TUTORIAL SESSION

Redundant Robots: The Promise of Human-Like Dexterity

Prof. Anthony A. Maciejewski
Colorado State University, USA
aam@colostate.edu

Duration

3 Hours

Abstract

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.

Target 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.

Qualifications of the Instructor(s)

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