Tutelage and Collaboration for Humanoid Robots

The hypothesis for this research is that applying the Human Computer Interaction (HCI) concepts of using multiple modalities, dialog management, context, and semantics to Human Robot Interaction (HRI) will improve the performance of Instruction Based Learning (IBL) compared to only using speech. We tested the hypothesis by simulating a domestic robot that can be taught to clean a house using a multi-modal interface. We used a method of semantically integrating the inputs from multiple modalities and contexts that multiplies a confidence score for each input by a Fusion Weight, sums the products, and then uses the input with the highest product sum. We developed an algorithm for determining the Fusion Weights. We concluded that different modalities, contexts, and modes of dialog management impact human robot interaction; however, which combination is better depends on the importance of the accuracy of learning what is taught versus the succinctness of the dialog between the user and the robot.iii

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“…Speech + Field of Vision (another type of modality) 6. Speech + Head Nodding (another type of modality) 7. Speech + All…”

Section: Methodsmentioning

confidence: 99%

“…Breazeal et al looked at IBL as collaboration between a human and a robot, instead of the classical teacher-student relationship [7,52]. Their research platform is Learning Theory [84], which theorizes that a child learns a new skill from a teacher through the process of scaffolding.…”

Section: Learning By Reinforcementmentioning

confidence: 99%

Human Robot Interaction Through Semantic Integration of Multiple Modalities, Dialog Management, and Contexts

Johnson

Agah

2009

Int J of Soc Robotics

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“…It can make eye contact and can direct its attention to salient objects. A more complex communication robot is Leonardo, developed by Breazeal et al [1]. It has 65 degrees of freedom to animate the eyes, facial expressions, the ears, and to move its head and arms.…”

Section: Related Workmentioning

confidence: 99%

“…More and more research groups worldwide develop complex machines with a human-like body plan and human-like senses [1], [2], [3]. One of the most important motivations for many humanoid projects is that such robots could be capable of intuitive, multimodal interaction with people.…”

Section: Introductionmentioning

confidence: 99%

The humanoid museum tour guide Robotinho

Faber

Bennewitz

Eppner

et al. 2009

RO-MAN 2009 - The 18th IEEE International Symposium on Robot and Human Interactive Communication

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Abstract-Wheeled tour guide robots have already been deployed in various museums or fairs worldwide. A key requirement for successful tour guide robots is to interact with people and to entertain them. Most of the previous tour guide robots, however, focused more on the involved navigation task than on natural interaction with humans. Humanoid robots, on the other hand, offer a great potential for investigating intuitive, multimodal interaction between humans and machines. In this paper, we present our mobile full-body humanoid tour guide robot Robotinho. We provide mechanical and electrical details and cover perception, the integration of multiple modalities for interaction, navigation control, and system integration aspects. The multimodal interaction capabilities of Robotinho have been designed and enhanced according to the questionnaires filled out by the people who interacted with the robot at previous public demonstrations. We present experiences we have made during experiments in which untrained users interacted with the robot.

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“…The robot's behaviors are not subject to deliberate decisions but are implemented by if-then rules based on the redundancy of the interlocutor's attentional behavior and the communication mode. Breazeal et al [20] work on a robot which is capable of rich social interactions and is provided with joint attention capabilities modeled as a collaborative process. The robot has an attention system which determines its attentional focus by calculating saliency values for all perceived objects.…”

Section: Related Workmentioning

confidence: 99%

Toward Alignment with a Virtual Human - Achieving Joint Attention

Pfeiffer-Leßmann

Wachsmuth

Lecture Notes in Computer Science

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Abstract. Alignment forms the basis of successful communication. It can be seen as the most efficient means for action coordination of cooperating agents, covering adaptation processes operating without an explicit exchange of information states. One critical condition of alignment consists of joint attention. We present work on equipping a virtual human with the capability of reaching joint attention with its human interlocutor. On the one hand, mechanisms to detect the human's focus of attention are employed. On the other hand, basic cognitive as well as intentional processes underlying the phenomenon of joint attention are incorporated in our agent's cognitive architecture. In this context, a dynamic working memory and a partner model accounting for theory of mind and intentionality are crucial constituents.

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Tutelage and Collaboration for Humanoid Robots

Cited by 120 publications

References 35 publications

Human Robot Interaction Through Semantic Integration of Multiple Modalities, Dialog Management, and Contexts

Human Robot Interaction Through Semantic Integration of Multiple Modalities, Dialog Management, and Contexts

The humanoid museum tour guide Robotinho

Toward Alignment with a Virtual Human - Achieving Joint Attention

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