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Abstract. This paper introduces a behavior-grounded approach to representing and learning the affordances of tools by a robot. The affordance 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. As a result of this exploratory procedure, the tool representation is grounded in the behavioral and perceptual repertoire of the robot. Furthermore, the representation is autonomously testable and verifiable by the robot as it is expressed in concrete terms (i.e., behaviors) that are directly available to the robot’s controller. The tool representation described here can also be used to solve tool-using tasks by dynamically sequencing the exploratory behaviors which were used to explore the tool based on their expected outcomes. The quality of the learned representation was tested on extension-of-reach tasks with rigid tools.

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Introduction

The ability to use tools is one of the hallmarks of intelligence. Tool use is fundamental to human life and has been for at least the last two million years. We use tools to extend our reach, to amplify our physical strength, to transfer objects and liquids, and to achieve many other everyday tasks. A large number of animals have also been observed to use tools [1]. Some birds, for example, use twigs or cactus pines to probe for larvae in crevices which they cannot reach with their beaks. Sea otters use stones to open hard-shelled mussels. Chimpanzees use stones to crack nuts open and sticks to reach food, dig holes, or attack predators. Orangutans fish for termites with twigs and grass blades. Horses and elephants use sticks to scratch their bodies. These examples suggest that the ability to use tools is an adaptation mechanism used by many organisms to overcome the limitations imposed on them by their anatomy. Despite the widespread use of tools in the animal world, however, studies of autonomous robotic tool use are still rare. There are industrial robots that use tools for tasks such as welding, cutting, and painting, but these operations are carefully scripted by a human programmer. Robot hardware capabilities, however, continue to increase at a remarkable rate. Humanoid robots such as Honda’s Asimo, Sony’s Qrio, and NASA’s Robonaut feature motor capabilities E. Rome et al. (Eds.): Affordance-Based Robot Control, LNAI 4760, pp. 140–158, 2008. c Springer-Verlag Berlin Heidelberg 2008 

Learning the Affordances of Tools Using a Behavior-Grounded Approach

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similar to those of humans. In the near future similar robots will be working side by side with humans in homes, offices, hospitals, and in outer space. It is difficult to imagine how these robots that will look like us, act like us, and live in the same physical environment like us, will be very useful if they are not capable of something so innate to human culture as the ability to use tools. Because of their humanoid “anatomy” these robots undoubtedly will have to use external obj