Underwater Robots - Gianluca Antonelli.pdf

106 6. Kinematic Control of UVMSs
energy savings or increase of system manipulability. To this purpose the task
priority redundancy resolution technique [195, 210] is well suited in that it allows
the specification of aprimary task which isfulfilled with higher priority
with respect to asecondary task.
Control of end-effector position/orientation can be obtained also with
dynamic control by suitably expressing the mathematical model [255, 256,
285]. This approach, successfully implemented for industrial robots, seems
not to be suitable for UVMSs for two main reasons: first, in underwater
environment the dynamic parameters are usually poorly known; second, the
redundancy of the system is not exploited. Some, approaches, moreover, are
specifically designed for a6-DOFs manipulator only.
By limiting our attention to UVMSs, few papers have addressed the problem
ofinverse kinematics resolution. Reference [237] proposes alocal motion
planner solved in parallel by adistributed search; this provides an iterative
algorithm for an approximate solution. In [20], atask priority approach
has been proposed aimed at fulfilling secondary tasks such asreduction of
fuel consumption, improvement ofsystem manipulability, and obstacle avoidance.
This approach has been further integrated with afuzzy approach
in [24, 25, 26, 29] and itwill be deeply analyzed inthis Chapter. In [249, 250],
asecond-order inverse kinematics approach isdeveloped to reduce the total
hydrodynamic drag forces ofthe system. Simulations results are performed
on a6-link vehicle carrying a3-link manipulator. The same authors also developed
adynamic-based algorithm in [235] that generates the joint trajectories
by taking into account the natural frequencies ofthe two subsystems: vehicle
and manipulator; the task-space trajectory is represented by Fourier series
and suitably projected on the subsystems. Reference [252] reports an adaptive
dynamic controller that uses, as reference trajectory, the output of afirstorder
inverse kinematics algorithm aimed at satisfying joint limits. In [163],
the Authors develop two cost functions devoted at increase the manipulability
and respect the joint limits to be used inatask priority approach.
In [160, 161], agenetic algorithm-based motion planner is proposed; dividing
the workspace in cells, the presence ofobstacles and the minimization of the
drag forces are taken into consideration. Finally, in[73] adistributed kinematic
control was developed for coordination ofamulti-manipulator system
mounted under afree-flying base such as, e.g., an underwater vehicle; the
case of apossible under-actuated vehicle is explicitly taken into account.
6.2 Kinematic Control
Amanipulation task isusually given in terms of position and orientation
trajectory of the end effector. The objective ofkinematic control is to find
suitable vehicle/joint trajectories η ( t ), q ( t ) that correspond to a desired
end-effector trajectory η ee,d( t ). The output ofthe inverse kinematics algorithm
η r ( t ), q r ( t )provides the reference values to the control law ofthe