Publications (3)0 Total impact
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Conference Proceeding: Interactive online multimodal association for internal concept building in humanoids
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ABSTRACT: In this paper we report the results of our research on learning and developing cognitive systems. The results are integrated into ALIS 3, our Autonomous Learning and Interacting System version 3 realized the humanoid robot ASIMO. The results presented address crucial issues in autonomously acquiring mental concepts in artifacts. The major contributions are the following: We researched distributed learning in various modalities in which the local learning decisions mutually support each other. Associations between the different modalities (speech, vision, behavior) are learnt online, thus addressing the issue of grounding semantics. The data from the different modalities is uniformly represented in a hybrid data representation for global decisions and local novelty detection. On the behavior generation side proximity sensor driven reflexive grasping and releasing have been integrated with a planning approach based on whole body motion control. The feasibility of the chosen approach is demonstrated in interactive experiments with the integrated system. The system interactively learns visually defined classes like ??left??, ??right??, ??up??, ??down??, ??large??, ??small??, learns corresponding auditory labels and creates associations linking the auditory labels to the visually defined classes or basic behaviors for building internal concepts.Humanoid Robots, 2009. Humanoids 2009. 9th IEEE-RAS International Conference on; 01/2010 -
Conference Proceeding: Teaching a humanoid robot: Headset-free speech interaction for audio-visual association learning
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ABSTRACT: Based on inspirations from infant development we present a system which learns associations between acoustic labels and visual representations in interaction with its tutor. The system is integrated with a humanoid robot. Except for a few trigger phrases to start learning all acoustical representations are learned online and in interaction. Similar, for the visual domain the clusters are not predefined and fully learned online. In contrast to other interactive systems the interaction with the acoustic environment is solely based on the two microphones mounted on the robots head. In this paper we give an overview on all key elements of the system and focus on the challenges arising from the headset-free learning of speech labels. In particular we present a mechanism for auditory attention integrating bottom-up and top-down information for the segmentation of the acoustic stream. The performance of the system is evaluated based on offline tests of individual parts of the system and an analysis of the online behavior.Robot and Human Interactive Communication, 2009. RO-MAN 2009. The 18th IEEE International Symposium on; 11/2009 -
Conference Proceeding: Organizing multimodal perception for autonomous learning and interactive systems
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ABSTRACT: A stable perception of the environment is a crucial prerequisite for researching the learning of semantics from human-robot interaction and also for the generation of behavior relying on the robots perception. In this paper, we propose several contributions to this research field. To organize visual perception the concept of proto-objects is used for the representation of scene elements. These proto-objects are created by several different sources and can be combined to provide the means for interactive autonomous behavior generation. They are also processed by several classifiers, extracting different visual properties. The robot learns to associate speech labels with these properties by using the outcome of the classifiers for online training of a speech recognition system. To ease the combination of visual and speech classifier outputs, a necessity for the online training and basis for future learning of semantics, a common representation for all classifier results is used. This uniform handling of multimodal information provides the necessary flexibility for further extension. We will show the feasibility of the proposed approach by interactive experiments with the humanoid robot ASIMO.Humanoid Robots, 2008. Humanoids 2008. 8th IEEE-RAS International Conference on; 01/2009
