Publication View

Behavior-Grounded Representation of Tool Affordances (2005)

Abstract
This paper introduces a novel approach to representing and learning tool affordances by a robot. The tool representation described here uses a behavior-based approach to ground the tool affordances in the behavioral repertoire of the robot. The representation is learned during a behavioral babbling stage in which the robot randomly chooses different exploratory behaviors, applies them to the tool, and observes their effects on environmental objects. The paper shows how the autonomously learned affordance representation can be used to solve tool-using tasks by dynamically sequencing the exploratory behaviors based on their expected outcomes. The quality of the learned representation was tested on extension-of-reach tool-using tasks.

Publication details
Download http://hdl.handle.net/1853/20655
Publisher Georgia Institute of Technology
Contributors Georgia Institute of Technology
Repository Georgia Tech's Institutional Repository ()
Keywords Autonomous tool use, Behavior-based robotics, Learning of affordances, Tool affordances
Type Paper
Language English