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WORLDCOMP'11 Featured Tutorial: Prof. Anthony A. Maciejewski

Last modified 2011-06-18 13:03


Redundant Robots: The Promise of Human-Like Dexterity
Prof. Anthony A. Maciejewski
Fellow of IEEE; Prof. & Head, Department of Electrical & Computer Engineering
Colorado State University, Fort Collins,Colorado, USA

Date: July 19, 2011
Time: 6:00-9:30 PM
Location: Ballroom 2


DESCRIPTION

    The vast majority of robots in use today operate in very structured environments, e.g., in factory assembly lines, and possess only those limited motion capabilities required to perform specific tasks. While these robots can outperform humans in terms of speed, strength, and accuracy for these tasks, they are no match for the dexterity of human motion. Part of a human's inherent advantage over industrial robots is due to the large number of degrees of freedom in the human body. Articulated, i.e., jointed, motion systems that possess more degrees of freedom than the minimum required to perform a specified task are referred to as kinematically redundant. In an effort to mimic the dexterity of biological systems, researchers have built a number of kinematically redundant robotic systems, e.g., anthropomorphic arms, multi-fingered hands, dual-arm manipulators, and walking machines. While these systems vary in their appearance and intended applications, they all require motion control strategies that coordinate large numbers of joints to achieve the high degree of dexterity possible with redundant systems. This talk will discuss the issues that arise when designing such strategies, frequently drawing on the use of the singular value decomposition, including the characterization of redundancy, the quantification of dexterity, and the development of efficient and numerically stable motion control algorithms that simultaneously optimize multiple criteria. In addition, the ability of kinematically redundant robots to sustain component failures and yet still complete an assigned task will addressed, thereby extending the application of robots to environments that are unacceptable or inaccessible to humans.


OBJECTIVES

    This course will enable you to:
      • Understand the issues associated with motion planning for robotic systems
      • Be able to quantify the dexterity of various robotic systems
      • Apply a general control formulation for coordinating the motion of high degree-of-freedom robotic systems for multi-objective optimization
      • Understand how kinematically redundant robotic systems can be designed and operated for failure tolerant behavior.

INTENDED AUDIENCE

    This course is intended for faculty, engineers, scientists, and students who want an overview of motion planning for kinematically redundant robots, i.e., a formal approach for dealing with the coordination of multiple degree-of-freedom systems. It is also useful for those who are considering a career as a robotics engineer.

BIOGRAPHY OF INSTRUCTOR

    Anthony A. (Tony) Maciejewski received the B.S., M.S., and Ph.D. degrees in Electrical Engineering in 1982, 1984, and 1987, respectively, all from The Ohio State University. From 1988 to 2001, he was a Professor of Electrical and Computer Engineering at Purdue University. In 2001, he joined Colorado State University where he is currently the Head of the Department of Electrical and Computer Engineering. He has co-authored over 200 technical publications in the areas of robotics and high-performance computing and served on eight journal editorial boards and over 80 conference program committees. He is a Fellow of IEEE and currently serves on the Board of Governor's for the Systems, Man, and Cybernetics Society and is Vice-President Elect of Financial Activities for the Robotics and Automation Society. A complete up-to-date vita is available at www.engr.colostate.edu/~aam

    Prof. Anthony A. Maciejewski, Head
    Electrical and Computer Engineering Department Colorado State University
    Fort Collins, CO 80523-1373
    Tel: (970) 491-6600
    Fax: (970) 491-2249
    aam@colostate.edu
    http://www.engr.colostate.edu/~aam/

Academic Co-Sponsors
The Berkeley Initiative in Soft Computing (BISC)
University of California, Berkeley, USA

Biomedical Cybernetics Laboratory, HST of Harvard University
Massachusetts Institute of Technology (MIT)

Intelligent Data Exploration and Analysis Laboratory
University of Texas at Austin, Austin, Texas, USA

Collaboratory for Advanced Computing and Simulations (CACS)
University of Southern California, USA

Minnesota Supercomputing Institute
University of Minnesota, USA

Knowledge Management & Intelligent System Center (KMIS)
University of Siegen, Germany

UMIT, Institute of Bioinformatics and Translational Research, Austria
BioMedical Informatics & Bio-Imaging Laboratory
Georgia Institute of Technology and Emory University, Atlanta, Georgia, USA


Hawkeye Radiology Informatics, Department of Radiology, College of Medicine, University of Iowa, Iowa, USA

Supercomputer Software Department (SSD), Institute of Computational Mathematics & Mathematical Geophysics, Russian Academy of Sciences
SECLAB of University of Naples Federico II
University of Naples Parthenope, & Second University of Naples, Italy

Medical Image HPC & Informatics Lab (MiHi Lab)
University of Iowa, Iowa, USA

Intelligent Cyberspace Engineering Lab., ICEL, Texas A&M; University (Com./Texas), USA
Model-Based Engineering Laboratory, University of North Dakota, North Dakota, USA


Corporate Sponsor

Intel Corporation



Altera Corporation

Pico Computing

High Performance Computing for Nanotechnology (HPCNano)

International Society of Intelligent Biological Medicine

World Academy of Biomedical Sciences and Technologies
The International Council on Medical and Care Compunetics
The UK Department for Business, Enterprise & Regulatory Reform
Scientific Technologies Corporation

HoIP - Health without Boundaries


 


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