Organizational Unit:

Mobile Robot Laboratory

Permanent Link

https://hdl.handle.net/1853/70779

Parent Organization

Organizational Unit

College of Computing

ArchiveSpace Name Record

https://finding-aids.library.gatech.edu/agents/corporate_entities/1110

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Publication Search Results

Now showing 1 - 10 of 67

Robotic Discovery of the Auditory Scene

(Georgia Institute of Technology, 2007) Martinson, Eric ; Schultz, Alan

In this work, we describe an autonomous mobile robotic system for finding and investigating ambient noise sources in the environment. Motivated by the large negative effect of ambient noise sources on robot audition, the long-term goal is to provide awareness of the auditory scene to a robot, so that it may more effectively act to filter out the interference or re-position itself to increase the signal-to-noise ratio. Here, we concentrate on the discovery of new sources of sound through the use of mobility and directed investigation. This is performed in a two-step process. In the first step, a mobile robot first explores the surrounding acoustical environment, creating evidence grid representations to localize the most influential sound sources in the auditory scene. Then in the second step, the robot investigates each potential sound source location in the environment so as to improve the localization result, and identify volume and directionality characteristics of the sound source. Once every source has been investigated, a noise map of the entire auditory scene is created for use by the robot in avoiding areas of loud ambient noise when performing an auditory task.
Analyzing Social Situations for Human-Robot Interaction

(Georgia Institute of Technology, 2007) Wagner, Alan R. ; Arkin, Ronald C.

This paper presents an algorithm for analyzing social situations within a robot. We contribute a method that allows the robot to use information about the situation to select interactive behaviors. This work is based on interdependence theory, a social psychological theory of interaction and interpersonal situation analysis. Experiments demonstrate the utility of the information provided by the situation analysis algorithm and of the value of this method for guiding robot interaction. We conclude that the situation analysis algorithm offers a viable, principled, and general approach to explore interactive robotics problems.
Multi-Method Learning and Assimilation

(Georgia Institute of Technology, 2007) Takamuku, Shinya ; Arkin, Ronald C.

Considering the wide range of possible behaviors to be acquired for domestic robots, applying a single learning method is clearly insufficient. In this paper, we propose a new strategy for behavior acquisition for domestic robots where the behaviors are acquired using multiple differing learning methods that are subsequently incorporated into a common behavior selection system, enabling them to be performed in appropriate situations. An example implementation of this strategy applied to the entertainment humanoid robot QRIO is introduced and the results are discussed.
Adaptive Teams of Autonomous Aerial and Ground Robots for Situational Awareness

(Georgia Institute of Technology, 2007) Arkin, Ronald C. ; Endo, Yoichiro ; Chaimowicz, Luiz ; Cowley, Anthony ; Grocholsky, Ben ; Hsieh, Mong-ying A. ; Jung, Boyoon ; Keller, James F. ; Kumar, Vijay ; MacKenzie, Douglas Christopher ; Sukhatme, Gaurav S. ; Taylor, Camillo J. ; Wolf, Denis F.

In this paper, we report on the integration challenges of the various component technologies developed towards the establishment of a framework for deploying an adaptive system of heterogeneous robots for urban surveillance. In our integrated experiment and demonstration, aerial robots generate maps that are used to design navigation controllers and plan missions for the team. A team of ground robots constructs a radio signal strength map that is used as an aid for planning missions. Multiple robots establish a mobile, ad-hoc communication network that is aware of the radio signal strength between nodes and can adapt to changing conditions to maintain connectivity. Finally, the team of aerial and ground robots is able to monitor a small village, and search for and localize human targets by the color of the uniform, while ensuring that the information from the team is available to a remotely located human operator. The key component technologies and contributions include (a) mission speci cation and planning software; (b) exploration and mapping of radio signal strengths in an urban environment; (c) programming abstractions and composition of controllers for multi-robot deployment; (d) cooperative control strategies for search, identi cation, and localization of targets; and (e) three-dimensional mapping in an urban setting.
Governing Lethal Behavior: Embedding Ethics in a Hybrid Deliberative/Reactive Robot Architecture

(Georgia Institute of Technology, 2007) Arkin, Ronald C.

This article provides the basis, motivation, theory, and design recommendations for the implementation of an ethical control and reasoning system potentially suitable for constraining lethal actions in an autonomous robotic system so that they fall within the bounds prescribed by the Laws of War and Rules of Engagement. It is based upon extensions to existing deliberative/reactive autonomous robotic architectures, and includes recommendations for (1) post facto suppression of unethical behavior, (2) behavioral design that incorporates ethical constraints from the onset, (3) the use of affective functions as an adaptive component in the event of unethical action, and (4) a mechanism in support of identifying and advising operators regarding the ultimate responsibility for the deployment of such a system.
On the Ethical Quandaries of a Practicing Roboticist: A First-Hand Look

(Georgia Institute of Technology, 2007) Arkin, Ronald C.

Robotics has progressed substantially over the last 20 years, moving from simple proof-of-concept experimental research to developing market and military technologies that have significant ethical consequences. This paper provides the reflections of a roboticist on current research directions within the field and the social implications associated with its conduct.
Modeling Cross-Sensory and Sensorimotor Correlations to Detect and Localize Faults in Mobile Robots

(Georgia Institute of Technology, 2007) Kira, Zsolt

We present a novel framework for learning crosssensory and sensorimotor correlations in order to detect and localize faults in mobile robots. Unlike traditional fault detection and identification schemes, we do not use a priori models of fault states or system dynamics. Instead, we utilize additional information and possible source of redundancy that mobile robots have available to them, namely a hierarchical graph representing stages of sensory processing at multiple levels of abstractions and their outputs. We learn statistical models of correlations between elements in the hierarchy, in addition to the control signals, and use this to detect and identify changes in the capabilities of the robot. The framework is instantiated using Self-Organizing Maps, a simple unsupervised learning algorithm. Results indicate that the system can detect sensory and motor faults in a mobile robot and identify their cause, without using a priori models of the robot or its fault states.
Modeling Robot Differences by Leveraging a Physically Shared Context

(Georgia Institute of Technology, 2007) Kira, Zsolt ; Long, Kathryn

Knowledge sharing, either implicit or explicit, is crucial during development as evidenced by many studies into the transfer of knowledge by teachers via gaze following and learning by imitation. In the future, the teacher of one robot may be a more experienced robot. There are many new difficulties, however, with regard to knowledge transfer among robots that develop embodiment-specific knowledge through individual solo interaction with the world. This is especially true for heterogeneous robots, where perceptual and motor capabilities may differ. In this paper, we propose to leverage similarity, in the form of a physically shared context, to learn models of the differences between two robots. The second contribution we make is to analyze the cost and accuracy of several methods for the establishment of the physically shared context with respect to such modeling. We demonstrate the efficacy of the proposed methods in a simulated domain involving shared attention of an object.
Lethality and Autonomous Robots: An Ethical Stance

(Georgia Institute of Technology, 2007) Arkin, Ronald C. ; Moshkina, Lilia

This paper addresses a difficult issue confronting the designers of intelligent robotic systems: their potential use of lethality in warfare. As part of an ARO-funded study, we are currently investigating the points of view of various demographic groups, including researchers, regarding this issue, as well as developing methods to engineer ethical safeguards into their use in the battlefield.
From Deliberative to Routine Behaviors: a Cognitively-Inspired Action Selection Mechanism for Routine Behavior Capture

(Georgia Institute of Technology, 2006-11-06) Chernova, Sonia ; Arkin, Ronald C.

Long-term human-robot interaction, especially in the case of humanoid robots, requires an adaptable and varied behavior base. In this work we present a method for capturing, or learning, sequential tasks by transferring serial behavior execution from deliberative to routine control. The incorporation of this approach leads to natural development of complex and varied behaviors, with lower demands for planning, coordination and resources. We demonstrate how this process can be performed autonomously as part of the normal function of the robot, without the need for an explicit learning stage or user guidance. The complete implementation of this algorithm on the Sony QRIO humanoid robot is described.