Introduces a revolutionary, quadratic-programming based approach to
solving long-standing problems in motion planning and control of
redundant manipulators
This book describes a novel quadratic programming approach to solving
redundancy resolutions problems with redundant manipulators. Known as
``QP-unified motion planning and control of redundant manipulators''
theory, it systematically solves difficult optimization problems of
inequality-constrained motion planning and control of redundant
manipulators that have plagued robotics engineers and systems designers
for more than a quarter century.
An example of redundancy resolution could involve a robotic limb with
six joints, or degrees of freedom (DOFs), with which to position an
object. As only five numbers are required to specify the position and
orientation of the object, the robot can move with one remaining DOF
through practically infinite poses while performing a specified task. In
this case redundancy resolution refers to the process of choosing an
optimal pose from among that infinite set. A critical issue in robotic
systems control, the redundancy resolution problem has been widely
studied for decades, and numerous solutions have been proposed. This
book investigates various approaches to motion planning and control of
redundant robot manipulators and describes the most successful strategy
thus far developed for resolving redundancy resolution problems.
- Provides a fully connected, systematic, methodological, consecutive,
and easy approach to solving redundancy resolution problems
- Describes a new approach to the time-varying Jacobian matrix
pseudoinversion, applied to the redundant-manipulator kinematic
control
- Introduces The QP-based unification of robots' redundancy resolution
- Illustrates the effectiveness of the methods presented using a large
number of computer simulation results based on PUMA560, PA10, and
planar robot manipulators
- Provides technical details for all schemes and solvers presented, for
readers to adopt and customize them for specific industrial
applications
Robot Manipulator Redundancy Resolution is must-reading for advanced
undergraduates and graduate students of robotics, mechatronics,
mechanical engineering, tracking control, neural dynamics/neural
networks, numerical algorithms, computation and optimization, simulation
and modelling, analog, and digital circuits. It is also a valuable
working resource for practicing robotics engineers and systems designers
and industrial researchers.
