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University of Bridgeport Department of Computer Science and Engineering Robotics, Intelligent Sensing and Control RISC Laboratory. Robotics, Intelligent Sensing and Control Lab (RISC). Faculty, Staff and Students. Faculty: Prof. Tarek Sobh. Staff:. Lab Manager: Abdelshakour Abuzneid

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robotics intelligent sensing and control lab risc

University of Bridgeport

Department of Computer Science and Engineering

Robotics, Intelligent Sensing and Control

RISC Laboratory

Robotics, Intelligent Sensing and Control Lab (RISC)

faculty staff and students
Faculty, Staff and Students

Faculty: Prof. Tarek Sobh

Staff:

  • Lab Manager: Abdelshakour Abuzneid
  • Tech. Assistant: Matanya Elchanani

Students:

  • Raul Mihali, Gerald Lim, Ossama Abdelfattah, Wei Zhang, Radesh Kanniganti, Hai-Poh Teoh, Petar Gacesa.
objectives and ongoing projects robotics and prototyping
Objectives and Ongoing ProjectsRobotics and Prototyping
  • Prototyping and synthesis of controllers, simulators, and monitors, calibration of manipulators and singularity determination for generic robots.
    • Real time controlling/simulating/monitoring of manipulators.
    • Kinematics and Dynamics hardware for multi-degree of freedom manipulators.
objectives and ongoing projectsrobotics and prototyping
Objectives and Ongoing ProjectsRobotics and Prototyping
  • Concurrent optimal engineering design of manipulator prototypes.
  • Component-Based Dynamics simulation for robotics manipulators.
  • Active kinematic (and Dynamic) calibration of generic manipulators
  • Manipulator design based on task specification
  • Kinematic Optimization of manipulators.
  • Singularity Determination for manipulators.
objectives and ongoing projects robotics and prototyping cont
Objectives and Ongoing Projects Robotics and Prototyping (cont.)
  • Service robotics (tire-changing robots)
  • Web tele-operated control of robotic manipulators (for Distance Learning too).
  • Algorithms for manipulator workspace generation and visualization in the presence of obstacles.
objectives and ongoing projects sensing
Objectives and Ongoing ProjectsSensing
  • Precise Reverse Engineering and inspection
  • Feature-based reverse engineering and inspection of machine parts.
  • Computation of manufacturing tolerances from sense data
  • Algorithms for uncertainty computation from sense data
  • Unifying tolerances across sensing, design and manufacturing
  • Tolerance representation and determination for inspection and manufacturing.
  • Parallel architectures for the realization of uncertainty from sensed data
  • Reverse engineering applications in dentistry.
  • Parallel architectures for robust motion and structure recovery from uncertainty in sensed data.
  • Active sensing under uncertainty.
objectives and ongoing projects hybrid and autonomous systems
Objectives and Ongoing ProjectsHybrid and Autonomous systems
  • Uncertainty modeling, representing, controlling, and observing interactive robotic agents in unstructured environments.
  • Modeling and verification of distributed control schemes for mobile robots.
  • Sensor-based distributed control schemes (for mobile robots).
  • Discrete event modeling and control of autonomous agents under uncertainty.
  • Discrete event and hybrid systems in robotics and automation
  • Framework for timed hybrid systems representation, synthesis, and analysis
prototyping environment for robot manipulators

University of Bridgeport

Department of Computer Science and Engineering

Robotics, Intelligent Sensing and Control

RISC Laboratory

Prototyping Environment for Robot Manipulators

Prof. Tarek Sobh

to design a robot manipulator the following tasks are required
To design a robot manipulator, the following tasks are required:
  • Specify the tasks and the performance requirements.
  • Determine the robot configuration and parameters.
  • Select the necessary hardware components.
  • Order the parts.
  • Develop the required software systems (controller, simulator, etc...).
  • Assemble and test.
the required sub systems for robot manipulator prototyping
The required sub-systems for robot manipulator prototyping:
  • Design
  • Simulation
  • Control
  • Monitoring
  • Hardware selection
  • CAD/CAM modeling
  • Part Ordering
  • Physical assembly and testing
manipulator workspace generation and visualization in the presence of obstacles

University of Bridgeport

Department of Computer Science and Engineering

Robotics, Intelligent Sensing and Control

RISC Laboratory

Manipulator Workspace Generation and Visualization in the Presence of Obstacles

Prof. Tarek Sobh

industrial inspection and reverse engineering

University of Bridgeport

Department of Computer Science and Engineering

Robotics, Intelligent Sensing and Control

RISC Laboratory

Industrial Inspection and Reverse Engineering

Prof. Tarek Sobh

what is reverse engineering

What is reverse engineering?

Reconstruction of an object from sensed information.

why reverse engineering
Why reverse engineering?
  • Applications:
    • Legal technicalities.
    • Unfriendly competition.
    • Shapes designed off-line.
    • Post-design changes.
    • Pre-CAD designs.
    • Lost or corrupted information.
    • Isolated working environment.
    • Medical.
  • Interesting problem
  • Findings useful.
recovering 3 d uncertainties from sensory measurements for robotics applications

University of Bridgeport

Department of Computer Science and Engineering

Robotics, Intelligent Sensing and Control

RISC Laboratory

Recovering 3-D Uncertainties from Sensory Measurements for Robotics Applications

Prof. Tarek Sobh

refining image motion
Refining Image Motion
  • Mechanical limitations
  • Geometrical imitations
tolerancing and other projects

University of Bridgeport

Department of Computer Science and Engineering

Robotics, Intelligent Sensing and Control

RISC Laboratory

Tolerancing and Other Projects

Prof. Tarek Sobh

problem
Problem

A unifying framework for tolerance specification, synthesis, and analysis across the domains of industrial inspection using sensed data, CAD design, and manufacturing.

solution
Solution

We guide our sensing strategies based on the manufacturing process plans for the parts that are to be inspected and define, compute and analyze the tolerances of the parts based on the uncertainty in the sensed data along the different toolpaths of the sensed part.

contribution
Contribution

We believe that our new approach is the best way to unify tolerances across sensing, CAD, and CAM, as it captures the manufacturing knowledge of the parts to be inspected, as opposed to just CAD geometric representations.

sensing under uncertainty for mobile robots

University of Bridgeport

  • Department of Computer Science and Engineering
  • Robotics, Intelligent Sensing and Control
  • RISC Laboratory

Sensing Under Uncertainty for Mobile Robots

Prof. Tarek Sobh

abstract sensor model we can view the sensory system using three different levels of abstraction
Abstract Sensor ModelWe can view the sensory system using three different levels of abstraction
  • Dumb Sensor: returns raw data without any interpretation.
  • Intelligent Sensor: interprets the raw data into an event.
  • Controlling sensor: can issue commands based on the received events.
discrete event and hybrid systems

University of Bridgeport

Department of Computer Science and Engineering

Robotics, Intelligent Sensing and Control

RISC Laboratory

Discrete Event and Hybrid Systems

Prof. Tarek Sobh

the problem hybrid systems that contain a mix of
The ProblemHybrid systems that contain a “mix” of:
  • Continuous Parameters and Functions.
  • Discrete Parameters and Functions.
  • Chaotic Behavior.
  • Symbolic Aspects.

Are hard to define, model, analyze, control, or observe !!

slide48

Discrete Event Dynamic Systems (DEDS) are dynamic systems (typically asynchronous) in which state transitions are triggered by the occurrence of discrete events in the system.

Modified DEDS might be suitable for representing hybrid systems.

eventual goal develop the ultimate framework and tools
Eventual GoalDevelop the Ultimate Framework and Tools !!
  • Controlling and observing co-operating moving agents (robots).
  • A CMM Controller for sensing tasks.
  • Multimedia Synchronization.
  • Intelligent Sensing (for manufacturing, autonomous agents, etc...).
  • Hardwiring the framework in hardware (with Ganesh).
applications
Applications
  • Networks and Communication Protocols
  • Manufacturing (sensing, inspection, and assembly)
  • Economy
  • Robotics (cooperating agents)
  • Highway traffic control
  • Operating systems
  • Concurrency control
  • Scheduling
  • Assembly planning
  • Real-Time systems
  • Observation under uncertainty
  • Distributed Systems
other projects
Other Projects
  • Modeling and recovering uncertainty in 3-D structure and motion
  • Dynamics and kinematics generation and analysis for multi-DOF robots
  • Active observation and control of a moving agent under uncertainty
  • Automation for genetics application
  • Manipulator workspace generation in the presence of obstacles
  • Turbulent flow analysis using sensors within a DES framework
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