Tamara Rogers

ISAC: foundations in human-humanoid interaction

The authors describe their humanoid robotic system, ISAC (Intelligent Soft-Arm Control), and their approach to human-humanoid interaction (HHI). They present a software architecture called the Intelligent Machine Architecture (IMA) and two high-level agents (the Human agent and the Self agent) within their HHI framework.

TOWARD SOCIALLY INTELLIGENT SERVICE ROBOTS

In the Intelligent Robotics Laboratory at Vanderbilt University, we seek to develop service robots with a high level of social intelligence and interactivity. In order to achieve this goal, we have identified two main issues for research. The first issue is how to achieve a high level of interaction between the human and the robot. This has lead to the formulation of our philosophy of Human Directed Local Autonomy (HuDL), a guiding principle for research, design, and implementation of service robots. The motivation for integrating humans into a service robot system is to take advantage of human intelligence and skill. Human intelligence can be used to interpret robot sensor data, eliminating computationally expensive and possibly error-prone automated analyses. Human skill is a valuable resource for trajectory and path planning as well as for simplifying the search process. In this article, we present our plans for integrating humans into a service robot system. We present our paradigm for human-robot int...

Development of a cognitive model of humans in a multi-agent framework for human-robot interaction

Partnership between a person and a robot could be enhanced if the robot were intelligent enough to recognize an individual and adapt its behavior. During the last several years, we have been developing such an intelligent robot in the form of a humanoid robot called ISAC. In this paper, we will describe a user-centric multi-agent framework for robot control and human-robot interaction and one cognitive agent called the Human Agent. Additionally, a second cognitive agent and short- and long-term memory structures for the robot are briefly described. Finally, three applications are shown to illustrate how ISAC will interact effectively with humans.

Enhancing the classification accuracy of IP geolocation

The ability to localize Internet hosts is appealing for a range of applications from online advertising to localizing cyber attacks. Recently, measurement-based approaches have been proposed to accurately identify the location of Internet hosts. These approaches typically produce erroneous results due to measurement errors. In this paper, we propose an Enhanced Learning Classifier approach for estimating the geolocation of Internet hosts with increased accuracy. Our approach extends an exisiting machine learning based approach by extracting six features from network measurements and implementing a new landmark selection policy. These enhancements allow us to mitigate problems with measurement errors and reduces average error distance in estimating location of Internet hosts. To demonstrate the accuracy of our approach, we evaluate the performance on network routers using ping measurements from PlanetLab nodes with known geographic placement. Our results demonstrate that our approach improves average accuracy by geolocating internet hosts 100 miles closer to the true geographic location versus prior measurement-based approaches.

The human agent: a work in progress toward human-humanoid interaction

At the Intelligent Robotics Laboratory of the Center for Intelligent Systems at Vanderbilt University, we have been developing a humanoid system called ISAC, (Intelligent Soft-Arm Control), over the past several years. As people work with a humanoid system, the interaction should be natural and robust. Our framework for human-humanoid interaction (HHI) considers various aspects of HHI and the paper presents information about the development of one key element of this system: the human agent.

Multi-agent system for a human-friendly robot

At the Center for Intelligent Systems, we are working on human robot interaction (HRI). We present our approach for HRI. Our goals for HRI are to allow the human to influence the robots actions in some way and acquire feedback about the robots internal state. Additionally, we would like the robot to confirm the humans input and request the humans assistance if necessary. To achieve our goals, we are developing two intelligent agents: the human agent and the self agent. The human agent encapsulates what the robot knows about the human. The self agent maintains knowledge about the internal state of the robot and communicates with the human. We performed a preliminary demonstration of the system, in which the human could have limited conversation with the robot, a dual-armed humanoid. This limited conversation included commands to the robot and queries about the robots abilities and internal state.

Towards a human–robot symbiotic system

Abstract Partnership between a person and a robot could be simplified if the robot were intelligent enough to understand human intentions and perform accordingly. During the last decade, we have been developing such an intelligent robot called ISAC. Originally, ISAC was designed to assist the physically disabled, but gradually became a test bed for more robust human–robot teaming (see http://eecs.vanderbilt.edu/CIS/ ). In this paper, we will describe a framework for human–robot interaction, a multi-agent based robot control architecture, and short- and long-term memory structures for the robot brain. Two applications will illustrate how ISAC interacts with the human.

Modeling human-robot interaction for intelligent mobile robotics

The focus of this paper is the design of a system for human-robot interaction that allows the robot(s) to interact with people in modes that are common to them. The results are a designed architecture for a system to support human-robot interaction. The structure includes a monitoring agent for detecting the presence of people, an interaction agent to handle choosing robot behaviors that are used for interacting, both socially and for task completion, and a capability agent which is responsible for the robots abilities and actions.

Designing for human‐robot symbiosis

For the past ten years, the Intelligent Robotics Laboratory (IRL) at Vanderbilt University has been developing service robots that interact naturally, closely and safely with human beings. Two main issues for research have arisen from this prior work. The first is how to achieve a high level of interaction between the human and robot. The result has been the philosophy of human directed local autonomy (HuDL), a guiding principle for research, design, and implementation of service robots. The human‐robot relationship we seek to achieve is symbiotic in the sense that both the human and the robot work together to achieve goals, for example as aids to the elderly or disabled. The second issue is the general problem of system integration, with a specific focus on integrating humans into the service robotic system. This issue has led to the development of the Intelligent Machine Architecture (IMA), a novel software architecture specifically designed to simplify the integration of the many diverse algorithms, sensors, and actuators necessary for intelligent interactive service robots.

Attention Mechanisms for Social Engagements of Robots with Multiple People

Social robots need to have special human-robot interaction (HRI) systems to be accepted by people as natural partners. This paper first describes a multiple agent-based architecture designed to support HRI and then introduces an engagement mechanism based on attention distraction. The monitoring agent is a high-level agent that monitors and evaluates the surrounding environment and people. The interaction agent is another high-level agent that facilitates the seamless interaction between the robot and humans. The capability agent is a compound agent within the robot that is responsible for the robots abilities and actions. The use of multiple HRI modalities in the engagement mechanism provides means for people to solicit the robots attention while allowing the robot to ignore the distraction if it has recently become engaged with something else. The system has been successfully implemented and tested on a Pioneer 3-AT mobile robot