Towards Human-Induced Vision-Guided Robot Behavior

An appealing alternative to tediously specifying robot behaviors in response to particular image features is to have the robot’s behavior be induced by human decisions made when piloting the robot. This paper presents one promising approach to creating this alternative. A human pilots a camera-equipped robot, which builds a representation of its target environment using Growing Neural Gas (GNG). The robot associates an action with each GNG node based on what the human pilot was doing while the node was active. When running autonomously, the robot chooses the action associated with the node that is the closest match to the current input image. Preliminary results suggest that the approach has potential, but that subsequent alteration of the actions induced for some of the GNG nodes is important for acceptable performance.