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Tennessee State UniversityTennessee State UniversityCollege of EngineeringCollege of Engineering
ENGINEERING RESEARCH INSTITUTE (ERI)ENGINEERING RESEARCH INSTITUTE (ERI)Interdisciplinary Research in RoboticsInterdisciplinary Research in Robotics
Intelligent Tactical Mobility Research Laboratory (ITMRL)Intelligent Tactical Mobility Research Laboratory (ITMRL)Intelligent Control Systems Laboratory (ICS)Intelligent Control Systems Laboratory (ICS)
Center for Neural Engineering (CNE)Center for Neural Engineering (CNE)Computer and information systems Laboratory (CISE)Computer and information systems Laboratory (CISE)
Mohan J. Malkani, Ph.D. (Director)Mohan J. Malkani, Ph.D. (Director)(615) 963-5400 Fax: (615) 963-5397(615) 963-5400 Fax: (615) 963-5397
Research Projects in Robotics: Past and Present
Tele-Robotics jointly with Caltech funded by NSF (1997-2000)Tele-Robotics jointly with Caltech funded by NSF (1997-2000)
Originally Funded by US Army TACOM, Warren, MI, under two research Originally Funded by US Army TACOM, Warren, MI, under two research grant contracts:grant contracts:
1. Development of an Integrated High-level Mobility Controller for Virtual Tandem Robotic Vehicles, DAAE07-98-C-0029, (1997-2000)
2. Deliberative, Reactive, and Adaptive Task Planning of Intelligent Cooperative Mobile Robots, DAAE07-01-C-L-065, (2001-2002) Embodiment of intelligent behaviors on mobile robots using fuzzy-genetic Embodiment of intelligent behaviors on mobile robots using fuzzy-genetic
algorithms, funded by NASA/Ames Research Center (2000-2004)algorithms, funded by NASA/Ames Research Center (2000-2004) Funded by DARPA Through Penn State Applied Research “Sensor Funded by DARPA Through Penn State Applied Research “Sensor
surveillance” under MURI-ESP Research Project, surveillance” under MURI-ESP Research Project, DAAD19-01-1-0504,DAAD19-01-1-0504, (2002-2003)(2002-2003)
Funded by NASA/JPL, FAR Investigator Program, “Visual Telerobotic Task Funded by NASA/JPL, FAR Investigator Program, “Visual Telerobotic Task Planning of Cooperative Mobile Robots”, Planning of Cooperative Mobile Robots”,
(2003-2006)(2003-2006)
Development of Advanced Control schemes that enable tactical team Development of Advanced Control schemes that enable tactical team cooperation of Intelligent Autonomous robots effectively and efficiently.cooperation of Intelligent Autonomous robots effectively and efficiently.
Test and evaluate performance of advanced control schemes under Test and evaluate performance of advanced control schemes under different operational conditions and different sensory data modality different operational conditions and different sensory data modality experimentally using high-fidelity computer generated simulation and experimentally using high-fidelity computer generated simulation and physical robotic test beds.physical robotic test beds.
Technical Competency Areas Included:Technical Competency Areas Included: Behavior-based Distributed control of Cooperative Mobile Robots.Behavior-based Distributed control of Cooperative Mobile Robots. Sensory data and image processing and fusion for fault tolerance Sensory data and image processing and fusion for fault tolerance
control of intelligent robots. control of intelligent robots. Advanced control schemes based Soft Computing techniques, (Neural Advanced control schemes based Soft Computing techniques, (Neural
Networks, Fuzzy Logic, Genetic Algorithms, …).Networks, Fuzzy Logic, Genetic Algorithms, …). High-fidelity world perception modeling of robotic systems.High-fidelity world perception modeling of robotic systems. Man-machine development for Visual Teleoperation and Telerobotic Man-machine development for Visual Teleoperation and Telerobotic
control of Cooperative Robots. control of Cooperative Robots.
Research Focus Areas
Developed various behavior-based schemes for Developed various behavior-based schemes for intelligent deliberative, reactive, and adaptive intelligent deliberative, reactive, and adaptive task planning of cooperative robots.task planning of cooperative robots.
Developed various image processing techniques Developed various image processing techniques for visual localization and target tracking of for visual localization and target tracking of robots.robots.
Applied different soft computing methods for Applied different soft computing methods for target pattern recognition and classification.target pattern recognition and classification.
Developed FMCell comprehensive robotic Developed FMCell comprehensive robotic simulation software for the purpose of man-simulation software for the purpose of man-machine interface development.machine interface development.
State-of-the-art physical robotic test bed State-of-the-art physical robotic test bed consisting of twelve heterogeneous robots.consisting of twelve heterogeneous robots.
Embodiment of intelligent behaviors on mobile Embodiment of intelligent behaviors on mobile robots using fuzzy-genetic algorithmsrobots using fuzzy-genetic algorithms
Theoretical and Experimental Theoretical and Experimental Research Capabilities Research Capabilities
Image Image EnhancementEnhancement
Robot Identification ByRobot Identification ByColor Feature DetectionColor Feature Detection
ImageImageWindowingWindowing
Robots Pose Detection Robots Pose Detection Using Neural NetsUsing Neural Nets
Image CapturedImage CapturedBy Anchor RobotBy Anchor Robot
HD: 2.0LD: 2.6RO:-45.0ID : 3
HD: 6.1LD:-2.2Ro:-90.0ID : 1
HD: 9.3LD: 2.9RO:-82.5ID : 2
RobotsRobotsLocalizationLocalization
BackgroundBackgroundEliminationElimination
NoiseNoiseReductionReduction
RobotsRobotsIsolationIsolation
Image Image EnhancementEnhancementImage Image EnhancementEnhancement
Robot Identification ByRobot Identification ByColor Feature DetectionColor Feature DetectionRobot Identification ByRobot Identification ByColor Feature DetectionColor Feature Detection
ImageImageWindowingWindowingImageImageWindowingWindowing
Robots Pose Detection Robots Pose Detection Using Neural NetsUsing Neural NetsRobots Pose Detection Robots Pose Detection Using Neural NetsUsing Neural Nets
Image CapturedImage CapturedBy Anchor RobotBy Anchor RobotImage CapturedImage CapturedBy Anchor RobotBy Anchor Robot
HD: 2.0LD: 2.6RO:-45.0ID : 3
HD: 6.1LD:-2.2Ro:-90.0ID : 1
HD: 9.3LD: 2.9RO:-82.5ID : 2
RobotsRobotsLocalizationLocalization
HD: 2.0LD: 2.6RO:-45.0ID : 3
HD: 6.1LD:-2.2Ro:-90.0ID : 1
HD: 9.3LD: 2.9RO:-82.5ID : 2
RobotsRobotsLocalizationLocalization
BackgroundBackgroundEliminationEliminationBackgroundBackgroundEliminationElimination
NoiseNoiseReductionReductionNoiseNoiseReductionReduction
RobotsRobotsIsolationIsolationRobotsRobotsIsolationIsolation
Intelligent Man-Machine InterfaceIntelligent Man-Machine Interface Interactive Component Based Architecture for Interactive Component Based Architecture for
rapid task deployment of cooperative robots.rapid task deployment of cooperative robots. Image and sensory data processing and analysis Image and sensory data processing and analysis
capability for intelligent control of autonomous capability for intelligent control of autonomous robots.robots.
Soft computing capability for deliberative, Soft computing capability for deliberative, reactive, and adaptive development of behavior-reactive, and adaptive development of behavior-based robot tactical schemes.based robot tactical schemes.
3D modeling and simulation tools for world 3D modeling and simulation tools for world perception modeling and visualization of perception modeling and visualization of cooperative mobile robots. cooperative mobile robots.
Built-in TCP/IP wireless communication Built-in TCP/IP wireless communication protocols for distributed client/server-based protocols for distributed client/server-based control of remotely operating robots.control of remotely operating robots.
Experimental human-robot interactionExperimental human-robot interaction
Robotics ResearchRobotics Research
Human-Robot InteractionIntelligent Control Systems
TeleroboticsIntelligent User Interfaces
Multi-Robot CooperationInteroperability
Software Architectures
• Human-Robot Interaction– Over the Internet; Via PDAs; Via Speech– Via cellular phones (speech integrated) – Human detection, recognition, and localization– Social behavior modeling Interoperability for
Robotics– Programming language and operating system
independent software architecture• Intelligent User Interface Design
– Adaptive - mission aware– Multiple users – multiple robots
• Heterogeneous Multi-Robot Cooperation– Behavior-based approach
Robotics ResearchRobotics Research
The Human Agent System
• The Human Agent is a virtual agent that serves as an internal active representation of people in the robot’s environment.
•As a As a representation,representation, it is able to detect, represent and monitor people. The it is able to detect, represent and monitor people. The description description activeactive is used, much as in describing active perception vision is used, much as in describing active perception vision systems [Bajcsy 1987], to indicate that the system can take action to make its systems [Bajcsy 1987], to indicate that the system can take action to make its representation richer.representation richer.
Human DetectionAgent (motion)
Human DetectionAgent (sound)
AffectEstimationAgent
Human IdentificationAgent (face)
Human IdentificationAgent (voice)
Human Database
IdentificationAgent
Human AffectAgent
ObserverAgent
Monitoring Agent
Human Intention
Agent
SocialAgent
Interaction Agent
Human Agent
To Self Agent
Sensory EgoSphere (SES) for Mobile Robots• Peters redefined the
Sensory EgoSphere as a sparse spatiotemporally indexed short term memory (STM).
• Structure: a variable density geodesic dome.
• Nodes: links to data structures and files.
• Indexed by azimuth, elevation and time.
• Searchable by location and content.
images sonar
laserPeters, R. A. II, K. E. Hambuchen, K. Kawamura, and D. M. Wilkes, “The Sensory Ego-Sphere as
a Short-Term Memory for Humanoids”, Proc. IEEE-RAS Int’l. Conf. on Humanoid Robots, pp. 451-459, Waseda University, Tokyo, Japan, 22-24 Nov. 2001.
Experimental Design
• 2 training tasks with the original and enhanced interface
• 2 teleoperation tasks with the enhanced and orignal interface.
Telepresence Software Architecture (Over Internet)
Robot Control Programs
Internet Control (ServerSide)
Internet Control (Client Side)
TCP/IP (Internet)
USER
SERVERS
API
Hardware
HumanCommander
RobotCommand
er
Audio Command
s
Soldiers
Speech Recognition
TCP/IPInternet
Research Motivations (Consumer Tele-presence)
MANAGER
Robot-1 Grabs an Image
Process (NN-Fuzzy)
Grab
Robot-2 Grabs an Image
Process (NN-Fuzzy)
Image Image
Grab
Robot-3 Grabs an Image
Process (NN-Fuzzy)
Image
Grab
Final Decision (Fuzzy Logic)
Fuzzy Decision-2Fuzzy Decision-3
Fuzzy Decision-1
System Architecture
Research Motivations (Development of Robot Behaviors, NASA, Phase-I)FIRBA Implementation
Abstracts beeSoft: Complex API protocols are hidden
Object Oriented: Abstraction, reuse by inheritance.
Perception Sharing: Common perceptions can be shared
Action Suggestions: Arbitration through MAL, fuzzy inference and De-fuzzification.
Independent BehaviorsOverall Software Architecture.
LEVEL 1 BEHAVIORS
LEVEL 0 BEHAVIORS
SONARHANDLING
SONARCLASS
ODOMETERHANDLING
ODOMETERCLASS
SONAR PERCEPTIONS
TARGETHANDLING
TARGETCLASS
PATHHANDLING
PATHCLASS
TARGET PERCEPTIONS
MOTIONPRIMITI-
VES
Research Motivations (Development of Robot Behaviors, NASA, Phase-I)
SENSORS
Pre-Perception Processing
Perception Capabilities
Behaviors.
Action Capabilities
Action Execution
ACTUATORS
The FIRBA architecture.
FIRBA – Robot Control System
Complexity -• Robustness• Multiple Sensors• Multiple Methods• Integration• Incremental Development• Software
This complexity is handled by system decomposition in terms of :
-- functional units-- behavioral units