PhDIn this thesis, the synthesis of a grasping and manipulation controller of the Barrett hand, which
is an archetypal example of a multi-fingered robotic hand, is investigated in some detail. This
synthesis involves not only the dynamic modelling of the robotic hand but also the control
of the joint and workspace dynamics as well as the interaction of the hand with object it is
grasping and the environment it is operating in. Grasping and manipulation of an object by a
robotic hand is always challenging due to the uncertainties, associated with non-linearities of
the robot dynamics, unknown location and stiffness parameters of the objects which are not
structured in any sense and unknown contact mechanics during the interaction of the hand’s
fingers and the object. To address these challenges, the fundamental task is to establish the
mathematical model of the robot hand, model the body dynamics of the object and establish
the contact mechanics between the hand and the object.
A Lagrangian based mathematical model of the Barrett hand is developed for controller implementation.
A physical SimMechanics based model of the Barrett hand is also developed in
MATLAB/Simulink environment. A computed torque controller and an adaptive sliding model
controller are designed for the hand and their performance is assessed both in the joint space
and in the workspace. Stability analysis of the controllers are carried out before developing the
control laws. The higher order sliding model controllers are developed for the position control
assuming that the uncertainties are in place. Also, this controllers enhance the performance by
reducing chattering of the control torques applied to the robot hand.
A contact model is developed for the Barrett hand as its fingers grasp the object in the operating
environment. The contact forces during the simulation of the interaction of the fingers with
the object were monitored, for objects with different stiffness values. Position and force based
impedance controllers are developed to optimise the contact force. To deal with the unknown
stiffness of the environment, adaptation is implemented by identifying the impedance. An evolutionary
algorithm is also used to estimate the desired impedance parameters of the dynamics
of the coupled robot and compliant object.
A Newton-Euler based model is developed for the rigid object body. A grasp map and a hand
Jacobian are defined for the Barrett hand grasping an object. A fixed contact model with
friction is considered for the grasping and the manipulation control. The compliant dynamics of Barrett hand and object is developed and the control problem is defined in terms of the
contact force. An adaptive control framework is developed and implemented for different
grasps and manipulation trajectories of the Barrett hand. The adaptive controller is developed
in two stages: first, the unknown robot and object dynamics are estimated and second, the
contact force is computed from the estimated dynamics. The stability of the controllers is
ensured by applying Lyapunov’s direct method
