spatio-temporal affordance maps

Riccio, Francesco, Capobianco, Roberto, Hanheide, Marc and Nardi, Daniele (2016) Stam: a framework for spatio-temporal affordance maps. In: International Workshop on Modelling and Simulation for Autonomous Systems, 15 - 16 June 2016, Rome, Italy.

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Item Type:Conference or Workshop contribution (Paper)
Item Status:Live Archive


A�ordances have been introduced in literature as action op-
portunities that objects o�er, and used in robotics to semantically rep-
resent their interconnection. However, when considering an environment
instead of an object, the problem becomes more complex due to the
dynamism of its state. To tackle this issue, we introduce the concept
of Spatio-Temporal A�ordances (STA) and Spatio-Temporal A�ordance
Map (STAM). Using this formalism, we encode action semantics re-
lated to the environment to improve task execution capabilities of an
autonomous robot. We experimentally validate our approach to support
the execution of robot tasks by showing that a�ordances encode accurate
semantics of the environment.

Keywords:mobile robotics, Artificial intelligence
Subjects:G Mathematical and Computer Sciences > G700 Artificial Intelligence
H Engineering > H671 Robotics
Divisions:College of Science > School of Computer Science
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ID Code:24851
Deposited On:26 Oct 2016 08:55

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