modular and reusable software architectures for motion programming;
(ii) motion control laws that take into account the limited computing
resources; (iii) online rollover prevention in high speed mobile
manipulation based on the Lie group dynamics formulation;
(i) I describe a unified framework for task planning, motion planning,
and control of wheeled mobile manipulators. This relates to the setting
up of a (low-level, control level) motion primitives database which is
user-friendly and reusable and aims to combine with the higher level
components for reasoning and intelligence, etc. As a result, the
integrated, hierarchical programming environment for autonomous robots
is developed.
(ii) In the literature of human motor control, it is well known that
humans select the optimal motion among diverse feasible motions between
initial pose and goal pose. The various optimum criteria (e.g., minimum
energy, minimum jerk, minimum torque change, etc.) are evaluated to
explain the theory of human motor coordination. I suggest the minimum
attention that takes into account the cost of control as a paradigm for
human-like movement generation of a robot.
(iiI) I briefly introduce the Lie group dynamics formulation, and as an
application of this, a real-time dynamic balancing control law for
wheeled mobile manipulators is proposed. For the dynamic stability
criterion of zero moment point, a correct formulation which makes the
definition of a potential function mathematically consistent and
physically plausible is developed. Also, I derive efficient recursive
algorithms for computing exact analytic gradients of the zero moment
point functions. This leads to marked improvements in convergence and
computational performance over existing approaches.